| Title: |
A random forest-based framework for genotyping and accuracy assessment of copy number variations |
| Authors: |
ZHUANG, X; YE, R; So, MT; Lam, WY; KARIM, A; Yu, M; Ngo, ND; Cherny, SS; Tam, PKH; Garcia-Barcelo, MM; Tang, CSM; Sham, PC |
| Publisher Information: |
United Kingdom; Oxford University Press: Open Access Journals. The Journal's web site is located at https://academic.oup.com/nargab |
| Publication Year: |
2020 |
| Collection: |
University of Hong Kong: HKU Scholars Hub |
| Description: |
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. ; published_or_final_version |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| Relation: |
NAR Genomics and Bioinformatics; NAR Genomics and Bioinformatics, 2020, v. 2 n. 3, p. article no. lqaa071; article no. lqaa071; 320790; WOS:000645609500013; PMC7671382; https://hub.hku.hk/handle/10722/295279 |
| DOI: |
10.1093/nargab/lqaa071 |
| Availability: |
https://hub.hku.hk/handle/10722/295279; https://doi.org/10.1093/nargab/lqaa071 |
| Rights: |
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
| Accession Number: |
edsbas.CCFD042E |
| Database: |
BASE |