A fast algorithm for Bayesian multi-locus model in genome-wide association studies
Genome-wide association studies (GWAS) have identified a large amount of single-nucleotide polymorphisms (SNPs) associated with complex traits. A recently developed linear mixed model for estimating heritability by simultaneously fitting all SNPs suggests that common variants can explain a substanti...
Uloženo v:
| Vydáno v: | Molecular genetics and genomics : MGG Ročník 292; číslo 4; s. 923 - 934 |
|---|---|
| Hlavní autoři: | , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Berlin/Heidelberg
Springer Berlin Heidelberg
01.08.2017
Springer Nature B.V |
| Témata: | |
| ISSN: | 1617-4615, 1617-4623, 1617-4623 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Genome-wide association studies (GWAS) have identified a large amount of single-nucleotide polymorphisms (SNPs) associated with complex traits. A recently developed linear mixed model for estimating heritability by simultaneously fitting all SNPs suggests that common variants can explain a substantial fraction of heritability, which hints at the low power of single variant analysis typically used in GWAS. Consequently, many multi-locus shrinkage models have been proposed under a Bayesian framework. However, most use Markov Chain Monte Carlo (MCMC) algorithm, which are time-consuming and challenging to apply to GWAS data. Here, we propose a fast algorithm of Bayesian adaptive lasso using variational inference (BAL-VI). Extensive simulations and real data analysis indicate that our model outperforms the well-known Bayesian lasso and Bayesian adaptive lasso models in accuracy and speed. BAL-VI can complete a simultaneous analysis of a lung cancer GWAS data with ~3400 subjects and ~570,000 SNPs in about half a day. |
|---|---|
| AbstractList | Genome-wide association studies (GWAS) have identified a large amount of single-nucleotide polymorphisms (SNPs) associated with complex traits. A recently developed linear mixed model for estimating heritability by simultaneously fitting all SNPs suggests that common variants can explain a substantial fraction of heritability, which hints at the low power of single variant analysis typically used in GWAS. Consequently, many multi-locus shrinkage models have been proposed under a Bayesian framework. However, most use Markov Chain Monte Carlo (MCMC) algorithm, which are time-consuming and challenging to apply to GWAS data. Here, we propose a fast algorithm of Bayesian adaptive lasso using variational inference (BAL-VI). Extensive simulations and real data analysis indicate that our model outperforms the well-known Bayesian lasso and Bayesian adaptive lasso models in accuracy and speed. BAL-VI can complete a simultaneous analysis of a lung cancer GWAS data with ~3400 subjects and ~570,000 SNPs in about half a day. Genome-wide association studies (GWAS) have identified a large amount of single-nucleotide polymorphisms (SNPs) associated with complex traits. A recently developed linear mixed model for estimating heritability by simultaneously fitting all SNPs suggests that common variants can explain a substantial fraction of heritability, which hints at the low power of single variant analysis typically used in GWAS. Consequently, many multi-locus shrinkage models have been proposed under a Bayesian framework. However, most use Markov Chain Monte Carlo (MCMC) algorithm, which are time-consuming and challenging to apply to GWAS data. Here, we propose a fast algorithm of Bayesian adaptive lasso using variational inference (BAL-VI). Extensive simulations and real data analysis indicate that our model outperforms the well-known Bayesian lasso and Bayesian adaptive lasso models in accuracy and speed. BAL-VI can complete a simultaneous analysis of a lung cancer GWAS data with ~3400 subjects and ~570,000 SNPs in about half a day. Genome-wide association studies (GWAS) have identified a large amount of single-nucleotide polymorphisms (SNPs) associated with complex traits. A recently developed linear mixed model for estimating heritability by simultaneously fitting all SNPs suggests that common variants can explain a substantial fraction of heritability, which hints at the low power of single variant analysis typically used in GWAS. Consequently, many multi-locus shrinkage models have been proposed under a Bayesian framework. However, most use Markov Chain Monte Carlo (MCMC) algorithm, which are time-consuming and challenging to apply to GWAS data. Here, we propose a fast algorithm of Bayesian adaptive lasso using variational inference (BAL-VI). Extensive simulations and real data analysis indicate that our model outperforms the well-known Bayesian lasso and Bayesian adaptive lasso models in accuracy and speed. BAL-VI can complete a simultaneous analysis of a lung cancer GWAS data with ~3400 subjects and ~570,000 SNPs in about half a day.Genome-wide association studies (GWAS) have identified a large amount of single-nucleotide polymorphisms (SNPs) associated with complex traits. A recently developed linear mixed model for estimating heritability by simultaneously fitting all SNPs suggests that common variants can explain a substantial fraction of heritability, which hints at the low power of single variant analysis typically used in GWAS. Consequently, many multi-locus shrinkage models have been proposed under a Bayesian framework. However, most use Markov Chain Monte Carlo (MCMC) algorithm, which are time-consuming and challenging to apply to GWAS data. Here, we propose a fast algorithm of Bayesian adaptive lasso using variational inference (BAL-VI). Extensive simulations and real data analysis indicate that our model outperforms the well-known Bayesian lasso and Bayesian adaptive lasso models in accuracy and speed. BAL-VI can complete a simultaneous analysis of a lung cancer GWAS data with ~3400 subjects and ~570,000 SNPs in about half a day. |
| Author | Duan, Weiwei Yang, Sheng Huang, Lihong Du, Mulong Hu, Zhibin Zhao, Yang Chen, Feng Shen, Sipeng Wei, Yongyue Bai, Jianling |
| Author_xml | – sequence: 1 givenname: Weiwei surname: Duan fullname: Duan, Weiwei organization: Department of Biostatistics, School of Public Health, Nanjing Medical University, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Joint Laboratory of Health and Environmental Risk Assessment (HERA), Nanjing Medical University School of Public Health/Harvard School of Public Health, Key Laboratory of Biomedical Big Data, Nanjing Medical University – sequence: 2 givenname: Yang surname: Zhao fullname: Zhao, Yang organization: Department of Biostatistics, School of Public Health, Nanjing Medical University, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Joint Laboratory of Health and Environmental Risk Assessment (HERA), Nanjing Medical University School of Public Health/Harvard School of Public Health, Key Laboratory of Biomedical Big Data, Nanjing Medical University – sequence: 3 givenname: Yongyue surname: Wei fullname: Wei, Yongyue organization: Department of Biostatistics, School of Public Health, Nanjing Medical University, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Joint Laboratory of Health and Environmental Risk Assessment (HERA), Nanjing Medical University School of Public Health/Harvard School of Public Health, Key Laboratory of Biomedical Big Data, Nanjing Medical University – sequence: 4 givenname: Sheng surname: Yang fullname: Yang, Sheng organization: Department of Biostatistics, School of Public Health, Nanjing Medical University, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Joint Laboratory of Health and Environmental Risk Assessment (HERA), Nanjing Medical University School of Public Health/Harvard School of Public Health, Key Laboratory of Biomedical Big Data, Nanjing Medical University – sequence: 5 givenname: Jianling surname: Bai fullname: Bai, Jianling organization: Department of Biostatistics, School of Public Health, Nanjing Medical University, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Joint Laboratory of Health and Environmental Risk Assessment (HERA), Nanjing Medical University School of Public Health/Harvard School of Public Health, Key Laboratory of Biomedical Big Data, Nanjing Medical University – sequence: 6 givenname: Sipeng surname: Shen fullname: Shen, Sipeng organization: Department of Biostatistics, School of Public Health, Nanjing Medical University, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Joint Laboratory of Health and Environmental Risk Assessment (HERA), Nanjing Medical University School of Public Health/Harvard School of Public Health, Key Laboratory of Biomedical Big Data, Nanjing Medical University – sequence: 7 givenname: Mulong surname: Du fullname: Du, Mulong organization: Department of Biostatistics, School of Public Health, Nanjing Medical University, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Joint Laboratory of Health and Environmental Risk Assessment (HERA), Nanjing Medical University School of Public Health/Harvard School of Public Health, Key Laboratory of Biomedical Big Data, Nanjing Medical University – sequence: 8 givenname: Lihong surname: Huang fullname: Huang, Lihong organization: Department of Biostatistics, School of Public Health, Nanjing Medical University, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Joint Laboratory of Health and Environmental Risk Assessment (HERA), Nanjing Medical University School of Public Health/Harvard School of Public Health, Key Laboratory of Biomedical Big Data, Nanjing Medical University – sequence: 9 givenname: Zhibin surname: Hu fullname: Hu, Zhibin organization: The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Department of Epidemiology, School of Public Health, Nanjing Medical University, Section of Clinical Epidemiology, Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Nanjing Medical University – sequence: 10 givenname: Feng surname: Chen fullname: Chen, Feng email: fengchen@njmu.edu.cn organization: Department of Biostatistics, School of Public Health, Nanjing Medical University, The Key Laboratory of Modern Toxicology of Ministry of Education, School of Public Health, Nanjing Medical University, Joint Laboratory of Health and Environmental Risk Assessment (HERA), Nanjing Medical University School of Public Health/Harvard School of Public Health, Key Laboratory of Biomedical Big Data, Nanjing Medical University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28534238$$D View this record in MEDLINE/PubMed |
| BookMark | eNqFkVtrFTEUhYNU7EV_gC8S8MWX0VwnM4-1eIOCIPocMpOdY8pMUrMzlP57czytSEF9SgLfWtl7rVNylHICQp5z9pozZt4gY0oOHeOm41KITj0iJ7xvL9ULefT7zvUxOUW8Yg3shXlCjsWgpRJyOCFfzmlwWKlbdrnE-n2lIRf61t0CRpfoui01dkueN6Rr9rDQmOgOUl6hu4keqEPMc3Q15kSxbj4CPiWPg1sQnt2dZ-Tb-3dfLz52l58_fLo4v-xmxXRtE5tBTVIxFriZQq8VGO8HmIKQ0jjOlNLOswlcUJPRECa_30dpHbwJQy_PyKuD73XJPzbAateIMyyLS5A3tIIxppv9OP4X5WOLxjA-qoa-fIBe5a2ktkij-CDGYeSmUS_uqG1awdvrEldXbu19sA0wB2AuGbFAsHOsv2KqxcXFcmb3FdpDhbZ9b_cV2v0A_IHy3vxfGnHQYGPTDsofQ_9V9BPdQ6uX |
| CitedBy_id | crossref_primary_10_1080_21655979_2020_1860479 crossref_primary_10_1002_ijc_32079 crossref_primary_10_3390_jpm9030038 crossref_primary_10_1186_s40246_018_0179_x |
| Cites_doi | 10.1002/gepi.21772 10.1038/nature08494 10.1038/hdy.2009.180 10.1016/j.ajhg.2016.07.022 10.1080/01621459.1993.10476353 10.1371/journal.pgen.1004969 10.1111/j.1467-9868.2011.00771.x 10.2147/DDDT.S87197 10.1038/ng.875 10.1214/11-AOAS455 10.1038/sj.onc.1205405 10.1002/ijc.27426 10.1371/journal.pgen.1003264 10.1158/0008-5472.CAN-08-1083 10.1093/bioinformatics/btq688 10.1038/nrg2809 10.1038/sj.onc.1210183 10.1073/pnas.1419064111 10.1158/1541-7786.MCR-07-0142 10.1038/nmeth.1681 10.1186/s12711-014-0082-4 10.1198/016214506000000735 10.1214/09-BA403 10.1534/genetics.110.114280 10.1534/genetics.111.134866 10.1086/519795 10.1101/gr.169375.113 10.1002/ijc.30447 10.1038/ng.3190 10.1002/gepi.21809 10.1111/j.1467-9868.2005.00503.x 10.1023/A:1008932416310 10.1214/12-BA703 10.1371/journal.pone.0083745 10.1097/MPA.0000000000000542 10.1186/1471-2105-11-58 10.2307/2986138 10.1016/j.ajhg.2010.11.011 10.1038/ng.2310 10.1186/1471-2105-14-34 10.1198/016214508000000337 10.1534/genetics.115.182444 10.1111/j.1467-9868.2005.00532.x 10.1172/JCI73093 10.1534/genetics.108.099556 10.1056/NEJM200007133430201 10.1093/bioinformatics/bts261 10.1534/genetics.111.130278 10.1038/ng.546 10.1016/j.ajhg.2011.02.002 10.1534/g3.113.007096 10.1080/00031305.1992.10475878 10.1093/genetics/163.2.789 10.1111/j.2517-6161.1974.tb00989.x 10.1111/j.2517-6161.1996.tb02080.x |
| ContentType | Journal Article |
| Copyright | Springer-Verlag Berlin Heidelberg 2017 Molecular Genetics and Genomics is a copyright of Springer, 2017. |
| Copyright_xml | – notice: Springer-Verlag Berlin Heidelberg 2017 – notice: Molecular Genetics and Genomics is a copyright of Springer, 2017. |
| DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7SS 7TK 7TM 7X7 7XB 88A 88E 8AO 8FD 8FE 8FH 8FI 8FJ 8FK ABUWG AFKRA AZQEC BBNVY BENPR BHPHI CCPQU DWQXO FR3 FYUFA GHDGH GNUQQ HCIFZ K9. LK8 M0S M1P M7N M7P P64 PHGZM PHGZT PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS RC3 7X8 7S9 L.6 |
| DOI | 10.1007/s00438-017-1322-4 |
| DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Entomology Abstracts (Full archive) Neurosciences Abstracts Nucleic Acids Abstracts Health & Medical Collection ProQuest Central (purchase pre-March 2016) Biology Database (Alumni Edition) Medical Database (Alumni Edition) ProQuest Pharma Collection Technology Research Database ProQuest SciTech Collection ProQuest Natural Science Journals Hospital Premium Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) ProQuest Central (Alumni) ProQuest Central UK/Ireland ProQuest Central Essentials Biological Science Collection ProQuest Central Natural Science Collection ProQuest One Community College ProQuest Central Engineering Research Database Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) Biological Sciences ProQuest Health & Medical Collection Medical Database Algology Mycology and Protozoology Abstracts (Microbiology C) Biological Science Database Biotechnology and BioEngineering Abstracts ProQuest Central Premium ProQuest One Academic (New) ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) ProQuest One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China Genetics Abstracts MEDLINE - Academic AGRICOLA AGRICOLA - Academic |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) ProQuest Central Student Technology Research Database ProQuest One Academic Middle East (New) ProQuest Central Essentials Nucleic Acids Abstracts ProQuest Health & Medical Complete (Alumni) ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest One Health & Nursing ProQuest Natural Science Collection ProQuest Pharma Collection ProQuest Central China ProQuest Biology Journals (Alumni Edition) ProQuest Central ProQuest One Applied & Life Sciences ProQuest Health & Medical Research Collection Genetics Abstracts Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Algology Mycology and Protozoology Abstracts (Microbiology C) Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest Biological Science Collection ProQuest One Academic Eastern Edition ProQuest Hospital Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection Neurosciences Abstracts ProQuest Hospital Collection (Alumni) Biotechnology and BioEngineering Abstracts Entomology Abstracts ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition Engineering Research Database ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic AGRICOLA AGRICOLA - Academic |
| DatabaseTitleList | AGRICOLA ProQuest Central Student MEDLINE - Academic 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: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Biology |
| EISSN | 1617-4623 |
| EndPage | 934 |
| ExternalDocumentID | 28534238 10_1007_s00438_017_1322_4 |
| Genre | Journal Article |
| GrantInformation_xml | – fundername: National Natural Science Foundation of China grantid: 81402764; 81473070; 81530088 funderid: http://dx.doi.org/10.13039/501100001809 – fundername: Priority Academic Program Development of Jiangsu Higher Education Institutions – fundername: Research and Innovation Project for College Graduates of Jiangsu Province of China grantid: KYLX16_1123 – fundername: National Natural Science Foundation of China (CN) grantid: 81373102 |
| GroupedDBID | --- -4W -56 -5G -BR -DZ -EM -Y2 -~C -~X .55 .86 .GJ 06C 06D 0R~ 0VY 199 1N0 2.D 203 29M 29~ 2J2 2JN 2JY 2KG 2KM 2LR 2P1 2VQ 2~H 30V 3V. 4.4 406 408 409 40D 40E 53G 5RE 5VS 67N 67Z 6NX 78A 7X7 88A 88E 8AO 8FE 8FH 8FI 8FJ 8TC 8UJ 95- 95. 95~ 96X A8Z AAAVM AABHQ AACDK AAGAY AAHBH AAHNG AAIAL AAJBT AAJKR AANXM AANZL AARHV AARTL AASML AATNV AATVU AAUYE AAWCG AAYIU AAYOK AAYQN AAYTO AAYZH ABAKF ABBBX ABBXA ABDPE ABDZT ABECU ABFTV ABHLI ABHQN ABJNI ABJOX ABKCH ABKTR ABLJU ABMNI ABMQK ABNWP ABPLI ABQBU ABQSL ABSXP ABTEG ABTHY ABTKH ABTMW ABULA ABUWG ABWNU ABXPI ACAOD ACBXY ACDTI ACGFS ACHSB ACHXU ACKNC ACMDZ ACMLO ACNCT ACOKC ACOMO ACPIV ACPRK ACZOJ ADBBV ADHIR ADIMF ADINQ ADKNI ADKPE ADRFC ADTPH ADURQ ADYFF ADYPR ADZKW AEBTG AEFQL AEGAL AEGNC AEJHL AEJRE AEKMD AEMSY AENEX AEOHA AEPYU AESKC AETLH AEVLU AEXYK AFBBN AFDYV AFEXP AFFNX AFGCZ AFKRA AFLOW AFQWF AFWTZ AFZKB AGAYW AGDGC AGJBK AGMZJ AGQEE AGQMX AGRTI AGWIL AGWZB AGYKE AHAVH AHBYD AHKAY AHMBA AHSBF AHYZX AIAKS AIGIU AIIXL AILAN AITGF AJBLW AJRNO AJZVZ AKMHD ALIPV ALMA_UNASSIGNED_HOLDINGS ALWAN AMKLP AMXSW AMYLF AOCGG ARMRJ AXYYD AZFZN B-. BA0 BBNVY BDATZ BENPR BGNMA BHPHI BPHCQ BSONS BVXVI CAG CCPQU COF CSCUP DDRTE DL5 DNIVK DPUIP DU5 EBD EBLON EBS EIOEI EJD EMB EMOBN EN4 EPAXT ESBYG F5P FEDTE FERAY FFXSO FIGPU FINBP FNLPD FRRFC FSGXE FWDCC FYUFA G-Y G-Z GGCAI GGRSB GJIRD GNWQR GQ6 GQ7 GQ8 GXS H13 HCIFZ HF~ HG5 HG6 HLICF HMCUK HMJXF HQYDN HRMNR HVGLF HZ~ I09 IHE IJ- IKXTQ ITM IWAJR IXC IZIGR IZQ I~X I~Z J-C J0Z JBSCW JCJTX JZLTJ KDC KOV KPH L7B LAS LK8 LLZTM M0L M1P M4Y M7P MA- MQGED MVM N2Q NB0 NDZJH NPVJJ NQJWS NU0 O9- O93 O9G O9I O9J OAM OVD P0- P19 PF- PQQKQ PROAC PSQYO PT4 PT5 Q2X QF4 QM4 QN7 QO4 QOR QOS R89 R9I RHV RIG RNS ROL RPX RRX RSV S16 S1Z S26 S27 S28 S3A S3B SAP SBL SBY SCLPG SDH SDM SHX SISQX SJYHP SNE SNPRN SNX SOHCF SOJ SPISZ SRMVM SSLCW SSXJD STPWE SV3 SZN T13 T16 TEORI TSG TSK TSV TUC U2A U9L UG4 UKHRP UOJIU UTJUX UZXMN VC2 VFIZW W23 W48 WJK WK8 X7M YLTOR Z45 Z7U Z7V Z7W Z7Y Z87 Z8O Z8P Z8Q Z8S Z91 ZGI ZMTXR ZOVNA ZXP ~EX ~KM AAPKM AAYXX ABBRH ABDBE ABFSG ABRTQ ACSTC ADHKG AEZWR AFDZB AFFHD AFHIU AFOHR AGQPQ AHPBZ AHWEU AIXLP ATHPR AYFIA CITATION PHGZM PHGZT PJZUB PPXIY PQGLB CGR CUY CVF ECM EIF NPM 7SS 7TK 7TM 7XB 8FD 8FK AZQEC DWQXO ESTFP FR3 GNUQQ K9. M7N P64 PKEHL PQEST PQUKI PRINS RC3 7X8 PUEGO 7S9 L.6 |
| ID | FETCH-LOGICAL-c405t-13784b3400f17bf654e7dd8ebf2337a10445ad0beaf4b75efbd1617455fd7f863 |
| IEDL.DBID | RSV |
| ISICitedReferencesCount | 3 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000405521400017&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1617-4615 1617-4623 |
| IngestDate | Thu Oct 02 06:25:35 EDT 2025 Mon Sep 08 17:39:47 EDT 2025 Tue Nov 04 22:06:32 EST 2025 Thu Apr 03 07:08:54 EDT 2025 Sat Nov 29 06:46:16 EST 2025 Tue Nov 18 22:41:12 EST 2025 Fri Feb 21 02:26:25 EST 2025 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 4 |
| Keywords | Bayesian adaptive lasso Genome-wide association studies Multi-locus model Variational inference Variable selection |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c405t-13784b3400f17bf654e7dd8ebf2337a10445ad0beaf4b75efbd1617455fd7f863 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| PMID | 28534238 |
| PQID | 1918298917 |
| PQPubID | 55367 |
| PageCount | 12 |
| ParticipantIDs | proquest_miscellaneous_2000540099 proquest_miscellaneous_1901770194 proquest_journals_1918298917 pubmed_primary_28534238 crossref_citationtrail_10_1007_s00438_017_1322_4 crossref_primary_10_1007_s00438_017_1322_4 springer_journals_10_1007_s00438_017_1322_4 |
| PublicationCentury | 2000 |
| PublicationDate | 20170800 2017-8-00 2017-Aug 20170801 |
| PublicationDateYYYYMMDD | 2017-08-01 |
| PublicationDate_xml | – month: 8 year: 2017 text: 20170800 |
| PublicationDecade | 2010 |
| PublicationPlace | Berlin/Heidelberg |
| PublicationPlace_xml | – name: Berlin/Heidelberg – name: Germany – name: Heidelberg |
| PublicationTitle | Molecular genetics and genomics : MGG |
| PublicationTitleAbbrev | Mol Genet Genomics |
| PublicationTitleAlternate | Mol Genet Genomics |
| PublicationYear | 2017 |
| Publisher | Springer Berlin Heidelberg Springer Nature B.V |
| Publisher_xml | – name: Springer Berlin Heidelberg – name: Springer Nature B.V |
| References | Andrews, Mallows (CR1) 1974; 36 Singh, Arcaroli, Orlicky, Chen, Messersmith, Bagby, Purkey, Quackenbush, Thompson, Vasiliou (CR42) 2016; 45 Zhou, Carbonetto, Stephens (CR56) 2013; 9 Tibshirani (CR45) 1996; 58 Nagai, Sugito, Matsubara, Tatematsu, Hida, Sekido, Nagino, Nimura, Takahashi, Osada (CR38) 2007; 26 Jaakkola, Jordan (CR20) 2000; 10 Wang, Chen, Goddard, Meuwissen, Kemper, Hayes (CR47) 2015; 47 Fish, Capra, Bush (CR12) 2016; 99 Karkkainen, Sillanpää (CR22) 2013; 3 Kim, Lee, Jang, Kim, Noh, Song, Cho, Jeong, Kim, Yoo, Kim (CR24) 2008; 6 Carbonetto, Stephens (CR4) 2012; 7 Li, Sillanpää (CR27) 2012; 190 Lichtenstein, Holm, Verkasalo, Iliadou, Kaprio, Koskenvuo, Pukkala, Skytthe, Hemminki (CR29) 2000; 343 Hayashi, Iwata (CR18) 2013; 14 Gilks, Tan (CR15) 1995; 44 Lippert, Listgarten, Liu, Kadie, Davidson, Heckerman (CR30) 2011; 8 Purcell, Neale, Todd-Brown, Thomas, Ferreira, Bender, Maller, Sklar, de Bakker, Daly, Sham (CR41) 2007; 81 Zhang, Ersoz, Lai, Todhunter, Tiwari, Gore, Bradbury, Yu, Arnett, Ordovas, Buckler (CR54) 2010; 42 George, McCulloch (CR14) 1993; 88 Carlin, Louis (CR5) 2009; 149 Casella, George (CR6) 1992; 46 Moser, Lee, Hayes, Goddard, Wray, Visscher (CR36) 2015; 11 Beal (CR2) 2003 Park, Casella (CR40) 2008; 103 de Maturana, Ye, Calle, Rothman, Urrea, Kogevinas, Petrus, Chanock, Tardon, Garcia-Closas, Gonzalez-Neira, Vellalta, Carrato, Navarro, Lorente-Galdos, Silverman, Real, Wu, Malats (CR8) 2013; 8 Golan, Lander, Rosset (CR16) 2014; 111 Sun, Ibrahim, Zou (CR44) 2010; 185 Speed, Balding (CR43) 2014; 24 Guan, Stephens (CR17) 2011; 5 Logsdon, Hoffman, Mezey (CR31) 2010; 11 Eichler, Flint, Gibson, Kong, Leal, Moore, Nadeau (CR10) 2010; 11 Lee, Wray, Goddard, Visscher (CR26) 2011; 88 Xu (CR48) 2003; 163 Yi, Banerjee (CR51) 2009; 181 Frullanti, Colombo, Falvella, Galvan, Noci, De Cecco, Incarbone, Alloisio, Santambrogio, Nosotti, Tosi, Pastorino, Dragani (CR13) 2012; 131 Hu, Wu, Shi, Guo, Zhao, Yin, Yang, Dai, Hu, Tan, Li, Deng, Wang, Wu, Jin, Jiang, Yu, Zhou, Chen, Guan, Chen, Shu, Xu, Liu, Liu, Xu, Han, Bai, Zhao, Zhang, Yan, Ma, Chen, Chu, Lu, Zhang, Chen, Wang, Jin, Lu, Zhou, Lu, Wu, Lin, Shen (CR19) 2011; 43 de Maturana, Chanok, Picornell, Rothman, Herranz, Calle, Garcia-Closas, Marenne, Brand, Tardon, Carrato, Silverman, Kogevinas, Gianola, Real, Malats (CR9) 2014; 38 Zou, Hastie (CR58) 2005; 67 Mutshinda, Sillanpää (CR37) 2012; 192 Logsdon, Dai, Auer, Johnsen, Ganesh, Smith, Wilson, Tracy, Lange, Jiao, Rich, Lettre, Carlson, Jackson, O’Donnell, Wurfel, Nickerson, Tang, Reiner, Kooperberg (CR33) 2014; 38 O’Hara (CR39) 2009; 4 You, Guo, Xu (CR52) 2015; 9 Zhou, Stephens (CR55) 2012; 44 Logsdon, Carty, Reiner, Dai, Kooperberg (CR32) 2012; 28 Yang, Lee, Goddard, Visscher (CR50) 2011; 88 Bishop (CR3) 2006 Jeon, Dracheva, Yang, Meerzaman, Fukuoka, Shakoori, Shilo, Travis, Jen (CR21) 2008; 68 Feng, Lopez, Kim, Alvarez, Duncan, Nishikawa, Nagane, Su, Auron, Hedberg, Wang, Raizer, Kessler, Parsa, Gao, Kim, Minata, Nakano, Grandis, McLendon, Bigner, Lin, Furnari, Cavenee, Hu, Yan, Cheng (CR11) 2014; 124 Zou (CR57) 2006; 101 Karkkainen, Li, Sillanpää (CR23) 2015; 201 Tibshirani (CR46) 2011; 73 Yuan, Lin (CR53) 2006; 68 Dai, Shen, Wen, Chang, Wang, Chen, Jin, Ma, Wu, Li, Song, Zeng, Jiang, Chen, Wang, Zhu, Zhou, Du, Xiang, Shu, Hu, Zhou, Chen, Xu, Jia, Lin, Zheng, Shen (CR7) 2016; 140 Xu (CR49) 2010; 105 Manolio, Collins, Cox, Goldstein, Hindorff, Hunter, McCarthy, Ramos, Cardon, Chakravarti, Cho, Guttmacher, Kong, Kruglyak, Mardis, Rotimi, Slatkin, Valle, Whittemore, Boehnke, Clark, Eichler, Gibson, Haines, Mackay, McCarroll, Visscher (CR35) 2009; 461 Koshikawa, Osada, Kozaki, Konishi, Masuda, Tatematsu, Mitsudomi, Nakao, Takahashi (CR25) 2002; 21 Loh, Tucker, Bulik-Sullivan, Vilhjalmsson, Finucane, Salem, Chasman, Ridker, Neale, Berger, Patterson, Price (CR34) 2015; 47 Li, Das, Fu, Li, Wu (CR28) 2011; 27 BA Logsdon (1322_CR32) 2012; 28 MJ Beal (1322_CR2) 2003 M Yuan (1322_CR53) 2006; 68 HP Karkkainen (1322_CR22) 2013; 3 HP Karkkainen (1322_CR23) 2015; 201 P Carbonetto (1322_CR4) 2012; 7 X Zhou (1322_CR55) 2012; 44 M Kim (1322_CR24) 2008; 6 EI George (1322_CR14) 1993; 88 Y Guan (1322_CR17) 2011; 5 Z Hu (1322_CR19) 2011; 43 J Li (1322_CR28) 2011; 27 TA Manolio (1322_CR35) 2009; 461 P Lichtenstein (1322_CR29) 2000; 343 N Yi (1322_CR51) 2009; 181 G Casella (1322_CR6) 1992; 46 SH Lee (1322_CR26) 2011; 88 BA Logsdon (1322_CR33) 2014; 38 EL Maturana de (1322_CR8) 2013; 8 G Moser (1322_CR36) 2015; 11 WR Gilks (1322_CR15) 1995; 44 R Tibshirani (1322_CR46) 2011; 73 X Zhou (1322_CR56) 2013; 9 D Golan (1322_CR16) 2014; 111 CM Mutshinda (1322_CR37) 2012; 192 PR Loh (1322_CR34) 2015; 47 H Nagai (1322_CR38) 2007; 26 EL Maturana de (1322_CR9) 2014; 38 EE Eichler (1322_CR10) 2010; 11 W Sun (1322_CR44) 2010; 185 K Koshikawa (1322_CR25) 2002; 21 Q You (1322_CR52) 2015; 9 S Xu (1322_CR49) 2010; 105 H Zou (1322_CR58) 2005; 67 BP Carlin (1322_CR5) 2009; 149 T Park (1322_CR40) 2008; 103 CM Bishop (1322_CR3) 2006 H Zou (1322_CR57) 2006; 101 RB O’Hara (1322_CR39) 2009; 4 E Frullanti (1322_CR13) 2012; 131 C Lippert (1322_CR30) 2011; 8 R Tibshirani (1322_CR45) 1996; 58 Z Li (1322_CR27) 2012; 190 H Feng (1322_CR11) 2014; 124 J Dai (1322_CR7) 2016; 140 Z Zhang (1322_CR54) 2010; 42 S Singh (1322_CR42) 2016; 45 J Yang (1322_CR50) 2011; 88 DF Andrews (1322_CR1) 1974; 36 S Xu (1322_CR48) 2003; 163 TS Jaakkola (1322_CR20) 2000; 10 T Hayashi (1322_CR18) 2013; 14 S Purcell (1322_CR41) 2007; 81 HS Jeon (1322_CR21) 2008; 68 BA Logsdon (1322_CR31) 2010; 11 D Speed (1322_CR43) 2014; 24 T Wang (1322_CR47) 2015; 47 AE Fish (1322_CR12) 2016; 99 19047146 - Cancer Res. 2008 Dec 1;68(23):9686-92 23363272 - BMC Bioinformatics. 2013 Jan 31;14:34 11973641 - Oncogene. 2002 Apr 25;21(18):2822-8 20105321 - BMC Bioinformatics. 2010 Jan 27;11:58 19812666 - Nature. 2009 Oct 8;461(7265):747-53 25849665 - PLoS Genet. 2015 Apr 07;11(4):e1004969 23408905 - PLoS Genet. 2013;9(2):e1003264 25642633 - Nat Genet. 2015 Mar;47(3):284-90 21167468 - Am J Hum Genet. 2011 Jan 7;88(1):76-82 22042575 - Genetics. 2012 Jan;190(1):231-49 17213806 - Oncogene. 2007 Jun 7;26(27):4025-31 17701901 - Am J Hum Genet. 2007 Sep;81(3):559-75 24482836 - Genet Epidemiol. 2014 Jan;38(1):21-30 24796258 - Genet Epidemiol. 2014 Jul;38(5):467-76 22223368 - Int J Cancer. 2012 Sep 1;131(5):E643-8 26405029 - Genetics. 2015 Nov;201(3):865-70 21156729 - Bioinformatics. 2011 Feb 15;27(4):516-23 22982577 - Genetics. 2012 Dec;192(4):1483-91 27640306 - Am J Hum Genet. 2016 Oct 6;99(4):817-830 23821618 - G3 (Bethesda). 2013 Sep 04;3(9):1511-23 25061874 - J Clin Invest. 2014 Sep;124(9):3741-56 27668986 - Int J Cancer. 2017 Jan 15;140(2):329-336 10891514 - N Engl J Med. 2000 Jul 13;343(2):78-85 12618414 - Genetics. 2003 Feb;163(2):789-801 25422463 - Proc Natl Acad Sci U S A. 2014 Dec 9;111(49):E5272-81 24391818 - PLoS One. 2013 Dec 31;8(12):e83745 25926276 - Genet Sel Evol. 2015 Apr 30;47:34 21892150 - Nat Methods. 2011 Sep 04;8(10):833-5 21725308 - Nat Genet. 2011 Jul 03;43(8):792-6 22563072 - Bioinformatics. 2012 Jul 1;28(13):1738-44 24963154 - Genome Res. 2014 Sep;24(9):1550-7 20157003 - Genetics. 2010 May;185(1):349-59 26366059 - Drug Des Devel Ther. 2015 Sep 03;9:5087-97 20479774 - Nat Rev Genet. 2010 Jun;11(6):446-50 22706312 - Nat Genet. 2012 Jun 17;44(7):821-4 19139143 - Genetics. 2009 Mar;181(3):1101-13 20208535 - Nat Genet. 2010 Apr;42(4):355-60 20051978 - Heredity (Edinb). 2010 Nov;105(5):483-94 21376301 - Am J Hum Genet. 2011 Mar 11;88(3):294-305 18314483 - Mol Cancer Res. 2008 Feb;6(2):222-30 26566217 - Pancreas. 2016 Jan;45(1):117-22 |
| References_xml | – volume: 38 start-page: 21 year: 2014 end-page: 30 ident: CR33 article-title: A variational Bayes discrete mixture test for rare variant association publication-title: Genet Epidemiol doi: 10.1002/gepi.21772 – volume: 461 start-page: 747 year: 2009 end-page: 753 ident: CR35 article-title: Finding the missing heritability of complex diseases publication-title: Nature doi: 10.1038/nature08494 – volume: 58 start-page: 267 year: 1996 end-page: 288 ident: CR45 article-title: Regression shrinkage and selection via the lasso publication-title: J R Stat Soc – volume: 105 start-page: 483 year: 2010 end-page: 494 ident: CR49 article-title: An expectation-maximization algorithm for the Lasso estimation of quantitative trait locus effects publication-title: Heredity (Edinb) doi: 10.1038/hdy.2009.180 – volume: 163 start-page: 789 year: 2003 end-page: 801 ident: CR48 article-title: Estimating polygenic effects using markers of the entire genome publication-title: Genetics – volume: 99 start-page: 817 year: 2016 end-page: 830 ident: CR12 article-title: Are interactions between cis-regulatory variants evidence for biological epistasis or statistical artifacts? publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2016.07.022 – volume: 88 start-page: 881 year: 1993 end-page: 889 ident: CR14 article-title: Variable selection via gibbs sampling publication-title: J Am Stat Assoc doi: 10.1080/01621459.1993.10476353 – volume: 11 start-page: e1004969 year: 2015 ident: CR36 article-title: Simultaneous discovery, estimation and prediction analysis of complex traits using a bayesian mixture model publication-title: PLoS Genet doi: 10.1371/journal.pgen.1004969 – volume: 73 start-page: 273 year: 2011 end-page: 282 ident: CR46 article-title: Regression shrinkage and selection via the lasso: a retrospective publication-title: J R Stat Soc Ser B Stat Methodol doi: 10.1111/j.1467-9868.2011.00771.x – volume: 9 start-page: 5087 year: 2015 end-page: 5097 ident: CR52 article-title: Distinct prognostic values and potential drug targets of ALDH1 isoenzymes in non-small-cell lung cancer publication-title: Drug Des Devel Ther doi: 10.2147/DDDT.S87197 – volume: 149 start-page: 935 year: 2009 end-page: 936 ident: CR5 article-title: Bayesian methods for data analysis publication-title: J R Stat Soc – year: 2003 ident: CR2 publication-title: Variational algorithms for approximate Bayesian inference – volume: 43 start-page: 792 year: 2011 end-page: 796 ident: CR19 article-title: A genome-wide association study identifies two new lung cancer susceptibility loci at 13q12.12 and 22q12.2 in Han Chinese publication-title: Nat Genet doi: 10.1038/ng.875 – volume: 5 start-page: 1780 year: 2011 end-page: 1815 ident: CR17 article-title: Bayesian variable selection regression for genome-wide association studies and other large-scale problems publication-title: Ann Appl Stat doi: 10.1214/11-AOAS455 – volume: 21 start-page: 2822 year: 2002 end-page: 2828 ident: CR25 article-title: Significant up-regulation of a novel gene, CLCP1, in a highly metastatic lung cancer subline as well as in lung cancers in vivo publication-title: Oncogene doi: 10.1038/sj.onc.1205405 – volume: 131 start-page: E643 year: 2012 end-page: E648 ident: CR13 article-title: Association of lung adenocarcinoma clinical stage with gene expression pattern in noninvolved lung tissue publication-title: Int J Cancer doi: 10.1002/ijc.27426 – volume: 9 start-page: e1003264 year: 2013 ident: CR56 article-title: Polygenic modeling with Bayesian sparse linear mixed models publication-title: PLoS Genet doi: 10.1371/journal.pgen.1003264 – volume: 68 start-page: 9686 year: 2008 end-page: 9692 ident: CR21 article-title: SMAD6 contributes to patient survival in non-small cell lung cancer and its knockdown reestablishes TGF-beta homeostasis in lung cancer cells publication-title: Cancer Res doi: 10.1158/0008-5472.CAN-08-1083 – volume: 27 start-page: 516 year: 2011 end-page: 523 ident: CR28 article-title: The Bayesian lasso for genome-wide association studies publication-title: Bioinformatics doi: 10.1093/bioinformatics/btq688 – volume: 11 start-page: 446 year: 2010 end-page: 450 ident: CR10 article-title: Missing heritability and strategies for finding the underlying causes of complex disease publication-title: Nat Rev Genet doi: 10.1038/nrg2809 – volume: 26 start-page: 4025 year: 2007 end-page: 4031 ident: CR38 article-title: CLCP1 interacts with semaphorin 4B and regulates motility of lung cancer cells publication-title: Oncogene doi: 10.1038/sj.onc.1210183 – volume: 111 start-page: E5272 year: 2014 end-page: E5281 ident: CR16 article-title: Measuring missing heritability: inferring the contribution of common variants publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.1419064111 – volume: 6 start-page: 222 year: 2008 end-page: 230 ident: CR24 article-title: Epigenetic down-regulation and suppressive role of DCBLD2 in gastric cancer cell proliferation and invasion publication-title: Mol Cancer Res doi: 10.1158/1541-7786.MCR-07-0142 – volume: 8 start-page: 833 year: 2011 end-page: 835 ident: CR30 article-title: FaST linear mixed models for genome-wide association studies publication-title: Nat Methods doi: 10.1038/nmeth.1681 – volume: 47 start-page: 34 year: 2015 ident: CR47 article-title: A computationally efficient algorithm for genomic prediction using a Bayesian model publication-title: Genet Sel Evol doi: 10.1186/s12711-014-0082-4 – volume: 101 start-page: 1418 year: 2006 end-page: 1429 ident: CR57 article-title: The adaptive lasso and its oracle properties publication-title: J Am Stat Assoc doi: 10.1198/016214506000000735 – volume: 4 start-page: 85 year: 2009 end-page: 117 ident: CR39 article-title: A review of Bayesian variable selection methods: what, how and which publication-title: Bayesian Anal doi: 10.1214/09-BA403 – volume: 185 start-page: 349 year: 2010 end-page: 359 ident: CR44 article-title: Genomewide multiple-loci mapping in experimental crosses by iterative adaptive penalized regression publication-title: Genetics doi: 10.1534/genetics.110.114280 – volume: 190 start-page: 231 year: 2012 end-page: 249 ident: CR27 article-title: Estimation of quantitative trait locus effects with epistasis by variational Bayes algorithms publication-title: Genetics doi: 10.1534/genetics.111.134866 – volume: 81 start-page: 559 year: 2007 end-page: 575 ident: CR41 article-title: PLINK: a tool set for whole-genome association and population-based linkage analyses publication-title: Am J Hum Genet doi: 10.1086/519795 – volume: 24 start-page: 1550 year: 2014 end-page: 1557 ident: CR43 article-title: MultiBLUP: improved SNP-based prediction for complex traits publication-title: Genome Res doi: 10.1101/gr.169375.113 – volume: 140 start-page: 329 year: 2016 end-page: 336 ident: CR7 article-title: Estimation of heritability for nine common cancers using data from genome-wide association studies in Chinese population publication-title: Int J Cancer doi: 10.1002/ijc.30447 – volume: 47 start-page: 284 year: 2015 end-page: 290 ident: CR34 article-title: Efficient Bayesian mixed-model analysis increases association power in large cohorts publication-title: Nat Genet doi: 10.1038/ng.3190 – year: 2006 ident: CR3 publication-title: Pattern recognition and machine learning (Information Science and Statistics) – volume: 46 start-page: 167 year: 1992 end-page: 174 ident: CR6 article-title: Explaining the Gibbs sampler publication-title: Am Stat – volume: 38 start-page: 467 year: 2014 end-page: 476 ident: CR9 article-title: Whole genome prediction of bladder cancer risk with the Bayesian LASSO publication-title: Genet Epidemiol doi: 10.1002/gepi.21809 – volume: 67 start-page: 301 year: 2005 end-page: 320 ident: CR58 article-title: Regularization and variable selection via the elastic net publication-title: J R Stat Soc doi: 10.1111/j.1467-9868.2005.00503.x – volume: 10 start-page: 25 year: 2000 end-page: 37 ident: CR20 article-title: Bayesian parameter estimation via variational methods publication-title: Stat Comput doi: 10.1023/A:1008932416310 – volume: 7 start-page: 73 year: 2012 end-page: 107 ident: CR4 article-title: Scalable variational inference for Bayesian variable selection in Regression, and its accuracy in genetic association studies publication-title: Bayesian Anal doi: 10.1214/12-BA703 – volume: 8 start-page: e83745 year: 2013 ident: CR8 article-title: Application of multi-SNP approaches Bayesian LASSO and AUC-RF to detect main effects of inflammatory-gene variants associated with bladder cancer risk publication-title: PLoS One doi: 10.1371/journal.pone.0083745 – volume: 45 start-page: 117 year: 2016 end-page: 122 ident: CR42 article-title: Aldehyde dehydrogenase 1B1 as a modulator of pancreatic adenocarcinoma publication-title: Pancreas doi: 10.1097/MPA.0000000000000542 – volume: 11 start-page: 1 year: 2010 end-page: 13 ident: CR31 article-title: A variational Bayes algorithm for fast and accurate multiple locus genome-wide association analysis publication-title: BMC Bioinform doi: 10.1186/1471-2105-11-58 – volume: 36 start-page: 99 year: 1974 end-page: 102 ident: CR1 article-title: Scale mixtures of normal distributions publication-title: R Stat Soc Series B Stat Methodol – volume: 44 start-page: 455 year: 1995 end-page: 472 ident: CR15 article-title: Adaptive rejection metropolis sampling within Gibbs sampling publication-title: Appl Stat doi: 10.2307/2986138 – volume: 88 start-page: 76 year: 2011 end-page: 82 ident: CR50 article-title: GCTA: a tool for genome-wide complex trait analysis publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2010.11.011 – volume: 44 start-page: 821 year: 2012 end-page: 824 ident: CR55 article-title: Genome-wide efficient mixed-model analysis for association studies publication-title: Nat Genet doi: 10.1038/ng.2310 – volume: 14 start-page: 34 year: 2013 ident: CR18 article-title: A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits publication-title: BMC Bioinform doi: 10.1186/1471-2105-14-34 – volume: 103 start-page: 681 year: 2008 end-page: 686 ident: CR40 article-title: The Bayesian Lasso publication-title: J Am Stat Assoc doi: 10.1198/016214508000000337 – volume: 201 start-page: 865 year: 2015 end-page: 870 ident: CR23 article-title: An efficient genome-wide multilocus epistasis search publication-title: Genetics doi: 10.1534/genetics.115.182444 – volume: 68 start-page: 49 year: 2006 end-page: 67 ident: CR53 article-title: Model selection and estimation in regression with grouped variables publication-title: J R Stat Soc doi: 10.1111/j.1467-9868.2005.00532.x – volume: 124 start-page: 3741 year: 2014 end-page: 3756 ident: CR11 article-title: EGFR phosphorylation of DCBLD2 recruits TRAF6 and stimulates AKT-promoted tumorigenesis publication-title: J Clin Invest doi: 10.1172/JCI73093 – volume: 181 start-page: 1101 year: 2009 end-page: 1113 ident: CR51 article-title: Hierarchical generalized linear models for multiple quantitative trait locus mapping publication-title: Genetics doi: 10.1534/genetics.108.099556 – volume: 343 start-page: 78 year: 2000 end-page: 85 ident: CR29 article-title: Environmental and heritable factors in the causation of cancer—analyses of cohorts of twins from Sweden, Denmark, and Finland publication-title: N Engl J Med doi: 10.1056/NEJM200007133430201 – volume: 28 start-page: 1738 year: 2012 end-page: 1744 ident: CR32 article-title: A novel variational Bayes multiple locus Z-statistic for genome-wide association studies with Bayesian model averaging publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts261 – volume: 192 start-page: 1483 year: 2012 end-page: 1491 ident: CR37 article-title: A decision rule for quantitative trait locus detection under the extended Bayesian LASSO model publication-title: Genetics doi: 10.1534/genetics.111.130278 – volume: 42 start-page: 355 year: 2010 end-page: 360 ident: CR54 article-title: Mixed linear model approach adapted for genome-wide association studies publication-title: Nat Genet doi: 10.1038/ng.546 – volume: 88 start-page: 294 year: 2011 end-page: 305 ident: CR26 article-title: Estimating missing heritability for disease from genome-wide association studies publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2011.02.002 – volume: 3 start-page: 1511 year: 2013 end-page: 1523 ident: CR22 article-title: Fast genomic predictions via Bayesian G-BLUP and multilocus models of threshold traits including censored Gaussian data publication-title: G3 (Bethesda) doi: 10.1534/g3.113.007096 – volume: 68 start-page: 49 year: 2006 ident: 1322_CR53 publication-title: J R Stat Soc doi: 10.1111/j.1467-9868.2005.00532.x – volume: 149 start-page: 935 year: 2009 ident: 1322_CR5 publication-title: J R Stat Soc – volume: 8 start-page: 833 year: 2011 ident: 1322_CR30 publication-title: Nat Methods doi: 10.1038/nmeth.1681 – volume: 4 start-page: 85 year: 2009 ident: 1322_CR39 publication-title: Bayesian Anal doi: 10.1214/09-BA403 – volume: 46 start-page: 167 year: 1992 ident: 1322_CR6 publication-title: Am Stat doi: 10.1080/00031305.1992.10475878 – volume: 163 start-page: 789 year: 2003 ident: 1322_CR48 publication-title: Genetics doi: 10.1093/genetics/163.2.789 – volume: 27 start-page: 516 year: 2011 ident: 1322_CR28 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btq688 – volume: 81 start-page: 559 year: 2007 ident: 1322_CR41 publication-title: Am J Hum Genet doi: 10.1086/519795 – volume: 99 start-page: 817 year: 2016 ident: 1322_CR12 publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2016.07.022 – volume: 5 start-page: 1780 year: 2011 ident: 1322_CR17 publication-title: Ann Appl Stat doi: 10.1214/11-AOAS455 – volume: 47 start-page: 34 year: 2015 ident: 1322_CR47 publication-title: Genet Sel Evol doi: 10.1186/s12711-014-0082-4 – volume: 38 start-page: 21 year: 2014 ident: 1322_CR33 publication-title: Genet Epidemiol doi: 10.1002/gepi.21772 – volume: 43 start-page: 792 year: 2011 ident: 1322_CR19 publication-title: Nat Genet doi: 10.1038/ng.875 – volume: 8 start-page: e83745 year: 2013 ident: 1322_CR8 publication-title: PLoS One doi: 10.1371/journal.pone.0083745 – volume: 45 start-page: 117 year: 2016 ident: 1322_CR42 publication-title: Pancreas doi: 10.1097/MPA.0000000000000542 – volume: 103 start-page: 681 year: 2008 ident: 1322_CR40 publication-title: J Am Stat Assoc doi: 10.1198/016214508000000337 – volume: 6 start-page: 222 year: 2008 ident: 1322_CR24 publication-title: Mol Cancer Res doi: 10.1158/1541-7786.MCR-07-0142 – volume: 461 start-page: 747 year: 2009 ident: 1322_CR35 publication-title: Nature doi: 10.1038/nature08494 – volume: 3 start-page: 1511 year: 2013 ident: 1322_CR22 publication-title: G3 (Bethesda) doi: 10.1534/g3.113.007096 – volume: 131 start-page: E643 year: 2012 ident: 1322_CR13 publication-title: Int J Cancer doi: 10.1002/ijc.27426 – volume: 21 start-page: 2822 year: 2002 ident: 1322_CR25 publication-title: Oncogene doi: 10.1038/sj.onc.1205405 – volume: 44 start-page: 821 year: 2012 ident: 1322_CR55 publication-title: Nat Genet doi: 10.1038/ng.2310 – volume: 11 start-page: 446 year: 2010 ident: 1322_CR10 publication-title: Nat Rev Genet doi: 10.1038/nrg2809 – volume: 24 start-page: 1550 year: 2014 ident: 1322_CR43 publication-title: Genome Res doi: 10.1101/gr.169375.113 – volume: 26 start-page: 4025 year: 2007 ident: 1322_CR38 publication-title: Oncogene doi: 10.1038/sj.onc.1210183 – volume: 124 start-page: 3741 year: 2014 ident: 1322_CR11 publication-title: J Clin Invest doi: 10.1172/JCI73093 – volume: 181 start-page: 1101 year: 2009 ident: 1322_CR51 publication-title: Genetics doi: 10.1534/genetics.108.099556 – volume: 11 start-page: e1004969 year: 2015 ident: 1322_CR36 publication-title: PLoS Genet doi: 10.1371/journal.pgen.1004969 – volume: 42 start-page: 355 year: 2010 ident: 1322_CR54 publication-title: Nat Genet doi: 10.1038/ng.546 – volume: 9 start-page: 5087 year: 2015 ident: 1322_CR52 publication-title: Drug Des Devel Ther doi: 10.2147/DDDT.S87197 – volume-title: Variational algorithms for approximate Bayesian inference year: 2003 ident: 1322_CR2 – volume-title: Pattern recognition and machine learning (Information Science and Statistics) year: 2006 ident: 1322_CR3 – volume: 185 start-page: 349 year: 2010 ident: 1322_CR44 publication-title: Genetics doi: 10.1534/genetics.110.114280 – volume: 28 start-page: 1738 year: 2012 ident: 1322_CR32 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts261 – volume: 47 start-page: 284 year: 2015 ident: 1322_CR34 publication-title: Nat Genet doi: 10.1038/ng.3190 – volume: 192 start-page: 1483 year: 2012 ident: 1322_CR37 publication-title: Genetics doi: 10.1534/genetics.111.130278 – volume: 9 start-page: e1003264 year: 2013 ident: 1322_CR56 publication-title: PLoS Genet doi: 10.1371/journal.pgen.1003264 – volume: 36 start-page: 99 year: 1974 ident: 1322_CR1 publication-title: R Stat Soc Series B Stat Methodol doi: 10.1111/j.2517-6161.1974.tb00989.x – volume: 201 start-page: 865 year: 2015 ident: 1322_CR23 publication-title: Genetics doi: 10.1534/genetics.115.182444 – volume: 38 start-page: 467 year: 2014 ident: 1322_CR9 publication-title: Genet Epidemiol doi: 10.1002/gepi.21809 – volume: 111 start-page: E5272 year: 2014 ident: 1322_CR16 publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.1419064111 – volume: 7 start-page: 73 year: 2012 ident: 1322_CR4 publication-title: Bayesian Anal doi: 10.1214/12-BA703 – volume: 105 start-page: 483 year: 2010 ident: 1322_CR49 publication-title: Heredity (Edinb) doi: 10.1038/hdy.2009.180 – volume: 88 start-page: 881 year: 1993 ident: 1322_CR14 publication-title: J Am Stat Assoc doi: 10.1080/01621459.1993.10476353 – volume: 190 start-page: 231 year: 2012 ident: 1322_CR27 publication-title: Genetics doi: 10.1534/genetics.111.134866 – volume: 14 start-page: 34 year: 2013 ident: 1322_CR18 publication-title: BMC Bioinform doi: 10.1186/1471-2105-14-34 – volume: 10 start-page: 25 year: 2000 ident: 1322_CR20 publication-title: Stat Comput doi: 10.1023/A:1008932416310 – volume: 67 start-page: 301 year: 2005 ident: 1322_CR58 publication-title: J R Stat Soc doi: 10.1111/j.1467-9868.2005.00503.x – volume: 88 start-page: 76 year: 2011 ident: 1322_CR50 publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2010.11.011 – volume: 44 start-page: 455 year: 1995 ident: 1322_CR15 publication-title: Appl Stat doi: 10.2307/2986138 – volume: 11 start-page: 1 year: 2010 ident: 1322_CR31 publication-title: BMC Bioinform doi: 10.1186/1471-2105-11-58 – volume: 73 start-page: 273 year: 2011 ident: 1322_CR46 publication-title: J R Stat Soc Ser B Stat Methodol doi: 10.1111/j.1467-9868.2011.00771.x – volume: 68 start-page: 9686 year: 2008 ident: 1322_CR21 publication-title: Cancer Res doi: 10.1158/0008-5472.CAN-08-1083 – volume: 343 start-page: 78 year: 2000 ident: 1322_CR29 publication-title: N Engl J Med doi: 10.1056/NEJM200007133430201 – volume: 88 start-page: 294 year: 2011 ident: 1322_CR26 publication-title: Am J Hum Genet doi: 10.1016/j.ajhg.2011.02.002 – volume: 101 start-page: 1418 year: 2006 ident: 1322_CR57 publication-title: J Am Stat Assoc doi: 10.1198/016214506000000735 – volume: 140 start-page: 329 year: 2016 ident: 1322_CR7 publication-title: Int J Cancer doi: 10.1002/ijc.30447 – volume: 58 start-page: 267 year: 1996 ident: 1322_CR45 publication-title: J R Stat Soc doi: 10.1111/j.2517-6161.1996.tb02080.x – reference: 21156729 - Bioinformatics. 2011 Feb 15;27(4):516-23 – reference: 19047146 - Cancer Res. 2008 Dec 1;68(23):9686-92 – reference: 24963154 - Genome Res. 2014 Sep;24(9):1550-7 – reference: 23363272 - BMC Bioinformatics. 2013 Jan 31;14:34 – reference: 10891514 - N Engl J Med. 2000 Jul 13;343(2):78-85 – reference: 23408905 - PLoS Genet. 2013;9(2):e1003264 – reference: 26405029 - Genetics. 2015 Nov;201(3):865-70 – reference: 25849665 - PLoS Genet. 2015 Apr 07;11(4):e1004969 – reference: 22706312 - Nat Genet. 2012 Jun 17;44(7):821-4 – reference: 21376301 - Am J Hum Genet. 2011 Mar 11;88(3):294-305 – reference: 27640306 - Am J Hum Genet. 2016 Oct 6;99(4):817-830 – reference: 24391818 - PLoS One. 2013 Dec 31;8(12):e83745 – reference: 22042575 - Genetics. 2012 Jan;190(1):231-49 – reference: 26566217 - Pancreas. 2016 Jan;45(1):117-22 – reference: 25061874 - J Clin Invest. 2014 Sep;124(9):3741-56 – reference: 25926276 - Genet Sel Evol. 2015 Apr 30;47:34 – reference: 21892150 - Nat Methods. 2011 Sep 04;8(10):833-5 – reference: 22982577 - Genetics. 2012 Dec;192(4):1483-91 – reference: 27668986 - Int J Cancer. 2017 Jan 15;140(2):329-336 – reference: 23821618 - G3 (Bethesda). 2013 Sep 04;3(9):1511-23 – reference: 18314483 - Mol Cancer Res. 2008 Feb;6(2):222-30 – reference: 12618414 - Genetics. 2003 Feb;163(2):789-801 – reference: 20105321 - BMC Bioinformatics. 2010 Jan 27;11:58 – reference: 17213806 - Oncogene. 2007 Jun 7;26(27):4025-31 – reference: 24482836 - Genet Epidemiol. 2014 Jan;38(1):21-30 – reference: 25642633 - Nat Genet. 2015 Mar;47(3):284-90 – reference: 25422463 - Proc Natl Acad Sci U S A. 2014 Dec 9;111(49):E5272-81 – reference: 26366059 - Drug Des Devel Ther. 2015 Sep 03;9:5087-97 – reference: 20157003 - Genetics. 2010 May;185(1):349-59 – reference: 19812666 - Nature. 2009 Oct 8;461(7265):747-53 – reference: 20208535 - Nat Genet. 2010 Apr;42(4):355-60 – reference: 22563072 - Bioinformatics. 2012 Jul 1;28(13):1738-44 – reference: 20479774 - Nat Rev Genet. 2010 Jun;11(6):446-50 – reference: 24796258 - Genet Epidemiol. 2014 Jul;38(5):467-76 – reference: 11973641 - Oncogene. 2002 Apr 25;21(18):2822-8 – reference: 20051978 - Heredity (Edinb). 2010 Nov;105(5):483-94 – reference: 17701901 - Am J Hum Genet. 2007 Sep;81(3):559-75 – reference: 21725308 - Nat Genet. 2011 Jul 03;43(8):792-6 – reference: 21167468 - Am J Hum Genet. 2011 Jan 7;88(1):76-82 – reference: 19139143 - Genetics. 2009 Mar;181(3):1101-13 – reference: 22223368 - Int J Cancer. 2012 Sep 1;131(5):E643-8 |
| SSID | ssj0017627 |
| Score | 2.1930544 |
| Snippet | Genome-wide association studies (GWAS) have identified a large amount of single-nucleotide polymorphisms (SNPs) associated with complex traits. A recently... |
| SourceID | proquest pubmed crossref springer |
| SourceType | Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 923 |
| SubjectTerms | Algorithms Animal Genetics and Genomics Bayes Theorem Bayesian analysis Biochemistry Biomedical and Life Sciences Computational Biology - methods Computer Simulation Data processing Genome-wide association studies genome-wide association study Genome-Wide Association Study - methods Genomes Heritability Human Genetics Humans Life Sciences Lung cancer lung neoplasms Markov chain Markov Chains Mathematical models Methods Paper Microbial Genetics and Genomics Models, Genetic Monte Carlo Method Plant Genetics and Genomics Polymorphism Polymorphism, Single Nucleotide - genetics Quantitative Trait, Heritable Single-nucleotide polymorphism statistical models |
| SummonAdditionalLinks | – databaseName: Biological Science Database dbid: M7P link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1JS8UwEB5cwYv7UjcieFKCXdKX9CQqiicRUfBWkibRB9qn9j3Ff-8kXVREL56bliEzyXzJTL8PYFcnGAWJ0JSzTFMWxRFVmVA0DU0hMhNbzgovNsEvLsTtbXbZXLhVTVtluyf6jVoPCndHfoDnCuHYwiN--PRMnWqUq642EhrjMOlYEmLfunfZVRFwoXtxFczSlGHqbquaYU0imrg2Lk79eYx9z0s_wOaPQqnPP2dz_7V8HmYb5EmO6lBZgDFTLsJ0rUX5vgRXR8TKakjkwx2-PLx_JAhnybF8N-43S-IbDylmvlFFvHoO6ZfEEbw-GvrW14bITz-Tqm5OXIabs9Prk3PaCC7QAnGbk6XngqkEl7WNuLK9lBmutTDKxknCJZ7cWCp1qIy0TPHUWKXd3LI0tZpb0UtWYKIclGYNCNNR0TOZClPZY7iHiUKpJDSGC0SEmQ0DCNvpzouGjdyJYjzkHY-y91COHsqdh3IWwF73ylNNxfHX4M3WGXmzKqv80xMB7HSPcT25IokszWDkxuBHHEc9-31MXCNdBNcBrNbx0VkUI_5BiCoC2G8D5osBv5m7_re5GzATu1D1jYebMDF8GZktmCpeh_3qZdsH_QdtCgUC priority: 102 providerName: ProQuest |
| Title | A fast algorithm for Bayesian multi-locus model in genome-wide association studies |
| URI | https://link.springer.com/article/10.1007/s00438-017-1322-4 https://www.ncbi.nlm.nih.gov/pubmed/28534238 https://www.proquest.com/docview/1918298917 https://www.proquest.com/docview/1901770194 https://www.proquest.com/docview/2000540099 |
| Volume | 292 |
| WOSCitedRecordID | wos000405521400017&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: PRVPQU databaseName: Biological Science Database customDbUrl: eissn: 1617-4623 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0017627 issn: 1617-4615 databaseCode: M7P dateStart: 19970301 isFulltext: true titleUrlDefault: http://search.proquest.com/biologicalscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: Health & Medical Collection customDbUrl: eissn: 1617-4623 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0017627 issn: 1617-4615 databaseCode: 7X7 dateStart: 19970301 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1617-4623 dateEnd: 20171231 omitProxy: false ssIdentifier: ssj0017627 issn: 1617-4615 databaseCode: BENPR dateStart: 19970301 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVAVX databaseName: Springer Journals customDbUrl: eissn: 1617-4623 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017627 issn: 1617-4615 databaseCode: RSV dateStart: 20010101 isFulltext: true titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22 providerName: Springer Nature |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LT9wwEB7xqtRLy6OUtLAyEieQpTyctXMEBOpptVpotbfIjm260pJFm10Q_56x86AVD6m95JJJNBrPeD5rxvMBHOkEvSARmnKWacqiOKIqE4qmoSlEZmLLWeHJJvhgIMbjbNjc467abve2JOl36u6ymy9aUber-hMUW4V1zHbC8TWMrn51pQOMbs-ogqmZMszXbSnztV_8nYxeIMwX1VGfdC4__5e6m_CpwZjktHaKLVgx5TZ8qFknH3dgdEqsrBZETm9m88ni9y1B4ErO5KNxFyqJbzGkmOOWFfE8OWRSEjfK9dbQh4k2RD6vKKnqNsQv8PPy4vr8B22oFWiBCM0R0HPBVIIBbCOubD9lhmstjLJxknCJZzSWSh0qIy1TPDVWaWdQlqZWcyv6yS6slbPS7AFhOir6JlNhKvsMdytRKJWExnCB2C-zYQBha-O8aOaOO_qLad5NTPamytFUuTNVzgI47j65q4duvCe83y5c3sRfleMpVLjZ8hEP4LB7jZHjyiGyNLOlk8GfuGn07G2ZuMa0CKMD-Fo7RadRjEgHwagI4KT1gD8UeEvdb_8k_R0-xs6FfMfhPqwt5ktzABvF_WJSzXuwysfcP0UP1s8uBsNRzzWvDns-JJ4AT47-dw |
| linkProvider | Springer Nature |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB6VAqIX3tBAASPBBWSRh7N2DgiVR9WqZYVQkfaW2vEYVmqzpdml2j_V39ixs0lBVXvrgXOcaJL5PP4mHs8H8MpmhIJMWS5FYblI0oSbQhmex1ipAlMnRRXEJuRwqEaj4tsSnHRnYXxZZRcTQ6C2k8r_I39HeYXy3cIT-eHwN_eqUX53tZPQaGGxjfNjStma91ufyb-v03Tjy-6nTb5QFeAVkROvvS6VMBlh1yXSuEEuUFqr0Lg0y6Sm9ETk2sYGtRNG5uiM9TmAyHNnpVODjJ57Da5THJc-2ZOjPsFLKLAEMRcazgVRhW4XNW6blma-bEzykP-Jf9fBc-T23MZsWO827vxvX-ou3F4wa7beToV7sIT1fbjZam3OH8D3deZ0M2V6_ycZO_11wIius496jv4YKQuFlZxW9lnDgjoQG9fMN7A9QH48tsj0GY5Z0xZfPoQfV_JCj2C5ntS4CkzYpBpgYeJcDwTFaFUZk8WIUhHjLVwcQdy5t6wW3da96Md-2feJDogoCRGlR0QpInjT33LYthq5bPBa5_xyEXWa8szzEbzsL1O88JtAusbJzI-hh_ge_OLiMWnL5Cl5iOBxi8feopT4HVFwFcHbDqB_GXCRuU8uN_cF3Nrc_bpT7mwNt5_CSuqnSSiyXIPl6dEMn8GN6s903Bw9DxOOwd5V4_YUcxNiFQ |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LT9wwEB7RpUW9lL6AtLS4UntpZZGHs3YOFYLCCkS1WqFW4pbasV1WgiyQ3aL9a_11HTsPWiG4ceg5tjVJPo-_yUzmA3ivE0RBIjTlLNOURXFEVSYUTUNTiMzElrPCi03w4VAcH2ejBfjd_gvjyipbn-gdtZ4U7hv5JsYVwnULj_imbcoiRruDrfML6hSkXKa1ldOoIXJo5lcYvlWfD3bxXX-I48Hety_7tFEYoAUSFafDzgVTCeLYRlzZfsoM11oYZeMk4RJDFZZKHSojLVM8NVZpFw-wNLWaW9FPcN0HsMiRZLAeLO7sDUdHXQ4D3YyXdsEJlCFxaHOqYd3CNHFFZJz6aJD9eyreoLo30rT-9Bss_8_P7Sk8aTg32a43yTNYMOVzeFSrcM5fwNE2sbKaEnn6E42dnpwRJPJkR86N-8GU-JJLimf-rCJeN4iMS-Ja254ZejXWhshrhJOqLst8Cd_v5YZWoFdOSrMGhOmo6JtMhansM_TeolAqCY3hArlwZsMAwvZV50XTh93JgZzmXQdpj44c0ZE7dOQsgI_dlPO6Ccldg9dbIOSNP6ryaxQE8K67jJ7EpYdkaSYzNwYXcd352e1j4prjY1gRwGqNzc6iGJkfknMRwKcWrH8ZcJu5r-42dwOWEK7514Ph4Wt4HLsd46sv16E3vZyZN_Cw-DUdV5dvm91H4Md9A_cPpFlsNQ |
| 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+fast+algorithm+for+Bayesian+multi-locus+model+in+genome-wide+association+studies&rft.jtitle=Molecular+genetics+and+genomics+%3A+MGG&rft.au=Duan%2C+Weiwei&rft.au=Zhao%2C+Yang&rft.au=Wei%2C+Yongyue&rft.au=Yang%2C+Sheng&rft.date=2017-08-01&rft.eissn=1617-4623&rft.volume=292&rft.issue=4&rft.spage=923&rft_id=info:doi/10.1007%2Fs00438-017-1322-4&rft_id=info%3Apmid%2F28534238&rft.externalDocID=28534238 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1617-4615&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1617-4615&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1617-4615&client=summon |