SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data

Background There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations. Results We propose a novel computati...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Genome Biology Ročník 22; číslo 1; s. 37
Hlavní autoři:	Davis, Eric M., Sun, Yu, Liu, Yanling, Kolekar, Pandurang, Shao, Ying, Szlachta, Karol, Mulder, Heather L., Ren, Dongren, Rice, Stephen V., Wang, Zhaoming, Nakitandwe, Joy, Gout, Alexander M., Shaner, Bridget, Hall, Salina, Robison, Leslie L., Pounds, Stanley, Klco, Jeffery M., Easton, John, Ma, Xiaotu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London BioMed Central 25.01.2021 Springer Nature B.V BMC
Témata:	Accuracy Algorithms Animal Genetics and Genomics Bioinformatics Biomedical and Life Sciences Calibration Computer applications data collection Datasets Deoxyribonucleic acid DNA DNA libraries DNA sequencing Error suppression Evolutionary Biology Gene Library genome High-Throughput Nucleotide Sequencing - methods Human Genetics Humans Life Sciences Microbial Genetics and Genomics Models, Genetic Mutation Next-generation sequencing Nucleotide sequence Plant Genetics and Genomics Quality control SARS-CoV-2 Sequence Analysis, DNA - methods Sequencer/instrument error Error suppression Sequencer/instrument error DNA sequencing
ISSN:	1474-760X, 1474-7596, 1474-760X
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Abstract	Background There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations. Results We propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket. Conclusions Our study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets.
AbstractList	Background There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations. Results We propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket. Conclusions Our study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets. Abstract Background There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations. Results We propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket. Conclusions Our study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets. There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations.BACKGROUNDThere is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations.We propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket.RESULTSWe propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket.Our study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets.CONCLUSIONSOur study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets. BACKGROUND: There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations. RESULTS: We propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket. CONCLUSIONS: Our study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets. There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation sequencing applications aimed at discovering the genetic makeup of heterogeneous cellular populations. We propose a novel computational method, SequencErr, to address this challenge by measuring the base correspondence between overlapping regions in forward and reverse reads. An analysis of 3777 public datasets from 75 research institutions in 18 countries revealed the sequencer error rate to be ~ 10 per million (pm) and 1.4% of sequencers and 2.7% of flow cells have error rates > 100 pm. At the flow cell level, error rates are elevated in the bottom surfaces and > 90% of HiSeq and NovaSeq flow cells have at least one outlier error-prone tile. By sequencing a common DNA library on different sequencers, we demonstrate that sequencers with high error rates have reduced overall sequencing accuracy, and removal of outlier error-prone tiles improves sequencing accuracy. We demonstrate that SequencErr can reveal novel insights relative to the popular quality control method FastQC and achieve a 10-fold lower error rate than popular error correction methods including Lighter and Musket. Our study reveals novel insights into the nature of DNA sequencing errors incurred on DNA sequencers. Our method can be used to assess, calibrate, and monitor sequencer accuracy, and to computationally suppress sequencer errors in existing datasets.
ArticleNumber	37
Author	Ren, Dongren Shaner, Bridget Robison, Leslie L. Shao, Ying Liu, Yanling Pounds, Stanley Gout, Alexander M. Ma, Xiaotu Rice, Stephen V. Nakitandwe, Joy Easton, John Sun, Yu Davis, Eric M. Szlachta, Karol Hall, Salina Klco, Jeffery M. Wang, Zhaoming Mulder, Heather L. Kolekar, Pandurang
Author_xml	– sequence: 1 givenname: Eric M. surname: Davis fullname: Davis, Eric M. organization: Department of Computational Biology, St. Jude Children’s Research Hospital – sequence: 2 givenname: Yu surname: Sun fullname: Sun, Yu organization: Department of Computational Biology, St. Jude Children’s Research Hospital, Department of Computer Science, University of Memphis – sequence: 3 givenname: Yanling surname: Liu fullname: Liu, Yanling organization: Department of Computational Biology, St. Jude Children’s Research Hospital – sequence: 4 givenname: Pandurang surname: Kolekar fullname: Kolekar, Pandurang organization: Department of Computational Biology, St. Jude Children’s Research Hospital – sequence: 5 givenname: Ying surname: Shao fullname: Shao, Ying organization: Department of Computational Biology, St. Jude Children’s Research Hospital – sequence: 6 givenname: Karol surname: Szlachta fullname: Szlachta, Karol organization: Department of Computational Biology, St. Jude Children’s Research Hospital – sequence: 7 givenname: Heather L. surname: Mulder fullname: Mulder, Heather L. organization: Department of Computational Biology, St. Jude Children’s Research Hospital – sequence: 8 givenname: Dongren surname: Ren fullname: Ren, Dongren – sequence: 9 givenname: Stephen V. surname: Rice fullname: Rice, Stephen V. organization: Department of Computational Biology, St. Jude Children’s Research Hospital – sequence: 10 givenname: Zhaoming surname: Wang fullname: Wang, Zhaoming organization: Department of Epidemiology & Cancer Control, St. Jude Children’s Research Hospital – sequence: 11 givenname: Joy surname: Nakitandwe fullname: Nakitandwe, Joy organization: Department of Pathology, St. Jude Children’s Research Hospital – sequence: 12 givenname: Alexander M. surname: Gout fullname: Gout, Alexander M. organization: Department of Computational Biology, St. Jude Children’s Research Hospital – sequence: 13 givenname: Bridget surname: Shaner fullname: Shaner, Bridget organization: Department of Computational Biology, St. Jude Children’s Research Hospital – sequence: 14 givenname: Salina surname: Hall fullname: Hall, Salina organization: Discovery Life Sciences – sequence: 15 givenname: Leslie L. surname: Robison fullname: Robison, Leslie L. organization: Department of Epidemiology & Cancer Control, St. Jude Children’s Research Hospital – sequence: 16 givenname: Stanley surname: Pounds fullname: Pounds, Stanley organization: Department of Biostatistics, St. Jude Children’s Research Hospital – sequence: 17 givenname: Jeffery M. surname: Klco fullname: Klco, Jeffery M. organization: Department of Pathology, St. Jude Children’s Research Hospital – sequence: 18 givenname: John surname: Easton fullname: Easton, John organization: Department of Computational Biology, St. Jude Children’s Research Hospital – sequence: 19 givenname: Xiaotu orcidid: 0000-0002-6233-2145 surname: Ma fullname: Ma, Xiaotu email: Xiaotu.Ma@stjude.org organization: Department of Computational Biology, St. Jude Children’s Research Hospital
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/33487172$$D View this record in MEDLINE/PubMed
BookMark	eNqFkktv1DAUhS1URB_wB1igSGzYBPxKbLNAQlWBSpVYABKsLNu5GTzK2MFOEPx7nEkH2i7KIs7rO0fXPucUHYUYAKGnBL8kRLavMmG4UTWmuFy04TV9gE4IF7wWLf56dOP5GJ3mvMWYKE7bR-iYMS4FEfQEffsEP2YI7iKl19UOTJ6TD5vKhK7K8zgmyHl5zysFqYKUYsqVD1WAX1O9gQDJTD6GA7PgnZnMY_SwN0OGJ9f3M_Tl3cXn8w_11cf3l-dvr2onsJxqsIxKaQnpLGlbaXhPWtErBg4wEcCgJb1wQEGwxnXMMKmM4AaUY5YXITtDl6tvF81Wj8nvTPqto_F6_yGmjTZp8m4AbbntrMMgjOUcjJHMWsU4Z6zjjDZ98Xqzeo2z3UHnIEzJDLdMb_8J_rvexJ9aSKpKFsXgxbVBiuU08qR3PjsYBhMgzlnThpToOJHN_1EusShBtbigz--g2zinUE61UIpQ1ZS1UM9uDv936kPYBZAr4FLMOUGvnZ_22ZW9-EETrJde6bVXuvRK73ulFym9Iz243ytiqyiPS6kg_Rv7HtUfpuThIQ
CitedBy_id	crossref_primary_10_1097_IM9_0000000000000134 crossref_primary_10_1016_j_compbiomed_2025_111079 crossref_primary_10_3390_foods11233777 crossref_primary_10_1038_s41588_023_01376_0 crossref_primary_10_3390_ijms25179270 crossref_primary_10_1186_s12864_024_10137_0 crossref_primary_10_48130_vegres_0025_0021 crossref_primary_10_1016_j_crmeth_2021_100106 crossref_primary_10_1186_s13059_023_02922_z crossref_primary_10_1038_s41467_023_37438_4 crossref_primary_10_1038_s41598_024_60524_6 crossref_primary_10_1016_j_ijbiomac_2024_136424 crossref_primary_10_3390_pharmaceutics17030295 crossref_primary_10_1016_j_apsb_2025_03_005 crossref_primary_10_1016_j_freeradbiomed_2025_06_027 crossref_primary_10_1016_j_ijbiomac_2025_146740 crossref_primary_10_3390_ijms251910818 crossref_primary_10_3390_microorganisms10101882 crossref_primary_10_3389_fgene_2023_1144221 crossref_primary_10_1016_j_cbd_2024_101379 crossref_primary_10_1002_qub2_99 crossref_primary_10_3390_genes15060787 crossref_primary_10_1186_s40364_023_00449_w crossref_primary_10_1158_1078_0432_CCR_24_1063 crossref_primary_10_2147_IDR_S491858 crossref_primary_10_3389_fgene_2024_1365285 crossref_primary_10_3390_ijms25010657 crossref_primary_10_48130_mpb_0025_0001 crossref_primary_10_1007_s00122_025_04999_5 crossref_primary_10_1016_j_tig_2021_08_007 crossref_primary_10_1038_s41598_025_15221_3 crossref_primary_10_1186_s12870_024_05291_2 crossref_primary_10_3390_cancers13071591
Cites_doi	10.1101/gr.8.3.186 10.1186/s13059-014-0509-9 10.1186/s12864-015-2194-9 10.1186/s12864-015-1263-4 10.1126/science.1186802 10.1038/srep24607 10.1093/bioinformatics/bts690 10.1038/nrg.2017.117 10.1038/s41591-019-0652-7 10.1038/nmeth.1492 10.5281/zenodo.4312180 10.1186/s13059-020-01988-3 10.1111/j.1755-0998.2011.03024.x 10.1186/s12859-017-1469-3 10.1146/annurev-anchem-062012-092628 10.1038/nature08658 10.1371/journal.pone.0169774 10.1093/genetics/156.1.297 10.1093/nar/gks918 10.1158/1541-7786.MCR-18-0620 10.1182/blood.2019002220 10.1093/bioinformatics/btp324 10.1038/nrg.2016.49 10.1186/s13059-019-1659-6 10.1038/s41587-019-0171-6 10.5281/zenodo.4313906 10.1186/s12885-019-6313-x 10.1200/JCO.2018.77.8589 10.1126/science.aar3247 10.7554/eLife.03300
ContentType	Journal Article
Copyright	The Author(s) 2021 2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml	– notice: The Author(s) 2021 – notice: 2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID	C6C AAYXX CITATION CGR CUY CVF ECM EIF NPM 3V. 7X7 7XB 88E 8FE 8FH 8FI 8FJ 8FK ABUWG AFKRA AZQEC BBNVY BENPR BHPHI CCPQU COVID DWQXO FYUFA GHDGH GNUQQ HCIFZ K9. LK8 M0S M1P M7P PHGZM PHGZT PIMPY PJZUB PKEHL PPXIY PQEST PQGLB PQQKQ PQUKI PRINS 7X8 7S9 L.6 5PM DOA
DOI	10.1186/s13059-020-02254-2
DatabaseName	Springer Nature OA Free Journals CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed ProQuest Central (Corporate) Health & Medical Collection ProQuest Central (purchase pre-March 2016) Medical Database (Alumni Edition) ProQuest SciTech Collection ProQuest Natural Science Collection 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 (subscription) ProQuest Central Natural Science Collection ProQuest One Coronavirus Research Database ProQuest Central Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Health & Medical Complete (Alumni) ProQuest Biological Science Collection Health & Medical Collection (Alumni Edition) PML(ProQuest Medical Library) Biological Sciences ProQuest Central Premium ProQuest One Academic (New) Publicly Available Content Database (subscription) ProQuest Health & Medical Research Collection ProQuest One Academic Middle East (New) One Health & Nursing ProQuest One Academic Eastern Edition (DO NOT USE) One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China MEDLINE - Academic AGRICOLA AGRICOLA - Academic PubMed Central (Full Participant titles) DOAJ Directory of Open Access Journals
DatabaseTitle	CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Publicly Available Content Database ProQuest Central Student ProQuest One Academic Middle East (New) ProQuest Central Essentials 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 Central China ProQuest Central ProQuest One Applied & Life Sciences ProQuest Health & Medical Research Collection Health Research Premium Collection Health and Medicine Complete (Alumni Edition) Natural Science Collection ProQuest Central Korea Health & Medical Research Collection Biological Science Collection ProQuest Central (New) ProQuest Medical Library (Alumni) ProQuest Biological Science Collection ProQuest One Academic Eastern Edition Coronavirus Research Database ProQuest Hospital Collection Health Research Premium Collection (Alumni) Biological Science Database ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) ProQuest Health & Medical Complete ProQuest Medical Library ProQuest One Academic UKI Edition ProQuest One Academic ProQuest One Academic (New) ProQuest Central (Alumni) MEDLINE - Academic AGRICOLA AGRICOLA - Academic
DatabaseTitleList	MEDLINE - Academic AGRICOLA MEDLINE Publicly Available Content Database
Database_xml	– sequence: 1 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 2 dbid: NPM name: PubMed url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 3 dbid: PIMPY name: Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database
DeliveryMethod	fulltext_linktorsrc
Discipline	Biology
EISSN	1474-760X
EndPage	37
ExternalDocumentID	oai_doaj_org_article_b4bdbc0e7ab44eaa83bb934433d4325f PMC7829059 33487172 10_1186_s13059_020_02254_2
Genre	Research Support, Non-U.S. Gov't Journal Article Research Support, N.I.H., Extramural
GrantInformation_xml	– fundername: National Institutes of Health grantid: P30CA021765 funderid: http://dx.doi.org/10.13039/100000002 – fundername: Fund for Innovation in Cancer Informatics – fundername: American Lebanese Syrian Associated Charities funderid: http://dx.doi.org/10.13039/100012524 – fundername: NIH HHS grantid: P30CA021765 – fundername: ; – fundername: ; grantid: P30CA021765
GroupedDBID	--- 0R~ 29H 4.4 53G 5GY 5VS 7X7 88E 8FE 8FH 8FI 8FJ AAFWJ AAHBH AAJSJ AASML ABUWG ACGFO ACGFS ACJQM ACPRK ADBBV ADUKV AEGXH AFKRA AFPKN AHBYD AIAGR ALMA_UNASSIGNED_HOLDINGS AMKLP AMTXH AOIAM AOIJS BAPOH BAWUL BBNVY BCNDV BENPR BFQNJ BHPHI BMC BPHCQ BVXVI C6C CCPQU EBD EBLON EBS EMOBN FYUFA GROUPED_DOAJ GX1 HCIFZ HMCUK IAO IGS IHR ISR ITC KPI LK8 M1P M7P PHGZM PHGZT PIMPY PJZUB PPXIY PQGLB PQQKQ PROAC PSQYO PUEGO ROL RPM RSV SJN SOJ SV3 UKHRP AAYXX AFFHD CITATION 3V. ACRMQ ADINQ ALIPV C24 CGR CUY CVF ECM EIF NPM 7XB 8FK AZQEC COVID DWQXO GNUQQ K9. PKEHL PQEST PQUKI PRINS 7X8 7S9 L.6 5PM
ID	FETCH-LOGICAL-c708t-eb3288b11db1668a4f167f93ece017e3e61f7ce2e735cd3a389a74ae9c3b488b3
IEDL.DBID	DOA
ISICitedReferencesCount	36
ISICitedReferencesURI	http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000610871000001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN	1474-760X 1474-7596
IngestDate	Fri Oct 03 12:51:42 EDT 2025 Tue Nov 04 02:05:43 EST 2025 Thu Sep 04 17:20:17 EDT 2025 Sun Nov 09 12:43:48 EST 2025 Tue Oct 14 12:41:10 EDT 2025 Thu Jan 02 22:55:37 EST 2025 Sat Nov 29 04:55:56 EST 2025 Tue Nov 18 22:04:53 EST 2025 Sat Sep 06 07:17:34 EDT 2025
IsDoiOpenAccess	true
IsOpenAccess	true
IsPeerReviewed	true
IsScholarly	true
Issue	1
Keywords	Error suppression Sequencer/instrument error DNA sequencing
Language	English
License	Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
LinkModel	DirectLink
MergedId	FETCHMERGED-LOGICAL-c708t-eb3288b11db1668a4f167f93ece017e3e61f7ce2e735cd3a389a74ae9c3b488b3
Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23
ORCID	0000-0002-6233-2145
OpenAccessLink	https://doaj.org/article/b4bdbc0e7ab44eaa83bb934433d4325f
PMID	33487172
PQID	2491295491
PQPubID	2040232
PageCount	1
ParticipantIDs	doaj_primary_oai_doaj_org_article_b4bdbc0e7ab44eaa83bb934433d4325f pubmedcentral_primary_oai_pubmedcentral_nih_gov_7829059 proquest_miscellaneous_2511184185 proquest_miscellaneous_2480733460 proquest_journals_2491295491 pubmed_primary_33487172 crossref_citationtrail_10_1186_s13059_020_02254_2 crossref_primary_10_1186_s13059_020_02254_2 springer_journals_10_1186_s13059_020_02254_2
PublicationCentury	2000
PublicationDate	2021-01-25
PublicationDateYYYYMMDD	2021-01-25
PublicationDate_xml	– month: 01 year: 2021 text: 2021-01-25 day: 25
PublicationDecade	2020
PublicationPlace	London
PublicationPlace_xml	– name: London – name: England
PublicationTitle	Genome Biology
PublicationTitleAbbrev	Genome Biol
PublicationTitleAlternate	Genome Biol
PublicationYear	2021
Publisher	BioMed Central Springer Nature B.V BMC
Publisher_xml	– name: BioMed Central – name: Springer Nature B.V – name: BMC
References	X Ma (2254_CR8) 2019; 20 L Song (2254_CR20) 2014; 15 H Li (2254_CR28) 2009; 25 B Li (2254_CR9) 2020; 135 MW Nachman (2254_CR12) 2000; 156 2254_CR27 L Pan (2254_CR18) 2015; 16 P Razavi (2254_CR4) 2019; 25 DW Craig (2254_CR26) 2016; 6 K Mitchell (2254_CR22) 2020; 21 S Goodwin (2254_CR6) 2016; 17 Y Liu (2254_CR21) 2013; 29 R D'Amore (2254_CR14) 2016; 17 S Chen (2254_CR17) 2017; 18 JC Roach (2254_CR13) 2010; 328 V Potapov (2254_CR11) 2017; 12 2254_CR7 DM Fowler (2254_CR16) 2010; 7 S., A (2254_CR19) 2010 JJ Salk (2254_CR2) 2018; 19 ED Pleasance (2254_CR25) 2010; 463 2254_CR15 A Wilm (2254_CR29) 2012; 40 B Ewing (2254_CR23) 1998; 8 2254_CR31 2254_CR30 JD Cohen (2254_CR3) 2018; 359 2254_CR10 DJ Craig (2254_CR24) 2019; 19 P Rugbjerg (2254_CR1) 2019; 37 TC Glenn (2254_CR5) 2011; 11
References_xml	– volume: 8 start-page: 186 year: 1998 ident: 2254_CR23 publication-title: Genome Res doi: 10.1101/gr.8.3.186 – volume: 15 start-page: 509 year: 2014 ident: 2254_CR20 publication-title: Genome Biol doi: 10.1186/s13059-014-0509-9 – volume: 17 start-page: 55 year: 2016 ident: 2254_CR14 publication-title: BMC Genomics doi: 10.1186/s12864-015-2194-9 – volume: 16 start-page: 83 year: 2015 ident: 2254_CR18 publication-title: BMC Genomics doi: 10.1186/s12864-015-1263-4 – volume: 328 start-page: 636 year: 2010 ident: 2254_CR13 publication-title: Science doi: 10.1126/science.1186802 – volume: 6 start-page: 24607 year: 2016 ident: 2254_CR26 publication-title: Sci Rep doi: 10.1038/srep24607 – volume: 29 start-page: 308 year: 2013 ident: 2254_CR21 publication-title: Bioinformatics doi: 10.1093/bioinformatics/bts690 – volume: 19 start-page: 269 year: 2018 ident: 2254_CR2 publication-title: Nat Rev Genet doi: 10.1038/nrg.2017.117 – volume: 25 start-page: 1928 year: 2019 ident: 2254_CR4 publication-title: Nat Med doi: 10.1038/s41591-019-0652-7 – volume: 7 start-page: 741 year: 2010 ident: 2254_CR16 publication-title: Nat Methods doi: 10.1038/nmeth.1492 – ident: 2254_CR30 doi: 10.5281/zenodo.4312180 – volume: 21 start-page: 71 year: 2020 ident: 2254_CR22 publication-title: Genome Biol doi: 10.1186/s13059-020-01988-3 – volume: 11 start-page: 759 year: 2011 ident: 2254_CR5 publication-title: Mol Ecol Resour doi: 10.1111/j.1755-0998.2011.03024.x – volume: 18 start-page: 80 year: 2017 ident: 2254_CR17 publication-title: BMC Bioinformatics doi: 10.1186/s12859-017-1469-3 – ident: 2254_CR7 doi: 10.1146/annurev-anchem-062012-092628 – volume: 463 start-page: 191 year: 2010 ident: 2254_CR25 publication-title: Nature doi: 10.1038/nature08658 – volume: 12 year: 2017 ident: 2254_CR11 publication-title: PLoS One doi: 10.1371/journal.pone.0169774 – volume: 156 start-page: 297 year: 2000 ident: 2254_CR12 publication-title: Genetics doi: 10.1093/genetics/156.1.297 – volume: 40 start-page: 11189 year: 2012 ident: 2254_CR29 publication-title: Nucleic Acids Res doi: 10.1093/nar/gks918 – ident: 2254_CR10 doi: 10.1158/1541-7786.MCR-18-0620 – volume: 135 start-page: 41 year: 2020 ident: 2254_CR9 publication-title: Blood doi: 10.1182/blood.2019002220 – volume: 25 start-page: 1754 year: 2009 ident: 2254_CR28 publication-title: Bioinformatics doi: 10.1093/bioinformatics/btp324 – volume: 17 start-page: 333 year: 2016 ident: 2254_CR6 publication-title: Nat Rev Genet doi: 10.1038/nrg.2016.49 – volume: 20 start-page: 50 year: 2019 ident: 2254_CR8 publication-title: Genome Biol doi: 10.1186/s13059-019-1659-6 – volume: 37 start-page: 869 year: 2019 ident: 2254_CR1 publication-title: Nat Biotechnol doi: 10.1038/s41587-019-0171-6 – ident: 2254_CR31 doi: 10.5281/zenodo.4313906 – volume: 19 start-page: 1081 year: 2019 ident: 2254_CR24 publication-title: BMC Cancer doi: 10.1186/s12885-019-6313-x – ident: 2254_CR27 doi: 10.1200/JCO.2018.77.8589 – volume-title: FastQC: a quality control tool for high throughput sequence data year: 2010 ident: 2254_CR19 – volume: 359 start-page: 926 year: 2018 ident: 2254_CR3 publication-title: Science doi: 10.1126/science.aar3247 – ident: 2254_CR15 doi: 10.7554/eLife.03300
SSID	ssj0019426 ssj0017866
Score	2.511164
Snippet	Background There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for... There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for next-generation... Background There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for... BACKGROUND: There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for... Abstract Background There is currently no method to precisely measure the errors that occur in the sequencing instrument/sequencer, which is critical for...
SourceID	doaj pubmedcentral proquest pubmed crossref springer
SourceType	Open Website Open Access Repository Aggregation Database Index Database Enrichment Source Publisher
StartPage	37
SubjectTerms	Accuracy Algorithms Animal Genetics and Genomics Bioinformatics Biomedical and Life Sciences Calibration Computer applications data collection Datasets Deoxyribonucleic acid DNA DNA libraries DNA sequencing Error suppression Evolutionary Biology Gene Library genome High-Throughput Nucleotide Sequencing - methods Human Genetics Humans Life Sciences Microbial Genetics and Genomics Models, Genetic Mutation Next-generation sequencing Nucleotide sequence Plant Genetics and Genomics Quality control SARS-CoV-2 Sequence Analysis, DNA - methods Sequencer/instrument error
SummonAdditionalLinks	– databaseName: Biological Sciences dbid: M7P link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lj9QwDI5gAYkL70dhQUXiBtU2zbNcEKBdcUCrlXhoOUVJ6y4jQWdoZ5D499jpYzU85sKxjVslsePY8Rebsac1oF5sQGWGB5lJAI9rDtBVEaXQwAtvY_2UT-_M8bE9PS1PxgO3foRVTjoxKup6WdEZ-QG6CTzGpPjL1feMqkZRdHUsoXGRXaIsCUWE7p3MUQRjyVYZH0pZDFeNCICoSj3doLH6oEdFrsqMPCnc0pTMiq1dKibz_5sF-ieQ8rdoatykjq7_7_BusGujeZq-GuTpJrsA7S12ZShY-fM2-_x-QF4fdt2L9Fs8XsR-pL6t036zGjC1-Dzhs7sUum7Z9emiTVtysc9ikmuShYmGyAmleod9PDr88OZtNhZnyCqT23WGTnhhbeC8Dlxr62XDtWlKARXgxIMAzRtTQQFGqKoWHg0jb6SHshIBlUYQd9leu2zhPkutMkF7NPWDquOJVIO_DTqAtKB9XiaMT8xw1Zi5nApofHXRg7HaDQx0yEAXGeiKhD2bv1kNeTt2Ur8mHs-UlHM7vlh2Z25cwi7IUIcqB-ODlOC9FSGUQkohaikK1SRsf2KtGxVB7875mrAnczMuYYrL-BaWG6KxVDpT6nwHDRrG6IyjdZWwe4PQzb2ly9ToleMozJY4bg1nu6VdfImpxA3F0RXO8PNJcM-7_u_perB7pA_Z1YKQPznPCrXP9tbdBh6xy9WP9aLvHscl-gu-4kCz priority: 102 providerName: ProQuest – databaseName: SpringerLINK Contemporary 1997-Present dbid: RSV link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnR3LbtQw0EItSFwoz5LSoiBxg4g4fqY3ilpxQBWiUJWTZSeTdqWSrZxdpP59x86jWloqwTHxxHLG8_SMZwh5WwPKxQZEpqjjGQewyHOArgormQRaWB37pxx_UYeH-uSk_DpcCuvGbPcxJBkldWRrLT90KG1FmQV3B_WO4BkK3nVUdzo0bPh2dDzFDkpUOuP1mFu_W1FBsVL_beblzSzJP0KlUQMdbPzf2h-TR4PFmX7sSeQJuQftU_Kg70F5-Yz8POqTqfe9301_xRNDnDm1bZ12y4s-TRafx5Rrn4L3c9-lszZtg9d8GutWh-0dYQJ4SDx9Tn4c7H__9Dkb-i1klcr1IkO_utDaUVo7KqW2vKFSNSWDCpBvgYGkjaqgAMVEVTOLto5V3EJZMYdywLEXZK2dt_CSpFooJy1a707U8ZCpwWmddMA1SJuXCaHjFphqKEYeemKcm-iUaGl6lBlEmYkoM0VC3k3fXPSlOO6E3gs7O0GGMtrxxdyfmoErjeOudlUOyjrOwVrNnCsZ54zVnBWiScj2SBdm4O3OoMNKY3SUJuTNNIxcGUIttoX5MsDo0A2Ty_wOGLR10b9Ggykhmz2pTasN96PR0ca_UCtEuPI7qyPt7CxWB1chNC4Qw-9HUrxe-t_RtfVv4K_IwyIk9-Q0K8Q2WVv4JeyQ-9XvxazzryM_XgF83DHt priority: 102 providerName: Springer Nature
Title	SequencErr: measuring and suppressing sequencer errors in next-generation sequencing data
URI	https://link.springer.com/article/10.1186/s13059-020-02254-2 https://www.ncbi.nlm.nih.gov/pubmed/33487172 https://www.proquest.com/docview/2491295491 https://www.proquest.com/docview/2480733460 https://www.proquest.com/docview/2511184185 https://pubmed.ncbi.nlm.nih.gov/PMC7829059 https://doaj.org/article/b4bdbc0e7ab44eaa83bb934433d4325f
Volume	22
WOSCitedRecordID	wos000610871000001&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: PRVADU databaseName: BioMed Central customDbUrl: eissn: 1474-760X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0017866 issn: 1474-760X databaseCode: RBZ dateStart: 20000101 isFulltext: true titleUrlDefault: https://www.biomedcentral.com/search/ providerName: BioMedCentral – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 1474-760X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0019426 issn: 1474-760X databaseCode: DOA dateStart: 20000101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVPQU databaseName: Biological Sciences customDbUrl: eissn: 1474-760X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0019426 issn: 1474-760X databaseCode: M7P dateStart: 20150101 isFulltext: true titleUrlDefault: http://search.proquest.com/biologicalscijournals providerName: ProQuest – providerCode: PRVPQU databaseName: Health & Medical Collection customDbUrl: eissn: 1474-760X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0019426 issn: 1474-760X databaseCode: 7X7 dateStart: 20150101 isFulltext: true titleUrlDefault: https://search.proquest.com/healthcomplete providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1474-760X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0019426 issn: 1474-760X databaseCode: BENPR dateStart: 20150101 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 1474-760X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0019426 issn: 1474-760X databaseCode: PIMPY dateStart: 20150101 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVAVX databaseName: Springer Journals New Starts & Take-Overs Collection customDbUrl: eissn: 1474-760X dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0019426 issn: 1474-760X databaseCode: RSV dateStart: 20000201 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/eLvHCXMwrV3di9QwEA96Kvgifp7Vc6ngm5ZrmjQfvrmyh4Iu5U6PPV9C0k51QbtHuyv43ztJ29X143zxpZB2WtLJTDK_zGSGkCcV4LxYQ55I6njCASzqHCBUYZoJoJlVoX7K6Rs5n6vFQhc_lfryMWF9euCecYeOu8qVKUjrOAdrFXNOM84ZqzjL8trPvqnUI5ga_AcaF57xiIwShx3O1LlOPFTCNSvnSbazDIVs_X8yMX-PlPzFXRpWoaOb5MZgPsYv-m7fIpeguU2u9QUlv90hZyd9ZPSsbZ_HX8L2H34mtk0Vd5vzPuYV22P8dBtD267aLl42ceMh8MeQhNqP1UjjyX0U6V3y_mj27uWrZCiekJQyVesEQXKmlKO0clQIZXlNhaw1gxJQCYGBoLUsIQPJ8rJiFg0XK7kFXTKHSu3YPbLXrBq4T2KVSycsmuIur8KOUY2fdcIBVyBsqiNCR16acsgs7gtcfDYBYShhev4b5L8J_DdZRJ5u3znv82pcSD31Q7Sl9Dmxww2UFDNIivmXpETkYBxgMyhqZxB90uDqpBF5vH2MKub9JraB1cbTKF_akov0Aho0XBEso_UTkf1eZra99YedETXjX8gdadr5nd0nzfJTSPUtvZ87Rw4_G-XuR9f_zq4H_4NdD8n1zMfvpDTJ8gOyt2438IhcLb-ul107IZflQoarmpAr09m8OJ4EFZz46NkC7xWv3xZn2DqefvDXk9Pv4Ak3NA
linkProvider	Directory of Open Access Journals
linkToHtml	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1bb9MwFD4aHQheuF8CA4IETxCtjh3bQUKIy6ZV66pJjGl7MnZyMipBWpIWtD_Fb8R2kk7l0rc98JjmNIqdz-fi8_kcgKc5Wr1YYBIJYljEELVdc2hDFZpSjiTW0vdPORyK0UgeHaX7a_CzOwvjaJWdTvSKOp9kbo9804YJxOekyOvpt8h1jXLZ1a6FRgOLXTz9YUO2-tXgvf2-z-J4e-vg3U7UdhWIMtGXs8hGj7GUhpDcEM6lZgXhokgpZmjRiRQ5KUSGMQqaZDnV1qJrwTSmGTUW7Yba516AdebA3oP1_cHe_vEibyGk847ai5TFzeEmR3lMUt6d2ZF8s7amI0kjF7tZI5qwKF6yi759wN983j-pm7_lb71Z3L72v03odbjaOuDhm2bF3IA1LG_CpaYl5-ktOP7QcMu3qupl-NVvoNpxh7rMw3o-bVjD9rpjoFchVtWkqsNxGZZuE-HEl_F2aO9knLjj4d6Gj-cyrjvQKycl3oNQJsJwbYMZk-R-z62wjzXcIJPIdT8NgHQfX2VtbXbXIuSL8jGa5KoBjLKAUR4wKg7g-eI_06YyyUrptw5TC0lXVdz_MKlOVKuklGEmN1kfhTaModaSGpNSxijNGY2TIoCNDkqqVXW1OsNRAE8Wt62ScpknXeJk7mSkaw7KeH-FjHX9iXS1lAK424B88bbuuLiwrnYAYgn-S8NZvlOOP_ti6cIxBRI7wy-6hXL26v-ervurR_oYLu8c7A3VcDDafQBXYsdz6pMoTjagN6vm-BAuZt9n47p61CqIED6d9xL6Bd1voCE
linkToPdf	http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3db9QwDI_Q-BAvjK-xsgFF4g2qNU2apHsbsBOI6TRpMI2nKGndcRLLndo7JP57nPQDDsYkxGMbp20cO_GvdmxCXlSA62INeSKp5QkHMKhzgFCFFUwAzYwK9VNOj-R0qs7OiuNfTvGHaPfBJdmdafBZmtxyb1HVnYorsdfiypsXiYc-uAflPMFF-Dr3gfQer5-cjn6EAjeg4ajMpf3WtqOQtf8yU_PPiMnf3KZhN5ps_v847pI7vSUaH3Sic49cA3ef3OxqU35_QD6fdEHWh02zH1-EP4n4lti4Km5Xiy58Fq-HUOwmhqaZN208c7HzaPo85LP20z7QeHIfkPqQfJocfnzzLunrMCSlTNUyQbydKWUprSwVQhleUyHrgkEJqM_AQNBalpCBZHlZMYM2kJHcQFEyi-uDZVtkw80dbJNY5dIKg1a9zavw86nGx1phgSsQJi0iQofp0GWfpNzXyviqA1hRQncs08gyHVims4i8HPssuhQdV1K_9rM8Uvr02uHGvDnXvbZqy21lyxSksZyDMYpZWzDOGas4y_I6IruDjOhe51uNQJYGrymNyPOxGbXVu2CMg_nK0yhfJZOL9AoatIERd6MhFZFHndiNX-vPTSMAx1HINYFcG856i5t9CVnDpXeZ58jhV4NY_vz0v7Pr8b-RPyO3jt9O9NH76Ycdcjvz8T8pTbJ8l2wsmxU8ITfKb8tZ2zwNavoDxLQ9tQ
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=SequencErr%3A+measuring+and+suppressing+sequencer+errors+in+next-generation+sequencing+data&rft.jtitle=Genome+biology&rft.au=Davis%2C+Eric+M&rft.au=Sun%2C+Yu&rft.au=Liu%2C+Yanling&rft.au=Kolekar%2C+Pandurang&rft.date=2021-01-25&rft.issn=1474-760X&rft.eissn=1474-760X&rft.volume=22&rft.issue=1&rft.spage=37&rft_id=info:doi/10.1186%2Fs13059-020-02254-2&rft.externalDBID=NO_FULL_TEXT
thumbnail_l	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1474-760X&client=summon
thumbnail_m	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1474-760X&client=summon
thumbnail_s	http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1474-760X&client=summon