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- Publisher Website: 10.1038/s42256-020-0167-4
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Article: Exploring the limit of using a deep neural network on pileup data for germline variant calling
Title | Exploring the limit of using a deep neural network on pileup data for germline variant calling |
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Authors | |
Issue Date | 2020 |
Publisher | Nature Research (part of Springer Nature). The Journal's web site is located at https://www.nature.com/natmachintell/ |
Citation | Nature Machine Intelligence, 2020, v. 2 n. 4, p. 220-227 How to Cite? |
Abstract | Single-molecule sequencing technologies have emerged in recent years and revolutionized structural variant calling, complex genome assembly and epigenetic mark detection. However, the lack of a highly accurate small variant caller has limited these technologies from being more widely used. Here, we present Clair, the successor to Clairvoyante, a program for fast and accurate germline small variant calling, using single-molecule sequencing data. For Oxford Nanopore Technology data, Clair achieves better precision, recall and speed than several competing programs, including Clairvoyante, Longshot and Medaka. Through studying the missed variants and benchmarking intentionally overfitted models, we found that Clair may be approaching the limit of possible accuracy for germline small variant calling using pileup data and deep neural networks. Clair requires only a conventional central processing unit (CPU) for variant calling and is an open-source project available at https://github.com/HKU-BAL/Clair. |
Persistent Identifier | http://hdl.handle.net/10722/282021 |
ISSN | 2023 Impact Factor: 18.8 2023 SCImago Journal Rankings: 5.940 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Luo, R | - |
dc.contributor.author | Wong, C-L | - |
dc.contributor.author | Wong, Y-S | - |
dc.contributor.author | Tang, C-I | - |
dc.contributor.author | Liu, C-M | - |
dc.contributor.author | Leung, C-M | - |
dc.contributor.author | Lam, T-W | - |
dc.date.accessioned | 2020-04-19T03:34:16Z | - |
dc.date.available | 2020-04-19T03:34:16Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Nature Machine Intelligence, 2020, v. 2 n. 4, p. 220-227 | - |
dc.identifier.issn | 2522-5839 | - |
dc.identifier.uri | http://hdl.handle.net/10722/282021 | - |
dc.description.abstract | Single-molecule sequencing technologies have emerged in recent years and revolutionized structural variant calling, complex genome assembly and epigenetic mark detection. However, the lack of a highly accurate small variant caller has limited these technologies from being more widely used. Here, we present Clair, the successor to Clairvoyante, a program for fast and accurate germline small variant calling, using single-molecule sequencing data. For Oxford Nanopore Technology data, Clair achieves better precision, recall and speed than several competing programs, including Clairvoyante, Longshot and Medaka. Through studying the missed variants and benchmarking intentionally overfitted models, we found that Clair may be approaching the limit of possible accuracy for germline small variant calling using pileup data and deep neural networks. Clair requires only a conventional central processing unit (CPU) for variant calling and is an open-source project available at https://github.com/HKU-BAL/Clair. | - |
dc.language | eng | - |
dc.publisher | Nature Research (part of Springer Nature). The Journal's web site is located at https://www.nature.com/natmachintell/ | - |
dc.relation.ispartof | Nature Machine Intelligence | - |
dc.rights | This is a post-peer-review, pre-copyedit version of an article published in Nature Machine Intelligence. The final authenticated version is available online at: https://doi.org/10.1038/s42256-020-0167-4 | - |
dc.title | Exploring the limit of using a deep neural network on pileup data for germline variant calling | - |
dc.type | Article | - |
dc.identifier.email | Luo, R: rbluo@cs.hku.hk | - |
dc.identifier.email | Wong, C-L: clacm@hku.hk | - |
dc.identifier.email | Wong, Y-S: ncls935@hku.hk | - |
dc.identifier.email | Liu, C-M: imcx@hku.hk | - |
dc.identifier.email | Leung, C-M: cmleung3@hku.hk | - |
dc.identifier.email | Lam, T-W: twlam@cs.hku.hk | - |
dc.identifier.authority | Luo, R=rp02360 | - |
dc.identifier.authority | Leung, C-M=rp00144 | - |
dc.identifier.authority | Lam, T-W=rp00135 | - |
dc.description.nature | preprint | - |
dc.identifier.doi | 10.1038/s42256-020-0167-4 | - |
dc.identifier.hkuros | 309705 | - |
dc.identifier.volume | 2 | - |
dc.identifier.issue | 4 | - |
dc.identifier.spage | 220 | - |
dc.identifier.epage | 227 | - |
dc.identifier.eissn | 2522-5839 | - |
dc.identifier.isi | WOS:000571260800006 | - |
dc.publisher.place | United Kingdom | - |
dc.identifier.issnl | 2522-5839 | - |