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Biology subjects

Law, W.-C.

Publications and source records attributed to Law, W.-C..

2 recordsLinked to original sources

HKG: An open genetic variant database of 205 Hong Kong Cantonese exomes

HKG is the first fully accessible variant database for Hong Kong Cantonese, constructed from 205 novel whole-exome sequencing data. There has long been a research gap in the understanding of the genetic architecture of southern Chinese subgroups, including Hong Kong Cantonese. HKG detected 196,325 high-quality variants with 5.93% being novel, and 25,472 variants were found to be unique in HKG compared to other Chinese populations (CHN). PCA illustrates the uniqueness of HKG in CHN, and IBD analysis revealed that it is related mostly to southern Chinese with a similar effective population size. An admixture study estimated the ancestral composition of HKG and CHN, with a gradient change from north to south, consistent with their geological distribution. ClinVar, CIViC and PharmGKB annotated 599 clinically significant variants and 360 putative loss-of-function variants, substantiating our understanding of population characteristics for future medical development. Among the novel variants, 96.57% were singleton and 6.85% were of high impact. With a good representation of Hong Kong Cantonese, we demonstrated better variant imputation using reference with the addition of HKG data, thus successfully filling the data gap in southern Chinese to facilitate the regional and global development of population genetics.

bioinformatics

SENSV: Detecting Structural Variations with Precise Breakpoints using Low-Depth WGS Data from a Single Oxford Nanopore MinION Flowcell

Structural variation (SV) is a major cause of genetic disorders. In this paper, we show that low-depth (specifically, 4x) whole-genome sequencing using a single Oxford Nanopore MinION flow cell suffices to support sensitive detection of SV, in particular, pathogenic SV for supporting clinical diagnosis. Existing SV calling software, when using 4x ONT WGS data, often fails to detect pathogenic SV especially in the form of long deletion, terminal deletion, duplication, and unbalanced translocation. Our new SV calling software SENSV is able to achieve high sensitivity for all types of SV and a breakpoint precision typically {+/-}100 bp, both features are important for clinical concerns. The improvement achieved by SENSV stems from several new algorithms. We evaluated SENSV and other software using both real and simulated data. The former was based on 24 patient samples, each diagnosed with a genetic disorder. SENSV found the pathogenic SV in 22 out of 24 cases (all heterozygous, size from hundreds of Kbp to a few Mbp), reporting breakpoints within 100 bp of the true answers. No existing software can detect the pathogenic SV in more than 10 out of 24 cases, even when the breakpoint requirement is relaxed to {+/-}2,000 bp.

bioinformatics