A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data

Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distr...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Bioinformatics Ročník 29; číslo 2; s. 189 - 196
Hlavní autoři:	Teschendorff, Andrew E., Marabita, Francesco, Lechner, Matthias, Bartlett, Thomas, Tegner, Jesper, Gomez-Cabrero, David, Beck, Stephan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	England Oxford University Press 15.01.2013
Témata:	Algorithms Bias Bioinformatics Deoxyribonucleic acid DNA Methylation Mathematical models Methylation Neoplasms - genetics Normal Distribution Nucleic Acid Probes - chemistry Oligonucleotide Array Sequence Analysis - methods Original Papers Quantiles Strategy Transformations
ISSN:	1367-4803, 1367-4811, 1367-4811, 1460-2059
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs. Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform. Availability: BMIQ is freely available from http://code.google.com/p/bmiq/. Contact: a.teschendorff@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online
AbstractList	The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs.MOTIVATIONThe Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs.Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform.RESULTSHere we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform.BMIQ is freely available from http://code.google.com/p/bmiq/.AVAILABILITYBMIQ is freely available from http://code.google.com/p/bmiq/.a.teschendorff@ucl.ac.ukCONTACTa.teschendorff@ucl.ac.ukSupplementary data are available at Bioinformatics online.SUPPLEMENTARY INFORMATIONSupplementary data are available at Bioinformatics online. Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs.Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform.Availability: BMIQ is freely available from http://code.google.com/p/bmiq/.Contact: a.teschendorff super(c)l.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs. Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform. Availability: BMIQ is freely available from http://code.google.com/p/bmiq/. Contact: a.teschendorff@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs. Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform. BMIQ is freely available from http://code.google.com/p/bmiq/. a.teschendorff@ucl.ac.uk Supplementary data are available at Bioinformatics online. Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs. Results: Here we propose a novel model-based intra-array normalization strategy for 450 k data, called BMIQ (Beta MIxture Quantile dilation), to adjust the beta-values of type2 design probes into a statistical distribution characteristic of type1 probes. The strategy involves application of a three-state beta-mixture model to assign probes to methylation states, subsequent transformation of probabilities into quantiles and finally a methylation-dependent dilation transformation to preserve the monotonicity and continuity of the data. We validate our method on cell-line data, fresh frozen and paraffin-embedded tumour tissue samples and demonstrate that BMIQ compares favourably with two competing methods. Specifically, we show that BMIQ improves the robustness of the normalization procedure, reduces the technical variation and bias of type2 probe values and successfully eliminates the type1 enrichment bias caused by the lower dynamic range of type2 probes. BMIQ will be useful as a preprocessing step for any study using the Illumina Infinium 450 k platform. Availability: BMIQ is freely available from http://code.google.com/p/bmiq/. Contact: a.teschendorff@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online
Author	Teschendorff, Andrew E. Bartlett, Thomas Marabita, Francesco Lechner, Matthias Gomez-Cabrero, David Tegner, Jesper Beck, Stephan
AuthorAffiliation	1 Statistical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK, 2 Department of Medicine, Unit of Computational Medicine, Centre for Molecular Medicine, Karolinska Institute, Solna 171 76, Stockholm, Sweden and 3 Medical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK
AuthorAffiliation_xml	– name: 1 Statistical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK, 2 Department of Medicine, Unit of Computational Medicine, Centre for Molecular Medicine, Karolinska Institute, Solna 171 76, Stockholm, Sweden and 3 Medical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK
Author_xml	– sequence: 1 givenname: Andrew E. surname: Teschendorff fullname: Teschendorff, Andrew E. – sequence: 2 givenname: Francesco surname: Marabita fullname: Marabita, Francesco – sequence: 3 givenname: Matthias surname: Lechner fullname: Lechner, Matthias – sequence: 4 givenname: Thomas surname: Bartlett fullname: Bartlett, Thomas – sequence: 5 givenname: Jesper surname: Tegner fullname: Tegner, Jesper – sequence: 6 givenname: David surname: Gomez-Cabrero fullname: Gomez-Cabrero, David – sequence: 7 givenname: Stephan surname: Beck fullname: Beck, Stephan
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/23175756$$D View this record in MEDLINE/PubMed http://kipublications.ki.se/Default.aspx?queryparsed=id:126019884$$DView record from Swedish Publication Index (Karolinska Institutet)
BookMark	eNqNkk1v1DAQhiNURD_gJ4B85BLqbydCQlqVr5UquMDZsh1na-rYW9sBisR_x222FcsBOHnked53ZjRz3ByEGGzTPEXwBYI9OdUuujDGNKniTD7VJfMOPmiOEOGipR1CB_cxJIfNcc5fIIQMMv6oOcQECSYYP2p-roC2RbWT-17mZMHVrEJx3oJwY-3dj2ofA5hsuYgDqPWAiSlZU1zYgG2K2oLBZrcJQDuVgQtg7f08uaDAOowuuHkClEFwCV5_WN3aXPvFclBFPW4ejspn-2T3njSf3775dPa-Pf_4bn22Om8N61BpyThSixkeuDCw0x3TZjA9hBRZZAnVsIPj0AuMMSKGc4p6qOnAKNMDGzulyEnTLr75m93OWm6Tm1S6llE5ufu6rJGVjBAMUeVfLXzNTHYwNpSk_J5sPxPchdzEr5IwykXPqsHznUGKV7PNRU4uG-u9CjbOWSIuEKW96P4DJZjgivbi3ygWhBOIaF_RZ79PcN_63eYr8HIBTIo5JztK48rtZupAzksE5c2dyf07k8udVTX7Q31X4O-6Xzss4Q8
CitedBy_id	crossref_primary_10_1371_journal_pone_0269105 crossref_primary_10_3389_fnins_2023_1198243 crossref_primary_10_1038_s41598_017_13099_4 crossref_primary_10_1186_s13148_015_0053_9 crossref_primary_10_1016_j_biopsych_2022_06_020 crossref_primary_10_1186_s13059_023_03114_5 crossref_primary_10_1016_j_ecoenv_2023_115544 crossref_primary_10_1007_s11060_022_04047_y crossref_primary_10_1080_15592294_2018_1543503 crossref_primary_10_1038_ncomms7326 crossref_primary_10_1007_s00439_023_02609_2 crossref_primary_10_1038_s41408_022_00715_4 crossref_primary_10_1186_s12974_023_02781_2 crossref_primary_10_1038_ncomms13555 crossref_primary_10_1158_2159_8290_CD_13_0349 crossref_primary_10_1242_bio_058222 crossref_primary_10_1093_eep_dvac004 crossref_primary_10_1186_s13293_021_00381_4 crossref_primary_10_1186_s43682_024_00027_7 crossref_primary_10_1289_EHP10118 crossref_primary_10_3389_fpubh_2022_1069685 crossref_primary_10_1371_journal_pone_0314014 crossref_primary_10_1080_15592294_2016_1146853 crossref_primary_10_1016_j_yexcr_2018_06_034 crossref_primary_10_2217_epi_2018_0049 crossref_primary_10_1016_j_molmet_2015_12_004 crossref_primary_10_1186_s13148_025_01839_7 crossref_primary_10_1136_annrheumdis_2020_219152 crossref_primary_10_2217_epi_2018_0042 crossref_primary_10_1186_s12864_020_07186_6 crossref_primary_10_1186_s13148_017_0320_z crossref_primary_10_1038_ncomms5361 crossref_primary_10_3390_biomedicines9010013 crossref_primary_10_1016_j_heliyon_2023_e23244 crossref_primary_10_1371_journal_pone_0155554 crossref_primary_10_1038_s41380_020_00968_0 crossref_primary_10_1136_jnnp_2023_332889 crossref_primary_10_1080_15622975_2023_2198595 crossref_primary_10_3390_toxics9120338 crossref_primary_10_1186_s12879_025_11181_1 crossref_primary_10_1002_cam4_451 crossref_primary_10_1016_j_csbj_2024_05_015 crossref_primary_10_2217_epi_2018_0037 crossref_primary_10_1186_s13148_018_0541_9 crossref_primary_10_3389_fphar_2020_620811 crossref_primary_10_3389_fnins_2022_858049 crossref_primary_10_1186_s13148_023_01516_7 crossref_primary_10_1371_journal_pgen_1004418 crossref_primary_10_1155_2018_8608327 crossref_primary_10_1080_19490976_2024_2363012 crossref_primary_10_1186_s13072_016_0074_4 crossref_primary_10_1080_15592294_2016_1192736 crossref_primary_10_1093_hmg_ddw072 crossref_primary_10_1186_s13148_019_0635_z crossref_primary_10_1289_EHP3849 crossref_primary_10_3389_fonc_2025_1585450 crossref_primary_10_1038_s41467_024_54110_7 crossref_primary_10_3389_fpsyt_2022_892302 crossref_primary_10_1038_s41598_018_33238_9 crossref_primary_10_1007_s13273_019_00068_3 crossref_primary_10_3390_biomedicines11010134 crossref_primary_10_1002_ajhb_23488 crossref_primary_10_1007_s00439_024_02659_0 crossref_primary_10_5646_ch_2025_31_e28 crossref_primary_10_1093_nar_gkac503 crossref_primary_10_1177_11769351251324545 crossref_primary_10_1016_j_psychres_2022_114789 crossref_primary_10_1038_s41598_018_34003_8 crossref_primary_10_1186_s13072_024_00555_5 crossref_primary_10_1371_journal_pone_0119201 crossref_primary_10_1016_j_gim_2024_101167 crossref_primary_10_1186_s13148_023_01580_z crossref_primary_10_1016_j_envres_2021_111640 crossref_primary_10_1016_j_bbih_2025_101014 crossref_primary_10_3389_fnins_2021_799761 crossref_primary_10_3389_fphar_2019_00385 crossref_primary_10_1093_nar_gkv907 crossref_primary_10_1089_omi_2016_0041 crossref_primary_10_1038_s42003_020_01479_y crossref_primary_10_1093_hmg_ddae112 crossref_primary_10_1093_hmg_ddad024 crossref_primary_10_1371_journal_pone_0152034 crossref_primary_10_1002_jimd_12829 crossref_primary_10_1093_hmg_ddv161 crossref_primary_10_1186_s13058_023_01730_4 crossref_primary_10_3892_mmr_2017_7869 crossref_primary_10_1093_nop_npad025 crossref_primary_10_1186_s13073_021_00905_y crossref_primary_10_1038_s41386_021_01073_8 crossref_primary_10_1016_j_forsciint_2024_112339 crossref_primary_10_3390_ijms26073419 crossref_primary_10_1016_j_envint_2024_108872 crossref_primary_10_1080_15592294_2023_2230670 crossref_primary_10_1210_endocr_bqaa050 crossref_primary_10_1007_s00401_020_02226_7 crossref_primary_10_1016_j_scitotenv_2023_161815 crossref_primary_10_1093_eep_dvaa014 crossref_primary_10_1186_s13059_014_0503_2 crossref_primary_10_1186_s13148_021_01194_3 crossref_primary_10_3233_JAD_221031 crossref_primary_10_1186_s12967_020_02608_1 crossref_primary_10_3390_epigenomes7030018 crossref_primary_10_1136_bmjopen_2017_016708 crossref_primary_10_1186_1471_2105_16_S3_A7 crossref_primary_10_1186_s12864_015_2034_y crossref_primary_10_1038_s41416_023_02550_1 crossref_primary_10_1038_s41598_023_34922_1 crossref_primary_10_1371_journal_pgen_1005553 crossref_primary_10_1503_jpn_210064 crossref_primary_10_1186_s13072_018_0245_6 crossref_primary_10_1111_cdev_14239 crossref_primary_10_3389_fonc_2022_927298 crossref_primary_10_1080_15592294_2022_2100684 crossref_primary_10_1186_s13148_021_01119_0 crossref_primary_10_1186_s13287_018_1118_4 crossref_primary_10_1038_s41586_018_0753_3 crossref_primary_10_1161_JAHA_124_035777 crossref_primary_10_1186_s40001_023_01032_7 crossref_primary_10_1371_journal_pone_0174265 crossref_primary_10_3390_ijms241914778 crossref_primary_10_3390_genes14122207 crossref_primary_10_1016_j_heliyon_2025_e43006 crossref_primary_10_1111_cea_13748 crossref_primary_10_3389_fimmu_2022_1011829 crossref_primary_10_3390_ijms231810699 crossref_primary_10_2217_epi_2023_0145 crossref_primary_10_1371_journal_pcbi_1005840 crossref_primary_10_1007_s41237_022_00183_x crossref_primary_10_1016_j_psyneuen_2015_09_020 crossref_primary_10_1186_s13148_023_01480_2 crossref_primary_10_1038_s41387_022_00228_w crossref_primary_10_1038_s41598_020_72068_6 crossref_primary_10_1159_000369904 crossref_primary_10_1016_j_neurobiolaging_2020_06_003 crossref_primary_10_2217_epi_2017_0046 crossref_primary_10_1016_j_envres_2023_116215 crossref_primary_10_1016_j_envpol_2023_122197 crossref_primary_10_1016_j_ajhg_2016_06_032 crossref_primary_10_1038_s41598_022_15924_x crossref_primary_10_1016_j_artere_2022_01_004 crossref_primary_10_1186_s13148_025_01846_8 crossref_primary_10_1080_15592294_2022_2080993 crossref_primary_10_1186_s13148_022_01412_6 crossref_primary_10_3389_fgene_2022_989459 crossref_primary_10_1002_gepi_22252 crossref_primary_10_3390_ijms241411772 crossref_primary_10_1155_2022_4995196 crossref_primary_10_1016_j_ijheh_2020_113569 crossref_primary_10_1093_hmg_ddv124 crossref_primary_10_1016_j_envint_2021_107054 crossref_primary_10_1080_15592294_2016_1161875 crossref_primary_10_1038_s42003_022_04267_y crossref_primary_10_1186_s13148_019_0653_x crossref_primary_10_1289_EHP1246 crossref_primary_10_1186_s13148_023_01438_4 crossref_primary_10_1111_jcmm_15642 crossref_primary_10_1093_biostatistics_kxv016 crossref_primary_10_1016_j_psychres_2022_114510 crossref_primary_10_1080_15592294_2019_1590085 crossref_primary_10_1164_rccm_202106_1440OC crossref_primary_10_1186_s13059_016_1068_z crossref_primary_10_1186_s13073_016_0342_8 crossref_primary_10_3389_fgene_2015_00092 crossref_primary_10_1111_eos_12607 crossref_primary_10_3389_fimmu_2023_1245876 crossref_primary_10_1186_s12859_016_1140_4 crossref_primary_10_1080_15592294_2018_1497387 crossref_primary_10_1016_j_forsciint_2025_112409 crossref_primary_10_1111_joim_13528 crossref_primary_10_1038_s41398_020_00948_6 crossref_primary_10_1007_s00401_020_02224_9 crossref_primary_10_1016_j_jad_2022_10_049 crossref_primary_10_1093_eep_dvae017 crossref_primary_10_1136_thoraxjnl_2020_215866 crossref_primary_10_1186_s13058_017_0873_y crossref_primary_10_1038_s41398_017_0026_1 crossref_primary_10_1038_s41390_020_01172_0 crossref_primary_10_1002_jbmr_2342 crossref_primary_10_2217_epi_15_64 crossref_primary_10_1007_s00401_017_1678_x crossref_primary_10_1111_acel_13652 crossref_primary_10_1371_journal_pone_0151109 crossref_primary_10_1186_s13148_022_01282_y crossref_primary_10_1186_s13148_025_01859_3 crossref_primary_10_1371_journal_pone_0230253 crossref_primary_10_1186_s12885_018_4482_7 crossref_primary_10_1186_s13059_016_1066_1 crossref_primary_10_1186_s13073_020_00778_7 crossref_primary_10_3389_fnagi_2018_00311 crossref_primary_10_1038_s41380_023_02243_4 crossref_primary_10_1038_s41398_024_02841_y crossref_primary_10_1097_QAD_0000000000003065 crossref_primary_10_1089_jicm_2022_0713 crossref_primary_10_1186_s13072_023_00507_5 crossref_primary_10_1097_PSY_0000000000000604 crossref_primary_10_1186_s12919_018_0150_9 crossref_primary_10_1053_j_gastro_2019_01_270 crossref_primary_10_2217_epi_2017_0002 crossref_primary_10_15252_emmm_201809443 crossref_primary_10_1186_s13148_016_0285_3 crossref_primary_10_1017_thg_2015_76 crossref_primary_10_1186_s13148_024_01699_7 crossref_primary_10_3389_fimmu_2023_1162796 crossref_primary_10_1038_s41467_021_24710_8 crossref_primary_10_2217_epi_13_68 crossref_primary_10_1016_j_jpsychires_2022_10_023 crossref_primary_10_1186_s40478_024_01874_0 crossref_primary_10_3389_fpsyt_2023_1065417 crossref_primary_10_1186_s13075_021_02697_3 crossref_primary_10_1186_s40478_021_01177_8 crossref_primary_10_1002_rco2_52 crossref_primary_10_1080_15592294_2021_1876297 crossref_primary_10_1038_s41598_024_68071_w crossref_primary_10_3389_fgene_2018_00258 crossref_primary_10_2217_epi_13_58 crossref_primary_10_1213_ANE_0000000000007749 crossref_primary_10_1186_s13148_020_00873_x crossref_primary_10_1186_s13148_024_01675_1 crossref_primary_10_1371_journal_pone_0269723 crossref_primary_10_1016_j_kint_2018_01_036 crossref_primary_10_3390_cancers17020266 crossref_primary_10_1038_s41398_021_01207_y crossref_primary_10_1186_s13073_021_00877_z crossref_primary_10_1186_s13148_015_0073_5 crossref_primary_10_1289_ehp_1509966 crossref_primary_10_1186_s13059_019_1743_y crossref_primary_10_1186_1471_2164_16_S12_S7 crossref_primary_10_2217_epi_15_21 crossref_primary_10_1371_journal_pone_0193271 crossref_primary_10_1186_s12859_020_03559_6 crossref_primary_10_1093_hmg_ddad084 crossref_primary_10_1080_15592294_2015_1006497 crossref_primary_10_1186_s13148_021_01010_y crossref_primary_10_12688_f1000research_8839_2 crossref_primary_10_12688_f1000research_8839_1 crossref_primary_10_12688_f1000research_8839_3 crossref_primary_10_1186_s13148_022_01284_w crossref_primary_10_1080_15592294_2015_1050172 crossref_primary_10_1186_s13059_015_0828_5 crossref_primary_10_1016_j_ecoenv_2024_116743 crossref_primary_10_1016_j_jpsychires_2024_07_013 crossref_primary_10_3390_genes14040842 crossref_primary_10_1371_journal_pgen_1003763 crossref_primary_10_1093_eep_dvac026 crossref_primary_10_1080_15592294_2018_1529849 crossref_primary_10_1186_s13148_022_01403_7 crossref_primary_10_1016_j_bbi_2019_06_025 crossref_primary_10_1016_j_scitotenv_2025_180079 crossref_primary_10_1111_acel_13863 crossref_primary_10_1007_s00438_024_02176_9 crossref_primary_10_1007_s00018_023_04714_x crossref_primary_10_1186_s12919_018_0152_7 crossref_primary_10_1186_s13148_018_0471_6 crossref_primary_10_1007_s00439_014_1526_1 crossref_primary_10_3390_brainsci11111376 crossref_primary_10_1158_1078_0432_CCR_19_4207 crossref_primary_10_1093_bib_bbaf170 crossref_primary_10_1007_s00251_014_0768_3 crossref_primary_10_1080_15592294_2019_1629234 crossref_primary_10_1007_s12031_015_0665_8 crossref_primary_10_1038_ncomms10967 crossref_primary_10_3389_fcell_2019_00032 crossref_primary_10_1016_j_jmoldx_2015_11_004 crossref_primary_10_1186_s13148_017_0392_9 crossref_primary_10_1289_EHP2192 crossref_primary_10_1038_s41398_025_03235_4 crossref_primary_10_1186_s13148_020_00984_5 crossref_primary_10_1016_j_envpol_2025_125737 crossref_primary_10_1097_PSY_0000000000000411 crossref_primary_10_1186_s13104_023_06673_9 crossref_primary_10_1053_j_gastro_2018_10_029 crossref_primary_10_1007_s10549_021_06273_w crossref_primary_10_1038_tp_2017_171 crossref_primary_10_1080_08039488_2019_1613446 crossref_primary_10_1177_07067437241300947 crossref_primary_10_1038_s41598_019_50250_9 crossref_primary_10_1093_nargab_lqae181 crossref_primary_10_1134_S199075081702007X crossref_primary_10_1093_ije_dyv027 crossref_primary_10_1093_nar_gkt242 crossref_primary_10_1016_j_ultras_2021_106561 crossref_primary_10_2217_epi_2016_0179 crossref_primary_10_1158_1940_6207_CAPR_17_0413 crossref_primary_10_1080_15592294_2019_1666650 crossref_primary_10_1093_humrep_deab078 crossref_primary_10_1038_s41598_025_13868_6 crossref_primary_10_1038_s41698_024_00689_5 crossref_primary_10_1101_gr_269233_120 crossref_primary_10_2217_epi_2020_0344 crossref_primary_10_1155_2016_2584940 crossref_primary_10_1186_s13059_016_1051_8 crossref_primary_10_1038_s41467_018_03170_7 crossref_primary_10_1007_s11060_016_2261_3 crossref_primary_10_1038_s41386_023_01579_3 crossref_primary_10_1158_2159_8290_CD_20_1202 crossref_primary_10_3389_fgene_2020_538492 crossref_primary_10_1038_s41380_022_01525_7 crossref_primary_10_3390_biology12010033 crossref_primary_10_3390_ijms222312840 crossref_primary_10_1186_s13075_025_03628_2 crossref_primary_10_1007_s12094_025_03864_7 crossref_primary_10_1038_s41467_022_28237_4 crossref_primary_10_1038_ijo_2017_245 crossref_primary_10_1007_s00438_023_02010_8 crossref_primary_10_1016_j_ebiom_2022_104206 crossref_primary_10_1002_art_40408 crossref_primary_10_1186_s12920_018_0341_2 crossref_primary_10_1038_s41467_018_04924_z crossref_primary_10_1016_j_jaut_2023_103137 crossref_primary_10_1186_s13148_022_01394_5 crossref_primary_10_1186_s12864_024_10226_0 crossref_primary_10_1371_journal_pcbi_1009562 crossref_primary_10_1038_s41598_018_31886_5 crossref_primary_10_1186_s40345_019_0176_6 crossref_primary_10_1073_pnas_1412759111 crossref_primary_10_1186_s12944_024_02304_9 crossref_primary_10_1002_aur_2822 crossref_primary_10_1002_dev_22085 crossref_primary_10_3390_ijms17081291 crossref_primary_10_1186_s13072_024_00529_7 crossref_primary_10_1038_ijo_2015_221 crossref_primary_10_1038_s41467_020_19615_x crossref_primary_10_1080_15592294_2017_1370172 crossref_primary_10_1038_s41598_017_08595_6 crossref_primary_10_1016_j_fertnstert_2021_06_025 crossref_primary_10_1038_s41598_019_55453_8 crossref_primary_10_1038_srep14466 crossref_primary_10_1186_s43682_022_00008_8 crossref_primary_10_1016_j_envres_2025_121286 crossref_primary_10_1371_journal_pone_0171694 crossref_primary_10_1186_s40478_025_01960_x crossref_primary_10_1038_s41598_019_48493_7 crossref_primary_10_1093_eep_dvv003 crossref_primary_10_1186_s12864_016_3310_1 crossref_primary_10_1038_s41598_024_73845_3 crossref_primary_10_1038_s42003_021_01661_w crossref_primary_10_2217_epi_2017_0078 crossref_primary_10_1038_ijo_2015_237 crossref_primary_10_1002_acn3_560 crossref_primary_10_1136_thorax_2023_220352 crossref_primary_10_1016_j_jpsychires_2016_09_006 crossref_primary_10_1016_j_envint_2021_106683 crossref_primary_10_1016_j_toxlet_2014_10_024 crossref_primary_10_1111_hepr_12992 crossref_primary_10_1016_j_jad_2025_120118 crossref_primary_10_1038_tp_2017_130 crossref_primary_10_1038_ng_3457 crossref_primary_10_1186_s13148_016_0303_5 crossref_primary_10_1186_s12919_018_0130_0 crossref_primary_10_1038_s41467_025_59427_5 crossref_primary_10_1186_s13059_017_1374_0 crossref_primary_10_1186_s13148_024_01706_x crossref_primary_10_1186_s13148_017_0370_2 crossref_primary_10_3390_genes13101888 crossref_primary_10_1038_s41390_024_03116_4 crossref_primary_10_1186_s13148_023_01540_7 crossref_primary_10_1016_j_molcel_2016_03_019 crossref_primary_10_1007_s00381_019_04305_x crossref_primary_10_3390_ijms150610835 crossref_primary_10_1016_j_spinee_2024_10_015 crossref_primary_10_1016_j_canep_2016_08_020 crossref_primary_10_1016_j_modpat_2025_100896 crossref_primary_10_1038_bjc_2014_337 crossref_primary_10_1016_j_compbiomed_2023_106573 crossref_primary_10_1038_s42003_022_03117_1 crossref_primary_10_1136_bmjonc_2024_000675 crossref_primary_10_1017_S2040174419000801 crossref_primary_10_1371_journal_pone_0272064 crossref_primary_10_3390_cancers13205165 crossref_primary_10_1038_ng_3488 crossref_primary_10_1016_j_msard_2024_105910 crossref_primary_10_1186_s13148_019_0670_9 crossref_primary_10_1186_s13148_022_01241_7 crossref_primary_10_1186_gb_2013_14_10_r115 crossref_primary_10_2217_epi_2017_0093 crossref_primary_10_1186_s13148_020_00877_7 crossref_primary_10_1186_s13148_022_01385_6 crossref_primary_10_1210_clinem_dgab488 crossref_primary_10_3390_ijms18030535 crossref_primary_10_1186_s13148_021_01002_y crossref_primary_10_1186_1471_2164_15_435 crossref_primary_10_1038_s41598_020_61236_3 crossref_primary_10_3389_fonc_2021_620873 crossref_primary_10_1002_em_22153 crossref_primary_10_1111_andr_12170 crossref_primary_10_7717_peerj_14786 crossref_primary_10_1038_s41467_021_23899_y crossref_primary_10_1016_j_jaci_2016_11_030 crossref_primary_10_1016_j_envres_2022_114797 crossref_primary_10_1038_s41588_023_01494_9 crossref_primary_10_1073_pnas_1820843116 crossref_primary_10_1186_1471_2164_14_293 crossref_primary_10_3390_genes5020347 crossref_primary_10_1016_j_cels_2020_06_006 crossref_primary_10_1161_CIRCGENETICS_116_001506 crossref_primary_10_1038_s41514_022_00085_y crossref_primary_10_1097_EE9_0000000000000083 crossref_primary_10_1016_j_bbagen_2017_10_012 crossref_primary_10_1134_S0026893323050047 crossref_primary_10_1093_eep_dvz004 crossref_primary_10_2217_epi_2021_0461 crossref_primary_10_3892_etm_2017_5394 crossref_primary_10_1186_s12931_021_01911_9 crossref_primary_10_1186_s13059_018_1601_3 crossref_primary_10_1038_srep26424 crossref_primary_10_1186_s13148_020_00942_1 crossref_primary_10_1016_j_stem_2018_09_016 crossref_primary_10_1038_s41598_020_80345_7 crossref_primary_10_1007_s00432_014_1841_x crossref_primary_10_2217_epi_2023_0358 crossref_primary_10_7554_eLife_41356 crossref_primary_10_1038_ncomms10577 crossref_primary_10_1186_s12940_019_0533_z crossref_primary_10_1016_j_psyneuen_2025_107516 crossref_primary_10_1186_s12859_018_2096_3 crossref_primary_10_1007_s00414_024_03365_2 crossref_primary_10_1007_s12975_024_01252_x crossref_primary_10_1038_ng_3415 crossref_primary_10_1038_s41598_019_42553_8 crossref_primary_10_1080_15592294_2024_2437275 crossref_primary_10_1038_s41598_024_69796_4 crossref_primary_10_1002_art_42654 crossref_primary_10_1016_j_orcp_2025_09_003 crossref_primary_10_1016_j_bbih_2022_100572 crossref_primary_10_1186_s13148_022_01232_8 crossref_primary_10_1038_s41588_022_01248_z crossref_primary_10_1186_s12859_017_1568_1 crossref_primary_10_1080_15592294_2016_1226451 crossref_primary_10_3390_ijerph21030256 crossref_primary_10_1080_15592294_2020_1734714 crossref_primary_10_1038_s41598_025_13951_y crossref_primary_10_1146_annurev_psych_122414_033653 crossref_primary_10_2217_epi_2016_0103 crossref_primary_10_1007_s11357_023_00903_5 crossref_primary_10_1186_s12885_021_08645_3 crossref_primary_10_1289_EHP6174 crossref_primary_10_1007_s00420_016_1148_0 crossref_primary_10_1186_s13148_021_01094_6 crossref_primary_10_1186_s13148_024_01779_8 crossref_primary_10_1093_bib_bbae496 crossref_primary_10_1186_s13148_022_01243_5 crossref_primary_10_1111_ppe_12826 crossref_primary_10_1038_s42003_023_04584_w crossref_primary_10_1186_s12933_023_01774_y crossref_primary_10_1515_biol_2018_0024 crossref_primary_10_2217_epi_2016_0109 crossref_primary_10_1038_s43587_022_00233_9 crossref_primary_10_1186_s12864_015_2066_3 crossref_primary_10_1016_j_dadr_2022_100077 crossref_primary_10_1073_pnas_1700655114 crossref_primary_10_1002_ajpa_23341 crossref_primary_10_1038_s41467_022_28355_z crossref_primary_10_1186_s13072_015_0007_7 crossref_primary_10_1186_s13148_019_0628_y crossref_primary_10_1371_journal_pgen_1005583 crossref_primary_10_1093_nar_gkz840 crossref_primary_10_1186_s13148_018_0556_2 crossref_primary_10_1038_s41514_025_00265_6 crossref_primary_10_1038_s41598_017_09235_9 crossref_primary_10_1016_j_socscimed_2024_117142 crossref_primary_10_3390_genes14020248 crossref_primary_10_1038_s41593_024_01742_z crossref_primary_10_1002_1878_0261_13479 crossref_primary_10_1016_j_jid_2016_11_029 crossref_primary_10_1007_s40618_022_01923_2 crossref_primary_10_3390_cancers13061189 crossref_primary_10_1186_s13148_023_01462_4 crossref_primary_10_3390_ijms242216412 crossref_primary_10_1038_s41386_020_0675_2 crossref_primary_10_1161_CIRCRESAHA_121_318965 crossref_primary_10_1073_pnas_1604558113 crossref_primary_10_1016_j_biopha_2023_115559 crossref_primary_10_1186_s12863_018_0648_1 crossref_primary_10_1158_1940_6207_CAPR_18_0111 crossref_primary_10_1242_jcs_261323 crossref_primary_10_1038_s41380_025_03031_y crossref_primary_10_1080_15592294_2018_1460034 crossref_primary_10_1016_j_jcf_2020_06_009 crossref_primary_10_1038_s41467_023_38378_9 crossref_primary_10_1080_15592294_2015_1057384 crossref_primary_10_1016_j_ygeno_2015_09_003 crossref_primary_10_18632_aging_206276 crossref_primary_10_1038_s41467_024_48649_8 crossref_primary_10_1186_s13148_021_01200_8 crossref_primary_10_1186_s13148_023_01507_8 crossref_primary_10_1016_j_ccell_2021_11_012 crossref_primary_10_1080_15592294_2023_2199373 crossref_primary_10_1186_s13148_016_0212_7 crossref_primary_10_1016_j_nicl_2020_102458 crossref_primary_10_1038_s41398_024_02992_y crossref_primary_10_1038_s41467_025_62894_5 crossref_primary_10_1186_s12859_017_1511_5 crossref_primary_10_1158_2159_8290_CD_22_0603 crossref_primary_10_1007_s00420_025_02147_6 crossref_primary_10_1038_s42003_024_06488_9 crossref_primary_10_1186_s13148_024_01690_2 crossref_primary_10_1186_s42466_024_00327_2 crossref_primary_10_1503_jpn_230062 crossref_primary_10_1002_hbm_70261 crossref_primary_10_1002_sctm_20_0491 crossref_primary_10_1016_j_vaccine_2015_04_088 crossref_primary_10_1016_j_fsigen_2021_102624 crossref_primary_10_1186_s13072_016_0108_y crossref_primary_10_1289_EHP333 crossref_primary_10_1161_CIRCRESAHA_115_305206 crossref_primary_10_1186_s13148_015_0168_z crossref_primary_10_3389_freae_2024_1427399 crossref_primary_10_1038_s41467_017_01078_2 crossref_primary_10_1371_journal_pone_0201066 crossref_primary_10_2217_epi_2016_0143 crossref_primary_10_3390_cancers12030680 crossref_primary_10_1007_s00438_020_01678_6 crossref_primary_10_3390_cancers15030647 crossref_primary_10_1007_s10120_014_0348_0 crossref_primary_10_1038_s41592_022_01412_7 crossref_primary_10_1002_mnfr_202100991 crossref_primary_10_1186_s13148_021_01115_4 crossref_primary_10_1177_09567976221122760 crossref_primary_10_1186_s13148_019_0637_x crossref_primary_10_1016_j_cels_2019_06_006 crossref_primary_10_1093_bib_bbac274 crossref_primary_10_1098_rsos_200872 crossref_primary_10_1016_j_envres_2025_121914 crossref_primary_10_1158_0008_5472_CAN_13_3198 crossref_primary_10_1186_s12863_018_0637_4 crossref_primary_10_1186_s13148_018_0558_0 crossref_primary_10_2217_epi_2018_0225 crossref_primary_10_1186_s12931_018_0850_8 crossref_primary_10_1038_s41467_025_57760_3 crossref_primary_10_1186_s13073_014_0116_0 crossref_primary_10_1371_journal_pgen_1009506 crossref_primary_10_1016_j_jaci_2024_01_014 crossref_primary_10_1371_journal_pone_0166486 crossref_primary_10_3389_fgene_2022_766553 crossref_primary_10_1002_jcp_27557 crossref_primary_10_4049_jimmunol_2100931 crossref_primary_10_1111_adb_13198 crossref_primary_10_1038_s41596_020_0369_6 crossref_primary_10_3390_math12172716 crossref_primary_10_1038_nature24294 crossref_primary_10_1371_journal_pone_0098330 crossref_primary_10_1186_s13148_025_01880_6 crossref_primary_10_1007_s11033_016_3946_6 crossref_primary_10_3390_ijerph192013421 crossref_primary_10_1186_s13148_023_01528_3 crossref_primary_10_1080_15592294_2020_1819666 crossref_primary_10_1186_s13073_016_0361_5 crossref_primary_10_1080_15592294_2017_1411444 crossref_primary_10_1097_MD_0000000000012763 crossref_primary_10_3892_mmr_2018_8487 crossref_primary_10_1177_09622802221146313 crossref_primary_10_1016_j_heliyon_2021_e06000 crossref_primary_10_1016_j_jid_2022_11_016 crossref_primary_10_1186_s13148_018_0588_7 crossref_primary_10_1001_jamanetworkopen_2022_23285 crossref_primary_10_1073_pnas_1717340115 crossref_primary_10_3390_cancers15194826 crossref_primary_10_1038_s41598_017_00384_5 crossref_primary_10_1002_humu_23740 crossref_primary_10_1093_ecco_jcc_jjae072 crossref_primary_10_3390_ijms241612576 crossref_primary_10_1016_j_jaci_2019_07_047 crossref_primary_10_1038_s41421_024_00652_5 crossref_primary_10_1186_s12916_022_02701_w crossref_primary_10_1038_s41598_019_54355_z crossref_primary_10_1210_JC_2015_2284 crossref_primary_10_1017_S2040174422000526 crossref_primary_10_3389_fgene_2022_929416 crossref_primary_10_1186_s12859_019_3307_2 crossref_primary_10_1038_s41467_019_12228_z crossref_primary_10_1038_s41598_018_35111_1 crossref_primary_10_1016_j_joca_2016_03_009 crossref_primary_10_2217_epi_2017_0105 crossref_primary_10_1080_15592294_2016_1270486 crossref_primary_10_1289_EHP11559 crossref_primary_10_3390_cancers12113079 crossref_primary_10_1186_s13148_017_0376_9 crossref_primary_10_1186_s13073_020_00724_7 crossref_primary_10_1186_s13148_019_0798_7 crossref_primary_10_1080_15592294_2021_1969499 crossref_primary_10_1080_15592294_2021_1985301 crossref_primary_10_1186_s13148_021_01207_1 crossref_primary_10_1093_ije_dyz082 crossref_primary_10_3390_cancers13246291 crossref_primary_10_1016_j_xhgg_2024_100326 crossref_primary_10_1186_s13072_022_00477_0 crossref_primary_10_1038_s41525_021_00225_5 crossref_primary_10_1038_s42003_020_01267_8 crossref_primary_10_1186_s40246_023_00484_6 crossref_primary_10_1093_toxsci_kfu210 crossref_primary_10_1186_s12859_020_03734_9 crossref_primary_10_1007_s00414_023_03049_3 crossref_primary_10_1016_j_ecoenv_2024_116823 crossref_primary_10_1016_j_envres_2018_01_009 crossref_primary_10_1016_j_jpsychires_2020_06_005 crossref_primary_10_1186_s12919_018_0125_x crossref_primary_10_3389_fgene_2019_01229 crossref_primary_10_3390_cancers14071664 crossref_primary_10_1038_s41525_025_00509_0 crossref_primary_10_1186_s40364_024_00592_y crossref_primary_10_3389_fpsyt_2022_870656 crossref_primary_10_1016_j_ajcnut_2024_08_033 crossref_primary_10_1038_s41467_022_31827_x crossref_primary_10_1002_dev_22103 crossref_primary_10_1186_s13148_016_0266_6 crossref_primary_10_3390_cells12071021 crossref_primary_10_1002_ana_26923 crossref_primary_10_1016_j_ebiom_2017_12_018 crossref_primary_10_1007_s12072_022_10469_7 crossref_primary_10_1093_mutage_geu089 crossref_primary_10_1371_journal_pone_0325050 crossref_primary_10_1093_eep_dvab003 crossref_primary_10_1080_15592294_2015_1105424 crossref_primary_10_1111_pcn_12835 crossref_primary_10_1093_sleep_zsz198 crossref_primary_10_1111_cns_12786 crossref_primary_10_1158_1541_7786_MCR_19_0309 crossref_primary_10_1080_15592294_2020_1805692 crossref_primary_10_1016_j_ajhg_2020_08_019 crossref_primary_10_1080_28361512_2025_2554836 crossref_primary_10_1111_cas_14160 crossref_primary_10_1038_srep46330 crossref_primary_10_1002_gepi_70008 crossref_primary_10_1016_j_ymeth_2020_10_002 crossref_primary_10_1186_s12885_020_07078_8 crossref_primary_10_1016_j_bone_2019_06_021 crossref_primary_10_1038_s41598_024_75287_3 crossref_primary_10_3389_fimmu_2021_737650 crossref_primary_10_1186_s13148_014_0040_6 crossref_primary_10_1002_2211_5463_13656 crossref_primary_10_1016_j_biopsych_2023_07_010 crossref_primary_10_1038_s41598_020_68741_5 crossref_primary_10_1080_15592294_2019_1565590 crossref_primary_10_3389_fgene_2020_522125 crossref_primary_10_2217_epi_2023_0284 crossref_primary_10_1080_1357650X_2017_1377726 crossref_primary_10_1186_s13148_019_0789_8 crossref_primary_10_1186_s13148_024_01767_y crossref_primary_10_1038_s41598_019_46930_1 crossref_primary_10_1186_s13073_025_01453_5 crossref_primary_10_3389_fgene_2021_810985 crossref_primary_10_1093_geronb_gbx015 crossref_primary_10_1038_s41370_019_0183_9 crossref_primary_10_1038_s41366_020_0546_2 crossref_primary_10_1093_infdis_jiaa599 crossref_primary_10_1038_s42003_025_08021_y crossref_primary_10_1016_j_fct_2023_114409 crossref_primary_10_1016_j_biopsych_2021_11_025 crossref_primary_10_1016_j_genrep_2024_101927 crossref_primary_10_3390_ijms241813910 crossref_primary_10_1038_s41598_024_77914_5 crossref_primary_10_1186_s13148_019_0678_1 crossref_primary_10_3390_biomedicines12061261 crossref_primary_10_1017_S2040174414000506 crossref_primary_10_1080_17501911_2025_2510190 crossref_primary_10_2217_epi_2023_0017 crossref_primary_10_1038_s41467_018_07276_w crossref_primary_10_1146_annurev_biodatasci_120924_091033 crossref_primary_10_1016_j_psyneuen_2014_07_011 crossref_primary_10_1111_acel_13100 crossref_primary_10_1016_j_ajhg_2017_09_028 crossref_primary_10_1093_neuonc_nox076 crossref_primary_10_1186_s13148_017_0367_x crossref_primary_10_1186_s13058_021_01434_7 crossref_primary_10_1002_mef2_27 crossref_primary_10_1158_1541_7786_MCR_17_0293 crossref_primary_10_3389_fimmu_2021_681714 crossref_primary_10_1186_s12859_016_1056_z crossref_primary_10_1016_j_psyneuen_2022_105748 crossref_primary_10_2217_epi_2017_0160 crossref_primary_10_2217_epi_2017_0162 crossref_primary_10_1136_lupus_2016_000183 crossref_primary_10_1371_journal_pgen_1009189 crossref_primary_10_1093_bib_bbac617 crossref_primary_10_1186_s12906_021_03310_5 crossref_primary_10_1038_s41698_024_00578_x crossref_primary_10_1186_s13148_015_0128_7 crossref_primary_10_1016_j_ejca_2017_01_014 crossref_primary_10_1038_mp_2016_250 crossref_primary_10_1186_s13072_015_0035_3 crossref_primary_10_1080_15592294_2022_2135201 crossref_primary_10_1371_journal_pcbi_1007095 crossref_primary_10_1093_nar_gkw1100 crossref_primary_10_1038_s41467_020_18618_y crossref_primary_10_1186_s12916_022_02610_y crossref_primary_10_3390_ijms23062957 crossref_primary_10_1002_art_39952 crossref_primary_10_1093_hmg_ddx424 crossref_primary_10_7554_eLife_80729 crossref_primary_10_1186_s13148_018_0488_x crossref_primary_10_1186_s40478_022_01470_0 crossref_primary_10_3389_fnins_2019_00712 crossref_primary_10_3390_ijms251910576 crossref_primary_10_1080_15592294_2022_2028072 crossref_primary_10_1097_MIB_0000000000000179 crossref_primary_10_1016_j_jcyt_2020_06_001 crossref_primary_10_1136_jitc_2024_009841 crossref_primary_10_3390_jcm10122680 crossref_primary_10_1016_j_envint_2020_105929 crossref_primary_10_1038_s41390_025_04381_7 crossref_primary_10_1038_s41467_022_29540_w crossref_primary_10_1038_s42003_022_03540_4 crossref_primary_10_1186_s40478_022_01406_8 crossref_primary_10_1038_s41398_023_02407_4 crossref_primary_10_1016_j_bpsgos_2025_100545 crossref_primary_10_1186_s13073_022_01079_x crossref_primary_10_1016_j_mce_2017_11_019 crossref_primary_10_1186_s12872_021_02001_w crossref_primary_10_1186_s13148_023_01546_1 crossref_primary_10_1186_s13148_015_0094_0 crossref_primary_10_1038_s41467_021_25583_7 crossref_primary_10_1007_s11357_017_0001_z crossref_primary_10_1371_journal_pone_0152314 crossref_primary_10_1093_ajcn_nqz031 crossref_primary_10_1093_nar_gkx1139 crossref_primary_10_3390_nu13093210 crossref_primary_10_1111_bdi_12422 crossref_primary_10_1212_WNL_0000000000207489 crossref_primary_10_1016_j_forsciint_2024_112247 crossref_primary_10_1016_j_envint_2018_07_041 crossref_primary_10_1186_1471_2105_15_199 crossref_primary_10_1186_s13148_015_0104_2 crossref_primary_10_1038_s41598_021_83016_3 crossref_primary_10_1111_jgh_16054 crossref_primary_10_1186_s12859_021_04268_4 crossref_primary_10_1371_journal_pone_0290450 crossref_primary_10_1016_j_artmed_2024_102962 crossref_primary_10_1080_15592294_2017_1412907 crossref_primary_10_3389_fgene_2019_00770 crossref_primary_10_1038_s41588_023_01520_w crossref_primary_10_1186_s12864_016_2421_z crossref_primary_10_1017_thg_2018_10 crossref_primary_10_1002_2211_5463_12907 crossref_primary_10_1158_1078_0432_CCR_17_2206 crossref_primary_10_1093_ije_dyu236 crossref_primary_10_1096_fj_201800400R crossref_primary_10_1038_s41467_017_01118_x crossref_primary_10_1186_s13148_018_0571_3 crossref_primary_10_3390_antibiotics12071217 crossref_primary_10_1038_s41380_021_01308_6 crossref_primary_10_1080_15592294_2022_2115600 crossref_primary_10_3389_fgene_2021_618803 crossref_primary_10_1016_j_ajcnut_2025_05_029 crossref_primary_10_1089_dna_2018_4469 crossref_primary_10_1186_s13148_016_0173_x crossref_primary_10_2337_db17_1539 crossref_primary_10_1016_j_jid_2021_08_445 crossref_primary_10_1177_25424823251341176 crossref_primary_10_1007_s10142_016_0533_9 crossref_primary_10_1186_s40478_020_00908_7 crossref_primary_10_3390_brainsci13081214 crossref_primary_10_1038_s41598_017_03434_0 crossref_primary_10_3109_10641955_2016_1162315 crossref_primary_10_1038_s41598_020_61430_3 crossref_primary_10_1159_000530106 crossref_primary_10_1053_j_gastro_2020_01_044 crossref_primary_10_1080_15592294_2018_1516453 crossref_primary_10_1161_CIRCULATIONAHA_124_073181 crossref_primary_10_3390_ijerph16040600 crossref_primary_10_1007_s13365_019_00777_4 crossref_primary_10_1016_j_ebiom_2021_103399 crossref_primary_10_1371_journal_pgen_1004996 crossref_primary_10_1093_toxres_tfad084 crossref_primary_10_1186_s12864_016_2819_7 crossref_primary_10_3390_ijms232315280 crossref_primary_10_1016_j_isci_2025_113181 crossref_primary_10_3390_biomedicines12051057 crossref_primary_10_1038_s41467_021_24558_y crossref_primary_10_2217_epi_14_20 crossref_primary_10_1038_s41467_018_05325_y crossref_primary_10_1093_gigascience_giaf039 crossref_primary_10_1186_s13148_016_0307_1 crossref_primary_10_3390_ijms241512155 crossref_primary_10_1080_15592294_2021_1928994 crossref_primary_10_1016_j_jmoldx_2022_03_010 crossref_primary_10_1038_s12276_024_01173_7 crossref_primary_10_2217_epi_2017_0146 crossref_primary_10_1007_s10910_022_01381_4 crossref_primary_10_1016_j_pnpbp_2019_109805 crossref_primary_10_1093_hmg_ddv232 crossref_primary_10_1186_s13148_021_01164_9 crossref_primary_10_1007_s12035_022_03180_z crossref_primary_10_3390_genes15121510 crossref_primary_10_3390_jcm8091307 crossref_primary_10_1093_g3journal_jkac041 crossref_primary_10_1111_jgs_18726 crossref_primary_10_3389_fgene_2016_00023 crossref_primary_10_1186_s40246_025_00763_4 crossref_primary_10_1089_dna_2018_4276 crossref_primary_10_1186_s12885_019_5291_3 crossref_primary_10_1097_MD_0000000000022389 crossref_primary_10_1210_jc_2017_00881 crossref_primary_10_1038_s12276_021_00612_z crossref_primary_10_1186_s12864_015_1381_z crossref_primary_10_1038_s41408_020_0310_9 crossref_primary_10_1016_j_envres_2020_109573 crossref_primary_10_1016_j_freeradbiomed_2025_08_039 crossref_primary_10_1161_JAHA_119_015299 crossref_primary_10_4251_wjgo_v9_i3_105 crossref_primary_10_1038_s41398_024_03148_8 crossref_primary_10_1002_ajmg_b_32278 crossref_primary_10_1111_jre_12868 crossref_primary_10_1186_s13148_023_01435_7 crossref_primary_10_1186_s13148_023_01459_z crossref_primary_10_1038_s41467_021_22874_x crossref_primary_10_1038_nmeth_3115 crossref_primary_10_1186_s13059_019_1753_9 crossref_primary_10_1186_s13148_016_0295_1 crossref_primary_10_1016_j_ygeno_2016_07_001 crossref_primary_10_1007_s00018_024_05208_0 crossref_primary_10_1177_0962280216683571 crossref_primary_10_1038_s42003_020_01469_0 crossref_primary_10_1038_s41598_021_81758_8 crossref_primary_10_3390_cancers12123589 crossref_primary_10_1016_j_psychres_2022_114901 crossref_primary_10_1371_journal_pone_0323756 crossref_primary_10_5498_wjp_v13_i8_524 crossref_primary_10_1111_jcpp_13613 crossref_primary_10_1186_s13059_016_1052_7 crossref_primary_10_1038_tp_2015_210 crossref_primary_10_1371_journal_pone_0263478 crossref_primary_10_1038_s41467_020_15342_5 crossref_primary_10_1038_s41467_025_56054_y crossref_primary_10_3390_cancers16132429 crossref_primary_10_1186_s13072_016_0058_4 crossref_primary_10_3389_fnagi_2023_1215957 crossref_primary_10_1016_j_phrs_2025_107767 crossref_primary_10_1038_s41598_017_05713_2 crossref_primary_10_2217_epi_15_110 crossref_primary_10_1186_s13073_023_01211_5 crossref_primary_10_1186_s13148_019_0618_0 crossref_primary_10_5812_ircmj_14873 crossref_primary_10_3892_ijo_2019_4885 crossref_primary_10_1038_s41467_020_19791_w crossref_primary_10_1002_art_39792 crossref_primary_10_1161_CIRCGENETICS_114_000804 crossref_primary_10_3892_mmr_2018_8804 crossref_primary_10_1111_acel_13608 crossref_primary_10_1016_j_placenta_2021_05_005 crossref_primary_10_1007_s12561_016_9145_0 crossref_primary_10_1007_s00059_017_4616_8 crossref_primary_10_1097_PSY_0000000000000506 crossref_primary_10_1200_JCO_2016_68_2153 crossref_primary_10_1186_s13059_015_0600_x crossref_primary_10_1186_s13148_019_0705_2 crossref_primary_10_1007_s10815_018_1244_z crossref_primary_10_1038_s41398_023_02441_2 crossref_primary_10_3389_fimmu_2016_00450 crossref_primary_10_1002_jcp_29809 crossref_primary_10_1289_EHP36 crossref_primary_10_1017_S0954579419001421 crossref_primary_10_1007_s10549_021_06185_9 crossref_primary_10_1210_jc_2018_02076 crossref_primary_10_1038_s41598_022_05744_4 crossref_primary_10_2217_epi_2019_0004 crossref_primary_10_1371_journal_pone_0117403 crossref_primary_10_1186_s12859_017_1870_y crossref_primary_10_1080_15592294_2024_2360160 crossref_primary_10_1186_s12967_024_05842_z crossref_primary_10_1186_s13148_024_01680_4 crossref_primary_10_1093_pnasnexus_pgaf177 crossref_primary_10_3390_cancers13071677 crossref_primary_10_1080_15592294_2017_1414127 crossref_primary_10_1038_s41598_018_37746_6 crossref_primary_10_3389_fgene_2019_00816 crossref_primary_10_1016_j_dib_2018_01_061 crossref_primary_10_1186_s13287_022_03159_6 crossref_primary_10_1097_QAD_0000000000002805 crossref_primary_10_1210_clinem_dgac010 crossref_primary_10_1038_s43587_025_00883_5 crossref_primary_10_1038_s41598_019_42654_4 crossref_primary_10_1080_15592294_2021_1993607 crossref_primary_10_1002_ijc_33355 crossref_primary_10_1038_s41467_017_01586_1 crossref_primary_10_2217_epi_2016_0077 crossref_primary_10_1186_s13148_021_01080_y crossref_primary_10_1080_15622975_2020_1747113 crossref_primary_10_1038_s41598_018_33498_5 crossref_primary_10_1093_hmg_ddt430 crossref_primary_10_1080_15592294_2020_1795605 crossref_primary_10_1186_s13059_022_02793_w crossref_primary_10_1186_s13148_015_0116_y crossref_primary_10_1016_j_ebiom_2023_104657 crossref_primary_10_1038_s41467_018_04540_x crossref_primary_10_3390_biomedicines10061406 crossref_primary_10_1186_s13148_018_0439_6 crossref_primary_10_1186_s13148_021_01121_6 crossref_primary_10_1186_s13058_018_1022_y crossref_primary_10_1186_s13073_015_0258_8 crossref_primary_10_1038_s10038_017_0382_y crossref_primary_10_1186_s13073_024_01408_2 crossref_primary_10_1186_s12890_025_03634_9 crossref_primary_10_1016_j_psyneuen_2020_105026 crossref_primary_10_1002_dmrr_3781 crossref_primary_10_1038_s41598_024_81486_9 crossref_primary_10_1155_2018_4390789 crossref_primary_10_1038_ng_3349 crossref_primary_10_1038_s41598_017_18034_1 crossref_primary_10_1080_15592294_2019_1634975 crossref_primary_10_3389_fgene_2021_676449 crossref_primary_10_2217_epi_2016_0087 crossref_primary_10_1017_S0033291723001629 crossref_primary_10_3389_fimmu_2023_1173187 crossref_primary_10_1016_j_ymeth_2014_08_011 crossref_primary_10_1186_s12891_015_0745_5 crossref_primary_10_1097_CEJ_0000000000000460 crossref_primary_10_1111_hepr_12877 crossref_primary_10_1007_s10552_024_01924_x crossref_primary_10_1016_j_envint_2018_08_044 crossref_primary_10_1038_jid_2015_128 crossref_primary_10_7554_eLife_07103 crossref_primary_10_1186_s13059_022_02705_y crossref_primary_10_1186_s12916_017_0870_0 crossref_primary_10_1016_j_jpeds_2018_02_074 crossref_primary_10_1371_journal_pone_0187422 crossref_primary_10_1038_ncomms10893 crossref_primary_10_1093_bioadv_vbaf150 crossref_primary_10_3389_fnagi_2023_1063536 crossref_primary_10_1186_s13148_016_0172_y crossref_primary_10_1186_s13148_020_00830_8 crossref_primary_10_1186_s13073_020_00752_3 crossref_primary_10_1186_s13148_024_01671_5 crossref_primary_10_1038_s41467_021_27427_w crossref_primary_10_1186_s13148_022_01299_3 crossref_primary_10_1371_journal_pone_0135022 crossref_primary_10_1186_s13072_019_0296_3 crossref_primary_10_1289_EHP2045 crossref_primary_10_1038_s41597_020_0456_0 crossref_primary_10_1093_pnasnexus_pgaf127 crossref_primary_10_1186_s13059_016_1030_0 crossref_primary_10_1186_s13148_024_01695_x crossref_primary_10_1002_ajmg_b_32568 crossref_primary_10_1080_15592294_2019_1568178 crossref_primary_10_3389_fgene_2019_00624 crossref_primary_10_1186_s13148_025_01868_2 crossref_primary_10_4161_15592294_2014_989077 crossref_primary_10_1016_j_jand_2024_01_002 crossref_primary_10_2217_epi_2019_0040 crossref_primary_10_2337_db20_0487 crossref_primary_10_1002_ijc_34477 crossref_primary_10_4161_15592294_2014_982445 crossref_primary_10_1038_s41598_018_33959_x crossref_primary_10_1080_15592294_2021_1982510 crossref_primary_10_1002_smll_201502346 crossref_primary_10_1093_cercor_bhac043 crossref_primary_10_1097_HC9_0000000000000496 crossref_primary_10_1186_s12263_019_0634_x crossref_primary_10_1289_EHP2034 crossref_primary_10_1016_j_envint_2021_106587 crossref_primary_10_1186_s13293_024_00682_4 crossref_primary_10_1186_s13073_015_0225_4 crossref_primary_10_1016_j_pnpbp_2018_11_011 crossref_primary_10_1002_1878_0261_13160 crossref_primary_10_1002_ajmg_b_32315 crossref_primary_10_3389_fgene_2019_00613 crossref_primary_10_1080_15592294_2020_1814504 crossref_primary_10_1186_1471_2105_15_141 crossref_primary_10_2217_epi_2019_0276 crossref_primary_10_1186_s13148_023_01598_3 crossref_primary_10_1186_s12967_024_05746_y crossref_primary_10_1186_s12864_018_4525_0 crossref_primary_10_1038_s41398_021_01225_w crossref_primary_10_1038_s42003_025_08121_9 crossref_primary_10_1186_s12864_020_07168_8 crossref_primary_10_4161_epi_27119 crossref_primary_10_1186_s13148_022_01277_9 crossref_primary_10_1007_s00401_019_02099_5 crossref_primary_10_1073_pnas_1707151114 crossref_primary_10_4161_epi_26037 crossref_primary_10_1186_s12864_021_07935_1 crossref_primary_10_1016_j_jid_2021_11_017 crossref_primary_10_1016_j_envint_2024_108763 crossref_primary_10_1093_hmg_ddac137 crossref_primary_10_1186_1868_7083_6_22 crossref_primary_10_1038_s41467_020_15538_9 crossref_primary_10_1186_s13148_019_0614_4 crossref_primary_10_1186_s13148_022_01397_2 crossref_primary_10_1038_srep19430 crossref_primary_10_1016_j_jaci_2019_01_034 crossref_primary_10_3390_nu15163621 crossref_primary_10_1016_j_envres_2021_111211 crossref_primary_10_1016_j_envint_2019_02_053 crossref_primary_10_1016_j_jad_2024_01_241 crossref_primary_10_1080_07435800_2019_1669160 crossref_primary_10_2217_epi_2019_0299 crossref_primary_10_1126_scitranslmed_aaz1803 crossref_primary_10_1073_pnas_1713736114 crossref_primary_10_1016_j_neo_2014_07_001 crossref_primary_10_1186_s12864_020_06789_3 crossref_primary_10_3389_fgene_2021_640266 crossref_primary_10_1186_s12864_018_4652_7 crossref_primary_10_1038_nn_4632 crossref_primary_10_1038_s41598_023_29843_y crossref_primary_10_1002_ajmg_b_32920 crossref_primary_10_1038_s41467_020_17165_w crossref_primary_10_1109_TPAMI_2014_2353639 crossref_primary_10_1186_s12940_023_01007_5 crossref_primary_10_1186_s12864_016_3426_3 crossref_primary_10_1038_s41467_024_55698_6 crossref_primary_10_1080_15592294_2018_1530008 crossref_primary_10_1080_01621459_2021_1914634 crossref_primary_10_1007_s10120_018_0803_4 crossref_primary_10_1177_15353702211007766 crossref_primary_10_1016_j_gene_2024_148903 crossref_primary_10_1038_ncomms9699 crossref_primary_10_1186_s13059_017_1186_2 crossref_primary_10_1186_s12859_024_05658_0 crossref_primary_10_1289_EHP10174 crossref_primary_10_1038_ncomms10478 crossref_primary_10_1371_journal_pone_0122146 crossref_primary_10_1093_humrep_dead191 crossref_primary_10_1038_ncomms13507 crossref_primary_10_1186_s13072_025_00616_3 crossref_primary_10_1002_wsbm_1242 crossref_primary_10_1016_j_neo_2016_08_008 crossref_primary_10_1038_s41598_023_37511_4 crossref_primary_10_1038_s41598_021_85812_3 crossref_primary_10_1016_j_envint_2019_03_071 crossref_primary_10_1017_S0954579417001213 crossref_primary_10_1038_tp_2016_297 crossref_primary_10_1186_s13073_022_01116_9 crossref_primary_10_2217_epi_15_2 crossref_primary_10_3389_fgene_2023_1248088 crossref_primary_10_1038_s41467_023_43719_9 crossref_primary_10_1111_jcmm_18032 crossref_primary_10_1016_j_bbr_2017_09_035 crossref_primary_10_1111_exd_14047 crossref_primary_10_1016_j_jaci_2021_11_013 crossref_primary_10_1186_s12967_018_1751_9 crossref_primary_10_1530_REP_16_0014 crossref_primary_10_2217_epi_2023_0424 crossref_primary_10_1016_j_bcp_2019_113699 crossref_primary_10_3390_ijerph18147429 crossref_primary_10_2217_epi_2016_0001 crossref_primary_10_1016_j_jhazmat_2021_126548 crossref_primary_10_1111_acel_70149 crossref_primary_10_1186_s13148_016_0235_0 crossref_primary_10_1002_gepi_21874 crossref_primary_10_1038_s41467_023_38891_x crossref_primary_10_1038_s41380_024_02808_x crossref_primary_10_1038_s41467_025_62533_z crossref_primary_10_1186_s13148_022_01399_0 crossref_primary_10_1186_s12863_018_0636_5 crossref_primary_10_1016_j_envint_2021_106955 crossref_primary_10_1371_journal_pone_0229763 crossref_primary_10_1080_15592294_2024_2333654 crossref_primary_10_1186_s13195_023_01216_7 crossref_primary_10_3389_fendo_2022_875180 crossref_primary_10_1002_advs_202100727 crossref_primary_10_1002_em_22095 crossref_primary_10_1016_j_devcel_2019_11_007 crossref_primary_10_1038_s41467_018_05570_1 crossref_primary_10_1016_j_jad_2024_02_044 crossref_primary_10_1038_leu_2016_356 crossref_primary_10_1007_s00018_021_04091_3 crossref_primary_10_1093_cvr_cvx050 crossref_primary_10_1038_s41467_019_10461_0 crossref_primary_10_1038_s41525_019_0102_y crossref_primary_10_1089_thy_2022_0373 crossref_primary_10_1038_s41598_025_87442_5 crossref_primary_10_1007_s10238_023_01119_9 crossref_primary_10_1186_s13148_017_0336_4 crossref_primary_10_3892_ol_2017_7083 crossref_primary_10_1016_j_neures_2017_02_005 crossref_primary_10_3390_ijms221910417 crossref_primary_10_1038_s41467_022_33544_x crossref_primary_10_1080_15592294_2019_1661211 crossref_primary_10_1007_s10522_020_09874_y crossref_primary_10_1038_s41467_022_33215_x crossref_primary_10_1007_s13365_015_0406_3 crossref_primary_10_1186_s40478_019_0744_0 crossref_primary_10_1080_15592294_2020_1712876 crossref_primary_10_1186_s12940_021_00717_y crossref_primary_10_1016_j_jsbmb_2016_03_005 crossref_primary_10_1016_j_xcrm_2025_102290 crossref_primary_10_1186_s12935_020_01640_x crossref_primary_10_1371_journal_pone_0204228 crossref_primary_10_1038_s41398_019_0376_y crossref_primary_10_1038_bjc_2013_496 crossref_primary_10_1038_s41467_017_01297_7 crossref_primary_10_4161_epi_28041
Cites_doi	10.4161/epi.6.6.16196 10.1038/ng1909 10.2217/epi.12.21 10.1038/nrg1748 10.1186/1471-2105-9-365 10.1016/0022-2836(87)90689-9 10.1038/nature09230 10.1093/bioinformatics/btq470 10.1093/ije/dyr238 10.1073/pnas.052410099 10.1016/j.ygeno.2011.07.007 10.1093/bioinformatics/bts013 10.1016/j.cell.2007.01.029 10.1186/gb-2012-13-6-r44 10.1186/1471-2105-13-59 10.1093/bioinformatics/bti318 10.1186/1471-2105-11-587 10.1038/nbt1010-1049 10.1093/biostatistics/kxq005 10.2217/epi.09.14 10.1038/nature10866 10.1007/0-387-29362-0_23 10.2217/epi.11.105 10.1038/nrg3000 10.1073/pnas.0812945106 10.1038/nrc1799
ContentType	Journal Article
Copyright	The Author 2012. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com 2012
Copyright_xml	– notice: The Author 2012. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com 2012
DBID	AAYXX CITATION CGR CUY CVF ECM EIF NPM 7X8 7QO 7TM 8FD FR3 P64 7SC JQ2 L7M L~C L~D 5PM ADTPV AOWAS D8T ZZAVC
DOI	10.1093/bioinformatics/bts680
DatabaseName	CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed MEDLINE - Academic Biotechnology Research Abstracts Nucleic Acids Abstracts Technology Research Database Engineering Research Database Biotechnology and BioEngineering Abstracts Computer and Information Systems Abstracts ProQuest Computer Science Collection Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional PubMed Central (Full Participant titles) SwePub SwePub Articles SWEPUB Freely available online SwePub Articles full text
DatabaseTitle	CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) MEDLINE - Academic Engineering Research Database Biotechnology Research Abstracts Technology Research Database Nucleic Acids Abstracts Biotechnology and BioEngineering Abstracts Computer and Information Systems Abstracts Computer and Information Systems Abstracts – Academic Advanced Technologies Database with Aerospace ProQuest Computer Science Collection Computer and Information Systems Abstracts Professional
DatabaseTitleList	MEDLINE - Academic Engineering Research Database Computer and Information Systems Abstracts CrossRef MEDLINE
Database_xml	– sequence: 1 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: 7X8 name: MEDLINE - Academic url: https://search.proquest.com/medline sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Biology
EISSN	1367-4811 1460-2059
EndPage	196
ExternalDocumentID	oai_swepub_ki_se_533201 PMC3546795 23175756 10_1093_bioinformatics_bts680
Genre	Research Support, Non-U.S. Gov't Journal Article
GrantInformation_xml	– fundername: Wellcome Trust grantid: 084071 – fundername: Wellcome Trust grantid: 093855
GroupedDBID	--- -E4 -~X .2P .DC .I3 0R~ 1TH 23N 2WC 4.4 48X 53G 5GY 5WA 70D AAIJN AAIMJ AAJKP AAJQQ AAKPC AAMDB AAMVS AAOGV AAPQZ AAPXW AAUQX AAVAP AAVLN AAYXX ABEJV ABEUO ABGNP ABIXL ABNKS ABPQP ABPTD ABQLI ABWST ABXVV ABZBJ ACGFS ACIWK ACPRK ACUFI ACUXJ ACYTK ADBBV ADEYI ADEZT ADFTL ADGKP ADGZP ADHKW ADHZD ADMLS ADOCK ADPDF ADRDM ADRTK ADVEK ADYVW ADZTZ ADZXQ AECKG AEGPL AEJOX AEKKA AEKSI AELWJ AEMDU AENEX AENZO AEPUE AETBJ AEWNT AFFZL AFGWE AFIYH AFOFC AFRAH AGINJ AGKEF AGQXC AGSYK AHMBA AHXPO AIJHB AJEEA AJEUX AKHUL AKWXX ALMA_UNASSIGNED_HOLDINGS ALTZX ALUQC AMNDL APIBT APWMN ARIXL ASPBG AVWKF AXUDD AYOIW AZVOD BAWUL BAYMD BHONS BQDIO BQUQU BSWAC BTQHN C45 CDBKE CITATION CS3 CZ4 DAKXR DIK DILTD DU5 D~K EBD EBS EE~ EJD EMOBN F5P F9B FEDTE FHSFR FLIZI FLUFQ FOEOM FQBLK GAUVT GJXCC GROUPED_DOAJ GX1 H13 H5~ HAR HW0 HZ~ IOX J21 JXSIZ KAQDR KOP KQ8 KSI KSN M-Z MK~ ML0 N9A NGC NLBLG NMDNZ NOMLY NU- NVLIB O0~ O9- OAWHX ODMLO OJQWA OK1 OVD OVEED P2P PAFKI PEELM PQQKQ Q1. Q5Y R44 RD5 RNS ROL ROX RPM RUSNO RW1 RXO SV3 TEORI TJP TLC TOX TR2 W8F WOQ X7H YAYTL YKOAZ YXANX ZKX ~91 ~KM ABQTQ CGR CUY CVF ECM EIF M49 NPM 7X8 482 7QO 7TM 8FD ABJNI FR3 P64 ROZ TN5 WH7 7SC JQ2 L7M L~C L~D 5PM C1A COF .-4 .GJ ABEFU ABNGD ACUKT ADTPV AFFNX AGQPQ AI. AOWAS AQDSO ATTQO AZFZN CAG D8T ELUNK HVGLF NTWIH O~Y PB- RNI RZF RZO VH1 ZGI ZZAVC
ID	FETCH-LOGICAL-c581t-3ff4e252d67c08b85bcdc90041e1e34b080fd9722213c664190b4d545bd5f8aa3
ISICitedReferencesCount	1219
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000313722800006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1367-4803 1367-4811
IngestDate	Tue Nov 25 03:36:02 EST 2025 Tue Nov 04 01:45:51 EST 2025 Thu Oct 02 06:20:19 EDT 2025 Tue Oct 07 09:26:28 EDT 2025 Sun Nov 09 12:04:22 EST 2025 Thu Apr 03 07:07:14 EDT 2025 Sat Nov 29 05:33:50 EST 2025 Tue Nov 18 21:17:01 EST 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	2
Language	English
License	http://creativecommons.org/licenses/by/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
LinkModel	OpenURL
MergedId	FETCHMERGED-LOGICAL-c581t-3ff4e252d67c08b85bcdc90041e1e34b080fd9722213c664190b4d545bd5f8aa3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Associate Editor: Olga Troyanskaya
OpenAccessLink	https://pubmed.ncbi.nlm.nih.gov/PMC3546795
PMID	23175756
PQID	1273630149
PQPubID	23479
PageCount	8
ParticipantIDs	swepub_primary_oai_swepub_ki_se_533201 pubmedcentral_primary_oai_pubmedcentral_nih_gov_3546795 proquest_miscellaneous_1671449785 proquest_miscellaneous_1323249797 proquest_miscellaneous_1273630149 pubmed_primary_23175756 crossref_citationtrail_10_1093_bioinformatics_bts680 crossref_primary_10_1093_bioinformatics_bts680
PublicationCentury	2000
PublicationDate	2013-01-15
PublicationDateYYYYMMDD	2013-01-15
PublicationDate_xml	– month: 01 year: 2013 text: 2013-01-15 day: 15
PublicationDecade	2010
PublicationPlace	England
PublicationPlace_xml	– name: England
PublicationTitle	Bioinformatics
PublicationTitleAlternate	Bioinformatics
PublicationYear	2013
Publisher	Oxford University Press
Publisher_xml	– name: Oxford University Press
References	Zhuang (2023012810154280700_bts680-B27) 2012; 24 Ji (2023012810154280700_bts680-B13) 2005; 21 Bibikova (2023012810154280700_bts680-B2) 2011; 98 Wu (2023012810154280700_bts680-B25) 2010; 11 Petronis (2023012810154280700_bts680-B17) 2010; 465 Feinberg (2023012810154280700_bts680-B7) 2010; 28 Takai (2023012810154280700_bts680-B21) 2002; 99 Jaffe (2023012810154280700_bts680-B12) 2012; 41 Turcan (2023012810154280700_bts680-B23) 2012; 483 Feinberg (2023012810154280700_bts680-B8) 2006; 7 Dedeurwaerder (2023012810154280700_bts680-B4) 2011; 3 Sandoval (2023012810154280700_bts680-B19) 2011; 6 Koestler (2023012810154280700_bts680-B15) 2010; 26 Eckhardt (2023012810154280700_bts680-B6) 2006; 38 Touleimat (2023012810154280700_bts680-B22) 2012; 4 Zhao (2023012810154280700_bts680-B26) 2009; 106 Smyth (2023012810154280700_bts680-B20) 2005 Jones (2023012810154280700_bts680-B14) 2007; 128 Du (2023012810154280700_bts680-B5) 2010; 11 Gardiner-Garden (2023012810154280700_bts680-B9) 1987; 196 Wang (2023012810154280700_bts680-B24) 2012; 28 Baylin (2023012810154280700_bts680-B1) 2006; 6 Maksimovic (2023012810154280700_bts680-B16) 2012; 13 Rakyan (2023012810154280700_bts680-B18) 2011; 12 Hansen (2023012810154280700_bts680-B10) 2012 Houseman (2023012810154280700_bts680-B11) 2008; 9 Bibikova (2023012810154280700_bts680-B3) 2009; 1 22524302 - BMC Bioinformatics. 2012;13:59 22122642 - Epigenomics. 2009 Oct;1(1):177-200 18782434 - BMC Bioinformatics. 2008;9:365 11891299 - Proc Natl Acad Sci U S A. 2002 Mar 19;99(6):3740-5 3656447 - J Mol Biol. 1987 Jul 20;196(2):261-82 15713737 - Bioinformatics. 2005 May 1;21(9):2118-22 22422453 - Int J Epidemiol. 2012 Feb;41(1):200-9 21118553 - BMC Bioinformatics. 2010;11:587 20944596 - Nat Biotechnol. 2010 Oct;28(10):1049-52 20834038 - Bioinformatics. 2010 Oct 15;26(20):2578-85 20535201 - Nature. 2010 Jun 10;465(7299):721-7 21747404 - Nat Rev Genet. 2011 Aug;12(8):529-41 21593595 - Epigenetics. 2011 Jun;6(6):692-702 21839163 - Genomics. 2011 Oct;98(4):288-95 22126295 - Epigenomics. 2011 Dec;3(6):771-84 20212320 - Biostatistics. 2010 Jul;11(3):499-514 16369569 - Nat Rev Genet. 2006 Jan;7(1):21-33 22703947 - Genome Biol. 2012;13(6):R44 16491070 - Nat Rev Cancer. 2006 Feb;6(2):107-16 22343889 - Nature. 2012 Mar 22;483(7390):479-83 22690668 - Epigenomics. 2012 Jun;4(3):325-41 19181860 - Proc Natl Acad Sci U S A. 2009 Feb 10;106(6):1886-91 22253290 - Bioinformatics. 2012 Mar 1;28(5):729-30 17072317 - Nat Genet. 2006 Dec;38(12):1378-85 17320506 - Cell. 2007 Feb 23;128(4):683-92
References_xml	– volume: 6 start-page: 692 year: 2011 ident: 2023012810154280700_bts680-B19 article-title: Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome publication-title: Epigenetics doi: 10.4161/epi.6.6.16196 – volume: 38 start-page: 1378 year: 2006 ident: 2023012810154280700_bts680-B6 article-title: DNA methylation profiling of human chromosomes 6, 20 and 22 publication-title: Nat. Genet. doi: 10.1038/ng1909 – volume: 4 start-page: 325 year: 2012 ident: 2023012810154280700_bts680-B22 article-title: Complete pipeline for infinium(®) human methylation 450k beadchip data processing using subset quantile normalization for accurate dna methylation estimation publication-title: Epigenomics doi: 10.2217/epi.12.21 – volume: 7 start-page: 21 year: 2006 ident: 2023012810154280700_bts680-B8 article-title: The epigenetic progenitor origin of human cancer publication-title: Nat. Rev. Genet. doi: 10.1038/nrg1748 – volume: 9 start-page: 365 year: 2008 ident: 2023012810154280700_bts680-B11 article-title: Model-based clustering of dna methylation array data: a recursive-partitioning algorithm for high-dimensional data arising as a mixture of beta distributions publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-9-365 – volume: 196 start-page: 261 year: 1987 ident: 2023012810154280700_bts680-B9 article-title: CpG islands in vertebrate genomes publication-title: J. Mol. Biol. doi: 10.1016/0022-2836(87)90689-9 – volume: 465 start-page: 721 year: 2010 ident: 2023012810154280700_bts680-B17 article-title: Epigenetics as a unifying principle in the aetiology of complex traits and diseases publication-title: Nature doi: 10.1038/nature09230 – volume: 26 start-page: 2578 year: 2010 ident: 2023012810154280700_bts680-B15 article-title: Semi-supervised recursively partitioned mixture models for identifying cancer subtypes publication-title: Bioinformatics doi: 10.1093/bioinformatics/btq470 – volume: 41 start-page: 200 year: 2012 ident: 2023012810154280700_bts680-B12 article-title: Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies publication-title: Int. J. Epidemiol. doi: 10.1093/ije/dyr238 – volume: 99 start-page: 3740 year: 2002 ident: 2023012810154280700_bts680-B21 article-title: Comprehensive analysis of cpg islands in human chromosomes 21 and 22 publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.052410099 – volume: 98 start-page: 288 year: 2011 ident: 2023012810154280700_bts680-B2 article-title: High density DNA methylation array with single CpG site resolution publication-title: Genomics doi: 10.1016/j.ygeno.2011.07.007 – volume: 28 start-page: 729 year: 2012 ident: 2023012810154280700_bts680-B24 article-title: IMA: an R package for high-throughput analysis of illumina’s 450k infinium methylation data publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts013 – volume: 128 start-page: 683 year: 2007 ident: 2023012810154280700_bts680-B14 article-title: The epigenomics of cancer publication-title: Cell doi: 10.1016/j.cell.2007.01.029 – volume: 13 start-page: R44 year: 2012 ident: 2023012810154280700_bts680-B16 article-title: Swan: Subset quantile Within-Array Normalization for illumina infinium humanmethylation450 beadchips publication-title: Genome Biol. doi: 10.1186/gb-2012-13-6-r44 – volume: 24 start-page: 59 year: 2012 ident: 2023012810154280700_bts680-B27 article-title: A comparison of feature selection and classification methods in DNA methylation studies using the illumina 27k platform publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-13-59 – volume: 21 start-page: 2118 year: 2005 ident: 2023012810154280700_bts680-B13 article-title: Applications of beta-mixture models in bioinformatics publication-title: Bioinformatics doi: 10.1093/bioinformatics/bti318 – year: 2012 ident: 2023012810154280700_bts680-B10 – volume: 11 start-page: 587 year: 2010 ident: 2023012810154280700_bts680-B5 article-title: Comparison of Beta-value and M-value methods for quantifying methylation levels by microarray analysis publication-title: BMC Bioinformatics doi: 10.1186/1471-2105-11-587 – volume: 28 start-page: 1049 year: 2010 ident: 2023012810154280700_bts680-B7 article-title: Epigenomics reveals a functional genome anatomy and a new approach to common disease publication-title: Nat. Biotechnol. doi: 10.1038/nbt1010-1049 – volume: 11 start-page: 499 year: 2010 ident: 2023012810154280700_bts680-B25 article-title: Redefining CpG islands using hidden Markov models publication-title: Biostatistics doi: 10.1093/biostatistics/kxq005 – volume: 1 start-page: 177 year: 2009 ident: 2023012810154280700_bts680-B3 article-title: Genome-wide DNA methylation profiling using Infinium® assay publication-title: Epigenomics doi: 10.2217/epi.09.14 – volume: 483 start-page: 479 year: 2012 ident: 2023012810154280700_bts680-B23 article-title: IDH1 mutation is sufficient to establish the glioma hypermethylator phenotype publication-title: Nature doi: 10.1038/nature10866 – start-page: 397 volume-title: Bioinformatics and Computational Biology Solutions using R and Bioconductor year: 2005 ident: 2023012810154280700_bts680-B20 article-title: Limma: linear models for microarray data doi: 10.1007/0-387-29362-0_23 – volume: 3 start-page: 771 year: 2011 ident: 2023012810154280700_bts680-B4 article-title: Evaluation of the infinium methylation 450k technology publication-title: Epigenomics doi: 10.2217/epi.11.105 – volume: 12 start-page: 529 year: 2011 ident: 2023012810154280700_bts680-B18 article-title: Epigenome-wide association studies for common human diseases publication-title: Nat. Rev. Genet. doi: 10.1038/nrg3000 – volume: 106 start-page: 1886 year: 2009 ident: 2023012810154280700_bts680-B26 article-title: Transcriptome-guided characterization of genomic rearrangements in a breast cancer cell line publication-title: Proc. Natl Acad. Sci. USA doi: 10.1073/pnas.0812945106 – volume: 6 start-page: 107 year: 2006 ident: 2023012810154280700_bts680-B1 article-title: Epigenetic gene silencing in cancer—a mechanism for early oncogenic pathway addiction? Nat publication-title: Rev. Cancer doi: 10.1038/nrc1799 – reference: 3656447 - J Mol Biol. 1987 Jul 20;196(2):261-82 – reference: 17320506 - Cell. 2007 Feb 23;128(4):683-92 – reference: 22126295 - Epigenomics. 2011 Dec;3(6):771-84 – reference: 22122642 - Epigenomics. 2009 Oct;1(1):177-200 – reference: 21839163 - Genomics. 2011 Oct;98(4):288-95 – reference: 15713737 - Bioinformatics. 2005 May 1;21(9):2118-22 – reference: 22343889 - Nature. 2012 Mar 22;483(7390):479-83 – reference: 21593595 - Epigenetics. 2011 Jun;6(6):692-702 – reference: 22524302 - BMC Bioinformatics. 2012;13:59 – reference: 16369569 - Nat Rev Genet. 2006 Jan;7(1):21-33 – reference: 22253290 - Bioinformatics. 2012 Mar 1;28(5):729-30 – reference: 20535201 - Nature. 2010 Jun 10;465(7299):721-7 – reference: 21118553 - BMC Bioinformatics. 2010;11:587 – reference: 20212320 - Biostatistics. 2010 Jul;11(3):499-514 – reference: 20944596 - Nat Biotechnol. 2010 Oct;28(10):1049-52 – reference: 19181860 - Proc Natl Acad Sci U S A. 2009 Feb 10;106(6):1886-91 – reference: 17072317 - Nat Genet. 2006 Dec;38(12):1378-85 – reference: 11891299 - Proc Natl Acad Sci U S A. 2002 Mar 19;99(6):3740-5 – reference: 16491070 - Nat Rev Cancer. 2006 Feb;6(2):107-16 – reference: 18782434 - BMC Bioinformatics. 2008;9:365 – reference: 22690668 - Epigenomics. 2012 Jun;4(3):325-41 – reference: 22422453 - Int J Epidemiol. 2012 Feb;41(1):200-9 – reference: 20834038 - Bioinformatics. 2010 Oct 15;26(20):2578-85 – reference: 21747404 - Nat Rev Genet. 2011 Aug;12(8):529-41 – reference: 22703947 - Genome Biol. 2012;13(6):R44
SSID	ssj0005056 ssj0051444
Score	2.6276877
Snippet	Motivation: The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a... The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty...
SourceID	swepub pubmedcentral proquest pubmed crossref
SourceType	Open Access Repository Aggregation Database Index Database Enrichment Source
StartPage	189
SubjectTerms	Algorithms Bias Bioinformatics Deoxyribonucleic acid DNA Methylation Mathematical models Methylation Neoplasms - genetics Normal Distribution Nucleic Acid Probes - chemistry Oligonucleotide Array Sequence Analysis - methods Original Papers Quantiles Strategy Transformations
Title	A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data
URI	https://www.ncbi.nlm.nih.gov/pubmed/23175756 https://www.proquest.com/docview/1273630149 https://www.proquest.com/docview/1323249797 https://www.proquest.com/docview/1671449785 https://pubmed.ncbi.nlm.nih.gov/PMC3546795 http://kipublications.ki.se/Default.aspx?queryparsed=id:126019884
Volume	29
WOSCitedRecordID	wos000313722800006&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText	1
inHoldings	1
isFullTextHit
isPrint
journalDatabaseRights	– providerCode: PRVASL databaseName: Oxford Journals Open Access Collection customDbUrl: eissn: 1367-4811 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0005056 issn: 1367-4803 databaseCode: TOX dateStart: 19850101 isFulltext: true titleUrlDefault: https://academic.oup.com/journals/ providerName: Oxford University Press – providerCode: PRVASL databaseName: Oxford Journals Open Access Collection customDbUrl: eissn: 1367-4811 dateEnd: 20220930 omitProxy: false ssIdentifier: ssj0005056 issn: 1367-4803 databaseCode: TOX dateStart: 19850101 isFulltext: true titleUrlDefault: https://academic.oup.com/journals/ providerName: Oxford University Press
link	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lj5swELZ201bqpeq76WPlSlUviN0ABuNjtN2qldp0D2mVGwJjtNZmnTSPVfbQ_97xgwCNlD6kXhAyGIznY5gxM_Mh9CYkIi0rQvwijUNwUGLi55EgfhWWRQBOMxcmw_vbJzoapZMJOz847NW5MNdTqlS62bD5fxU1tIGwdersX4h7e1FogH0QOmxB7LD9I8EPdexV7l_Jjfk58H0Ncwevvqe0dTp1aZeOOdoEGXJN0MFXNi1dx16UJqrDK2RugmU_ajJkqXLQJZVUcn3lkXjgXXrvRkNzmRsbTue5NLfmH7GcubKsphS0rmu6qUPpHXdIax1iLMDPFqqcLVydSBNp6Z0dN2vmi7yQ1tg1dCDQYdbEE_E6dccwmMu8Wf6HOZq6aORWOJRb6dCsE4Fvcz33ZVC2lHeka7inA6swRbvNKXSn8d2zyZbjbdV3YOmMnCUQWK7dnY-MLcBVdCZRN6yWiWWlaqFsfmVgFmozjca_FP02ZsT559Mohs8Viw_RrZDGTOvm8ZdJE6g0MBzE26er89BYdNIdw4kdga5v7W7XNbZ2PKjdQOBOuVxjYo3vo3vON8JDi-kH6ECoh-iOZUu9eYR-DHEb2bhGNu4gG1tkYxgvbpCNDbKxRTbWyMZS4RrZuEY2BmTjSwzIxi1kY43sx-jr-7Px6QffsYf4PE6DlR9VFRFhHJYJ5YMUVFHBS850fTkRiIgU4CpVJaNgHwcRTxIClnFBSnAoijKu0jyPnqCeminxDGEaVTzlg7wiHAxwzljCwfPnPAySAix60UeknuaMu9L6muFlmtkQjyjrCiqzguqj4223ua0t87sOr2sZZvAV0L_2ciVm62UWgBeS6NURtuecSHtPjDK655yEBkSTTsZ99NRiYzu0GlR9RDuo2Z6gK9V3jyh5YSrWO4D30VuLr04X13QJeyID7xNe_ef_fIsX6G6jOl6i3mqxFq_QbX69ksvFETqkk_TIvF4_AVGBKgc
linkProvider	Oxford University Press
openUrl	ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+beta-mixture+quantile+normalization+method+for+correcting+probe+design+bias+in+Illumina+Infinium+450+k+DNA+methylation+data&rft.jtitle=Bioinformatics+%28Oxford%2C+England%29&rft.au=Teschendorff%2C+Andrew+E.&rft.au=Marabita%2C+Francesco&rft.au=Lechner%2C+Matthias&rft.au=Bartlett%2C+Thomas&rft.date=2013-01-15&rft.pub=Oxford+University+Press&rft.issn=1367-4803&rft.eissn=1367-4811&rft.volume=29&rft.issue=2&rft.spage=189&rft.epage=196&rft_id=info:doi/10.1093%2Fbioinformatics%2Fbts680&rft_id=info%3Apmid%2F23175756&rft.externalDocID=PMC3546795
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1367-4803&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1367-4803&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1367-4803&client=summon