File Download
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1093/nargab/lqaa071
- Scopus: eid_2-s2.0-85113271334
- PMID: 33575619
- WOS: WOS:000645609500013
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: A random forest-based framework for genotyping and accuracy assessment of copy number variations
Title | A random forest-based framework for genotyping and accuracy assessment of copy number variations |
---|---|
Authors | |
Issue Date | 2020 |
Publisher | Oxford University Press: Open Access Journals. The Journal's web site is located at https://academic.oup.com/nargab |
Citation | NAR Genomics and Bioinformatics, 2020, v. 2 n. 3, p. article no. lqaa071 How to Cite? |
Abstract | Detection of copy number variations (CNVs) is essential for uncovering genetic factors underlying human diseases. However, CNV detection by current methods is prone to error, and precisely identifying CNVs from paired-end whole genome sequencing (WGS) data is still challenging. Here, we present a framework, CNV-JACG, for Judging the Accuracy of CNVs and Genotyping using paired-end WGS data. CNV-JACG is based on a random forest model trained on 21 distinctive features characterizing the CNV region and its breakpoints. Using the data from the 1000 Genomes Project, Genome in a Bottle Consortium, the Human Genome Structural Variation Consortium and in-house technical replicates, we show that CNV-JACG has superior sensitivity over the latest genotyping method, SV2, particularly for the small CNVs (≤1 kb). We also demonstrate that CNV-JACG outperforms SV2 in terms of Mendelian inconsistency in trios and concordance between technical replicates. Our study suggests that CNV-JACG would be a useful tool in assessing the accuracy of CNVs to meet the ever-growing needs for uncovering the missing heritability linked to CNVs. |
Persistent Identifier | http://hdl.handle.net/10722/295279 |
ISSN | 2023 Impact Factor: 4.0 2023 SCImago Journal Rankings: 2.454 |
PubMed Central ID | |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | ZHUANG, X | - |
dc.contributor.author | YE, R | - |
dc.contributor.author | So, MT | - |
dc.contributor.author | Lam, WY | - |
dc.contributor.author | KARIM, A | - |
dc.contributor.author | Yu, M | - |
dc.contributor.author | Ngo, ND | - |
dc.contributor.author | Cherny, SS | - |
dc.contributor.author | Tam, PKH | - |
dc.contributor.author | Garcia-Barcelo, MM | - |
dc.contributor.author | Tang, CSM | - |
dc.contributor.author | Sham, PC | - |
dc.date.accessioned | 2021-01-11T13:57:52Z | - |
dc.date.available | 2021-01-11T13:57:52Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | NAR Genomics and Bioinformatics, 2020, v. 2 n. 3, p. article no. lqaa071 | - |
dc.identifier.issn | 2631-9268 | - |
dc.identifier.uri | http://hdl.handle.net/10722/295279 | - |
dc.description.abstract | Detection of copy number variations (CNVs) is essential for uncovering genetic factors underlying human diseases. However, CNV detection by current methods is prone to error, and precisely identifying CNVs from paired-end whole genome sequencing (WGS) data is still challenging. Here, we present a framework, CNV-JACG, for Judging the Accuracy of CNVs and Genotyping using paired-end WGS data. CNV-JACG is based on a random forest model trained on 21 distinctive features characterizing the CNV region and its breakpoints. Using the data from the 1000 Genomes Project, Genome in a Bottle Consortium, the Human Genome Structural Variation Consortium and in-house technical replicates, we show that CNV-JACG has superior sensitivity over the latest genotyping method, SV2, particularly for the small CNVs (≤1 kb). We also demonstrate that CNV-JACG outperforms SV2 in terms of Mendelian inconsistency in trios and concordance between technical replicates. Our study suggests that CNV-JACG would be a useful tool in assessing the accuracy of CNVs to meet the ever-growing needs for uncovering the missing heritability linked to CNVs. | - |
dc.language | eng | - |
dc.publisher | Oxford University Press: Open Access Journals. The Journal's web site is located at https://academic.oup.com/nargab | - |
dc.relation.ispartof | NAR Genomics and Bioinformatics | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.title | A random forest-based framework for genotyping and accuracy assessment of copy number variations | - |
dc.type | Article | - |
dc.identifier.email | So, MT: jaymtso@hku.hk | - |
dc.identifier.email | Lam, WY: wyslam@hku.hk | - |
dc.identifier.email | Cherny, SS: cherny@hku.hk | - |
dc.identifier.email | Tam, PKH: paultam@hku.hk | - |
dc.identifier.email | Garcia-Barcelo, MM: mmgarcia@hku.hk | - |
dc.identifier.email | Tang, CSM: claratang@hku.hk | - |
dc.identifier.email | Sham, PC: pcsham@hku.hk | - |
dc.identifier.authority | Cherny, SS=rp00232 | - |
dc.identifier.authority | Tam, PKH=rp00060 | - |
dc.identifier.authority | Garcia-Barcelo, MM=rp00445 | - |
dc.identifier.authority | Tang, CSM=rp02105 | - |
dc.identifier.authority | Sham, PC=rp00459 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1093/nargab/lqaa071 | - |
dc.identifier.pmid | 33575619 | - |
dc.identifier.pmcid | PMC7671382 | - |
dc.identifier.scopus | eid_2-s2.0-85113271334 | - |
dc.identifier.hkuros | 320790 | - |
dc.identifier.volume | 2 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | article no. lqaa071 | - |
dc.identifier.epage | article no. lqaa071 | - |
dc.identifier.isi | WOS:000645609500013 | - |
dc.publisher.place | United Kingdom | - |