Next-generation sequencing (NGS) is an emerging technology to determine DNA/RNA sequences for whole genome or specific regions of interest at much lower cost than traditional Sanger sequencing. Combined with other technologies such as RNA extraction (RNA-Seq), enrichment for exome (Exome-seq) or other genomic regions of interest, chromatin immuno-precipitation (ChIP-Seq), and bisulfate conversion (BS-seq), NGS can provide rich information about genetic variants, transcriptome dynamics, transcription factor binding profile, epigenetic modifications, and other information. The applications of NGS are rapidly expanding, and this calls for efficient and creative data storage, analysis, and visualization methods.
We are actively involved in data analysis for a broad range of NGS applications, and have mature analysis pipelines for RNA-Seq data, detection of rare variants, and ChIP-Seq data. We routinely use in-house programs, as well as multiple commercial and open-source tools for different steps of the NGS data analysis, from base calling, sequence alignment, to downstream statistical analysis to suit various experimental designs. Moreover, we are devoted to developing novel and useful statistical tools for NGS data analysis. We carefully examine possible sources of abnormalities in data processing and searching for ways to overcome inherent bias in NGS data analysis.