Identification of rare DNA variants using SRMA

It is still challenging to identify rare functional DNA variants. Custom array-based resequencing has an advantage of processing hundreds of individuals at reasonable cost and has been used for medical sequencing studies with targeted genes. However, high false positive rate (FPR ∼3%) in detection of heterozygous signals limited the application of this technology. We have previously developed novel statistical methodology for resequencing array data to largely reduce false discovery rate of single nucleotide variants (FPR< 10−5, false negative rate < 10%). We have established an analysis pipeline for Affymetrix resequencing microarray data analysis and assembled an R package named ‘SRMA’ (sequence robust multi-array analysis). The package contains five modules of quality control, data normalization, single array analysis, multi-array analysis, and output analysis. This tool allows for processing array-based sequencing data and identifying the footprint effects, insertions/deletions, and rare DNA single nucleotide variations (SNV) with high accuracy. We demonstrate the work flow of the SRMA package in this manual.