Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome
Abstract Motivation Short-read whole-genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences and sequencing bias reduces the performance of variant calling using short-read alignment, but the loss in rec...
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| Veröffentlicht in: | Bioinformatics 2022-03, Vol.38 (7), p.1781-1787 |
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| creator | Marin, Maximillian Vargas, Roger Harris, Michael Jeffrey, Brendan Epperson, L Elaine Durbin, David Strong, Michael Salfinger, Max Iqbal, Zamin Akhundova, Irada Vashakidze, Sergo Crudu, Valeriu Rosenthal, Alex Farhat, Maha Reda |
| description | Abstract
Motivation
Short-read whole-genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences and sequencing bias reduces the performance of variant calling using short-read alignment, but the loss in recall and specificity has not been adequately characterized. To benchmark short-read variant calling, we used 36 diverse clinical Mycobacterium tuberculosis (Mtb) isolates dually sequenced with Illumina short-reads and PacBio long-reads. We systematically studied the short-read variant calling accuracy and the influence of sequence uniqueness, reference bias and GC content.
Results
Reference-based Illumina variant calling demonstrated a maximum recall of 89.0% and minimum precision of 98.5% across parameters evaluated. The approach that maximized variant recall while still maintaining high precision ( |
| doi_str_mv | 10.1093/bioinformatics/btac023 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_TOX</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8963317</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><oup_id>10.1093/bioinformatics/btac023</oup_id><sourcerecordid>2619545860</sourcerecordid><originalsourceid>FETCH-LOGICAL-c461t-df38a4a24b397a22a7acce0887861673a6701cc50fa46178f5eff981703fe0173</originalsourceid><addsrcrecordid>eNqNkU9v1DAQxS0Eon_gK1Q5ckk7jh3buSBBVShSEZf2ijXxjncNSbzYSaV--7q7S0VvnMbS_N4bPz3Gzjicc-jERR9imHxMI87B5Yt-RgeNeMWOuVRQN9B2r8tbKF1LA-KIneT8C6DlUsq37Ei00IDuxDH7-Zkmtxkx_Q7Tupo3VNG4DSk4HCp0bknoHqroq7yJaa4T4arK9GcpoiceXYo572Tfz6t56Sm5ZYg55GpNUxzpHXvjccj0_jBP2d2Xq9vL6_rmx9dvl59uaicVn-uVFwYlNrIXncamQV1uExijjeJKC1QauHMteCy8Nr4l7zvDNQhPwLU4ZR_3vtulH2nlaJoTDnabQon2YCMG-3IzhY1dx3trOiXEzuDDwSDFEi_PdgzZ0TDgRHHJtlG8a2VrFBRU7dFd-ET--QwH-1SOfVmOPZRThGf_fvJZ9reNAvA9EJft_5o-AuO3pOY</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2619545860</pqid></control><display><type>article</type><title>Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome</title><source>Oxford Journals Open Access Collection</source><creator>Marin, Maximillian ; Vargas, Roger ; Harris, Michael ; Jeffrey, Brendan ; Epperson, L Elaine ; Durbin, David ; Strong, Michael ; Salfinger, Max ; Iqbal, Zamin ; Akhundova, Irada ; Vashakidze, Sergo ; Crudu, Valeriu ; Rosenthal, Alex ; Farhat, Maha Reda</creator><creatorcontrib>Marin, Maximillian ; Vargas, Roger ; Harris, Michael ; Jeffrey, Brendan ; Epperson, L Elaine ; Durbin, David ; Strong, Michael ; Salfinger, Max ; Iqbal, Zamin ; Akhundova, Irada ; Vashakidze, Sergo ; Crudu, Valeriu ; Rosenthal, Alex ; Farhat, Maha Reda</creatorcontrib><description>Abstract
Motivation
Short-read whole-genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences and sequencing bias reduces the performance of variant calling using short-read alignment, but the loss in recall and specificity has not been adequately characterized. To benchmark short-read variant calling, we used 36 diverse clinical Mycobacterium tuberculosis (Mtb) isolates dually sequenced with Illumina short-reads and PacBio long-reads. We systematically studied the short-read variant calling accuracy and the influence of sequence uniqueness, reference bias and GC content.
Results
Reference-based Illumina variant calling demonstrated a maximum recall of 89.0% and minimum precision of 98.5% across parameters evaluated. The approach that maximized variant recall while still maintaining high precision (<99%) was tuning the mapping quality filtering threshold, i.e. confidence of the read mapping (recall = 85.8%, precision = 99.1%, MQ ≥ 40). Additional masking of repetitive sequence content is an alternative conservative approach to variant calling that increases precision at cost to recall (recall = 70.2%, precision = 99.6%, MQ ≥ 40). Of the genomic positions typically excluded for Mtb, 68% are accurately called using Illumina WGS including 52/168 PE/PPE genes (34.5%). From these results, we present a refined list of low confidence regions across the Mtb genome, which we found to frequently overlap with regions with structural variation, low sequence uniqueness and low sequencing coverage. Our benchmarking results have broad implications for the use of WGS in the study of Mtb biology, inference of transmission in public health surveillance systems and more generally for WGS applications in other organisms.
Availability and implementation
All relevant code is available at https://github.com/farhat-lab/mtb-illumina-wgs-evaluation.
Supplementary information
Supplementary data are available at Bioinformatics online.</description><identifier>ISSN: 1367-4803</identifier><identifier>EISSN: 1460-2059</identifier><identifier>EISSN: 1367-4811</identifier><identifier>DOI: 10.1093/bioinformatics/btac023</identifier><identifier>PMID: 35020793</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Benchmarking ; High-Throughput Nucleotide Sequencing - methods ; Humans ; Mycobacterium tuberculosis - genetics ; Original Papers ; Sequence Analysis, DNA - methods ; Software ; Tuberculosis</subject><ispartof>Bioinformatics, 2022-03, Vol.38 (7), p.1781-1787</ispartof><rights>The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com 2022</rights><rights>The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c461t-df38a4a24b397a22a7acce0887861673a6701cc50fa46178f5eff981703fe0173</citedby><cites>FETCH-LOGICAL-c461t-df38a4a24b397a22a7acce0887861673a6701cc50fa46178f5eff981703fe0173</cites><orcidid>0000-0001-5059-8002 ; 0000-0002-9108-3328</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963317/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8963317/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,723,776,780,881,1598,27901,27902,53766,53768</link.rule.ids><linktorsrc>$$Uhttps://dx.doi.org/10.1093/bioinformatics/btac023$$EView_record_in_Oxford_University_Press$$FView_record_in_$$GOxford_University_Press</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35020793$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Marin, Maximillian</creatorcontrib><creatorcontrib>Vargas, Roger</creatorcontrib><creatorcontrib>Harris, Michael</creatorcontrib><creatorcontrib>Jeffrey, Brendan</creatorcontrib><creatorcontrib>Epperson, L Elaine</creatorcontrib><creatorcontrib>Durbin, David</creatorcontrib><creatorcontrib>Strong, Michael</creatorcontrib><creatorcontrib>Salfinger, Max</creatorcontrib><creatorcontrib>Iqbal, Zamin</creatorcontrib><creatorcontrib>Akhundova, Irada</creatorcontrib><creatorcontrib>Vashakidze, Sergo</creatorcontrib><creatorcontrib>Crudu, Valeriu</creatorcontrib><creatorcontrib>Rosenthal, Alex</creatorcontrib><creatorcontrib>Farhat, Maha Reda</creatorcontrib><title>Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome</title><title>Bioinformatics</title><addtitle>Bioinformatics</addtitle><description>Abstract
Motivation
Short-read whole-genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences and sequencing bias reduces the performance of variant calling using short-read alignment, but the loss in recall and specificity has not been adequately characterized. To benchmark short-read variant calling, we used 36 diverse clinical Mycobacterium tuberculosis (Mtb) isolates dually sequenced with Illumina short-reads and PacBio long-reads. We systematically studied the short-read variant calling accuracy and the influence of sequence uniqueness, reference bias and GC content.
Results
Reference-based Illumina variant calling demonstrated a maximum recall of 89.0% and minimum precision of 98.5% across parameters evaluated. The approach that maximized variant recall while still maintaining high precision (<99%) was tuning the mapping quality filtering threshold, i.e. confidence of the read mapping (recall = 85.8%, precision = 99.1%, MQ ≥ 40). Additional masking of repetitive sequence content is an alternative conservative approach to variant calling that increases precision at cost to recall (recall = 70.2%, precision = 99.6%, MQ ≥ 40). Of the genomic positions typically excluded for Mtb, 68% are accurately called using Illumina WGS including 52/168 PE/PPE genes (34.5%). From these results, we present a refined list of low confidence regions across the Mtb genome, which we found to frequently overlap with regions with structural variation, low sequence uniqueness and low sequencing coverage. Our benchmarking results have broad implications for the use of WGS in the study of Mtb biology, inference of transmission in public health surveillance systems and more generally for WGS applications in other organisms.
Availability and implementation
All relevant code is available at https://github.com/farhat-lab/mtb-illumina-wgs-evaluation.
Supplementary information
Supplementary data are available at Bioinformatics online.</description><subject>Benchmarking</subject><subject>High-Throughput Nucleotide Sequencing - methods</subject><subject>Humans</subject><subject>Mycobacterium tuberculosis - genetics</subject><subject>Original Papers</subject><subject>Sequence Analysis, DNA - methods</subject><subject>Software</subject><subject>Tuberculosis</subject><issn>1367-4803</issn><issn>1460-2059</issn><issn>1367-4811</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkU9v1DAQxS0Eon_gK1Q5ckk7jh3buSBBVShSEZf2ijXxjncNSbzYSaV--7q7S0VvnMbS_N4bPz3Gzjicc-jERR9imHxMI87B5Yt-RgeNeMWOuVRQN9B2r8tbKF1LA-KIneT8C6DlUsq37Ei00IDuxDH7-Zkmtxkx_Q7Tupo3VNG4DSk4HCp0bknoHqroq7yJaa4T4arK9GcpoiceXYo572Tfz6t56Sm5ZYg55GpNUxzpHXvjccj0_jBP2d2Xq9vL6_rmx9dvl59uaicVn-uVFwYlNrIXncamQV1uExijjeJKC1QauHMteCy8Nr4l7zvDNQhPwLU4ZR_3vtulH2nlaJoTDnabQon2YCMG-3IzhY1dx3trOiXEzuDDwSDFEi_PdgzZ0TDgRHHJtlG8a2VrFBRU7dFd-ET--QwH-1SOfVmOPZRThGf_fvJZ9reNAvA9EJft_5o-AuO3pOY</recordid><startdate>20220328</startdate><enddate>20220328</enddate><creator>Marin, Maximillian</creator><creator>Vargas, Roger</creator><creator>Harris, Michael</creator><creator>Jeffrey, Brendan</creator><creator>Epperson, L Elaine</creator><creator>Durbin, David</creator><creator>Strong, Michael</creator><creator>Salfinger, Max</creator><creator>Iqbal, Zamin</creator><creator>Akhundova, Irada</creator><creator>Vashakidze, Sergo</creator><creator>Crudu, Valeriu</creator><creator>Rosenthal, Alex</creator><creator>Farhat, Maha Reda</creator><general>Oxford University Press</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-5059-8002</orcidid><orcidid>https://orcid.org/0000-0002-9108-3328</orcidid></search><sort><creationdate>20220328</creationdate><title>Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome</title><author>Marin, Maximillian ; Vargas, Roger ; Harris, Michael ; Jeffrey, Brendan ; Epperson, L Elaine ; Durbin, David ; Strong, Michael ; Salfinger, Max ; Iqbal, Zamin ; Akhundova, Irada ; Vashakidze, Sergo ; Crudu, Valeriu ; Rosenthal, Alex ; Farhat, Maha Reda</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c461t-df38a4a24b397a22a7acce0887861673a6701cc50fa46178f5eff981703fe0173</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Benchmarking</topic><topic>High-Throughput Nucleotide Sequencing - methods</topic><topic>Humans</topic><topic>Mycobacterium tuberculosis - genetics</topic><topic>Original Papers</topic><topic>Sequence Analysis, DNA - methods</topic><topic>Software</topic><topic>Tuberculosis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Marin, Maximillian</creatorcontrib><creatorcontrib>Vargas, Roger</creatorcontrib><creatorcontrib>Harris, Michael</creatorcontrib><creatorcontrib>Jeffrey, Brendan</creatorcontrib><creatorcontrib>Epperson, L Elaine</creatorcontrib><creatorcontrib>Durbin, David</creatorcontrib><creatorcontrib>Strong, Michael</creatorcontrib><creatorcontrib>Salfinger, Max</creatorcontrib><creatorcontrib>Iqbal, Zamin</creatorcontrib><creatorcontrib>Akhundova, Irada</creatorcontrib><creatorcontrib>Vashakidze, Sergo</creatorcontrib><creatorcontrib>Crudu, Valeriu</creatorcontrib><creatorcontrib>Rosenthal, Alex</creatorcontrib><creatorcontrib>Farhat, Maha Reda</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Bioinformatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Marin, Maximillian</au><au>Vargas, Roger</au><au>Harris, Michael</au><au>Jeffrey, Brendan</au><au>Epperson, L Elaine</au><au>Durbin, David</au><au>Strong, Michael</au><au>Salfinger, Max</au><au>Iqbal, Zamin</au><au>Akhundova, Irada</au><au>Vashakidze, Sergo</au><au>Crudu, Valeriu</au><au>Rosenthal, Alex</au><au>Farhat, Maha Reda</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome</atitle><jtitle>Bioinformatics</jtitle><addtitle>Bioinformatics</addtitle><date>2022-03-28</date><risdate>2022</risdate><volume>38</volume><issue>7</issue><spage>1781</spage><epage>1787</epage><pages>1781-1787</pages><issn>1367-4803</issn><eissn>1460-2059</eissn><eissn>1367-4811</eissn><abstract>Abstract
Motivation
Short-read whole-genome sequencing (WGS) is a vital tool for clinical applications and basic research. Genetic divergence from the reference genome, repetitive sequences and sequencing bias reduces the performance of variant calling using short-read alignment, but the loss in recall and specificity has not been adequately characterized. To benchmark short-read variant calling, we used 36 diverse clinical Mycobacterium tuberculosis (Mtb) isolates dually sequenced with Illumina short-reads and PacBio long-reads. We systematically studied the short-read variant calling accuracy and the influence of sequence uniqueness, reference bias and GC content.
Results
Reference-based Illumina variant calling demonstrated a maximum recall of 89.0% and minimum precision of 98.5% across parameters evaluated. The approach that maximized variant recall while still maintaining high precision (<99%) was tuning the mapping quality filtering threshold, i.e. confidence of the read mapping (recall = 85.8%, precision = 99.1%, MQ ≥ 40). Additional masking of repetitive sequence content is an alternative conservative approach to variant calling that increases precision at cost to recall (recall = 70.2%, precision = 99.6%, MQ ≥ 40). Of the genomic positions typically excluded for Mtb, 68% are accurately called using Illumina WGS including 52/168 PE/PPE genes (34.5%). From these results, we present a refined list of low confidence regions across the Mtb genome, which we found to frequently overlap with regions with structural variation, low sequence uniqueness and low sequencing coverage. Our benchmarking results have broad implications for the use of WGS in the study of Mtb biology, inference of transmission in public health surveillance systems and more generally for WGS applications in other organisms.
Availability and implementation
All relevant code is available at https://github.com/farhat-lab/mtb-illumina-wgs-evaluation.
Supplementary information
Supplementary data are available at Bioinformatics online.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>35020793</pmid><doi>10.1093/bioinformatics/btac023</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0001-5059-8002</orcidid><orcidid>https://orcid.org/0000-0002-9108-3328</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Benchmarking High-Throughput Nucleotide Sequencing - methods Humans Mycobacterium tuberculosis - genetics Original Papers Sequence Analysis, DNA - methods Software Tuberculosis |
| title | Benchmarking the empirical accuracy of short-read sequencing across the M. tuberculosis genome |
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