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Updated: Apr 29, 2026

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
FaSD-somatic: a fast and accurate somatic SNV detection algorithm for cancer genome sequencing data
Weixin Wang1, Panwen Wang1, Feng Xu1
1Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Department of Biochemistry, LKS Faculty of Medicine, Hong Kong SAR, Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, Guangdong 518057, HKU-BGI Bioinformatics Algorithms and Core Technology Research Laboratory, Department of Computer Science, Department of Pathology and Centre for Genomic Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
Unlabelled:
Recent advances in high-throughput sequencing technologies have enabled us to sequence large number of cancer samples to reveal novel insights into oncogenetic mechanisms. However, the presence of intratumoral heterogeneity, normal cell contamination and insufficient sequencing depth, together pose a challenge for detecting somatic mutations. Here we propose a fast and an accurate somatic single-nucleotide variations (SNVs) detection program, FaSD-somatic. The performance of FaSD-somatic is extensively assessed on various types of cancer against several state-of-the-art somatic SNV detection programs. Benchmarked by somatic SNVs from either existing databases or de novo higher-depth sequencing data, FaSD-somatic has the best overall performance. Furthermore, FaSD-somatic is efficient, it finishes somatic SNV calling within 14 h on 50X whole genome sequencing data in paired samples.
Availability And Implementation:
The program, datasets and supplementary files are available at http://jjwanglab.org/FaSD-somatic/.
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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