• gMVP (updated 2022), a graph attention neural network method for predicting functional effect of missense variants. Preprint is available on bioRxiv
• CNV-Espresso (updated 2022), a method for in silico confirmation of copy number variants called from exome sequencing data, as described in Tan and Shen, 2022
• VBASS (updated 2022), a probabilistic model that integrates single cell gene expression profile with rare genetic variation to identify risk genes of human conditions and diseases. A preprint is available: Zhong et al 2022
• MVP (updated 2021), an ensemble predictor of deleterious genetic effect of missense variants using residual convolutional neural networks, as described in Qi et al 2021.
• EM-mosaic (updated 2019), a method to detect mosaic mutations from trio exome or whole genome sequencing data. Use EM algorithm to infer overall rate of mosaicism among de novo mutations. Published in Hsieh et al 2020
• A-risk (updated 2020), a method to predict plausibility of being risk genes of autism based on expression patterns in brain single cells. Manuscript under prep.
• Episcore (Updated 2018), a method to predict gene haploinsufficiency based on human epigenomic profiles under normal conditions, as described in Han, Chen et al 2018
• HotSpots (Updated 2016) a method to infer cancer somatic mutation hotspots, as descriibed in Qi et al 2016
• CANOES, (Updated 2014) a method to call CNVs from exome sequencing data with arbitrary number of reference samples.
• Repertoire, (Updated 2015) Scripts for analyzing T cell receptor repertoire sequencing data.
• OPERA , (updated 2012) an online power calculator for genome sequencing and genetic studies
• Zinfandel, (updated 2012) calling Copy Number Variants (CNVs) from whole genome data based on both depth of coverage and mate pair information
• Atlas-SNP, (last updated 2010) bioinformatics analysis of next-generation sequencing, optimized for variant calling from 454 data
• Genometer, (last updated 2011) estimating genome size in the presence of repeats