Related Experiment Video
Updated: May 22, 2026

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
Published on: June 24, 2021
SRMA: an R package for resequencing array data analysis
Nianxiang Zhang1, Yan Xu, Martin O'Hely
1Department of Bioinformatics and Computational Biology, UT MD Anderson Cancer Center, Houston, TX 77030, USA.
Unlabelled:
Sequencing by hybridization to oligonucleotides has evolved into an inexpensive, reliable and fast technology for targeted sequencing. Hundreds of human genes can now be sequenced within a day using a single hybridization to a resequencing microarray. However, several issues inherent to these arrays (e.g. cross-hybridization, variable probe/target affinity) cause sequencing errors and have prevented more widespread applications. We developed an R package for resequencing microarray data analysis that integrates a novel statistical algorithm, sequence robust multi-array analysis (SRMA), for rare variant detection with high sensitivity (false negative rate, FNR 5%) and accuracy (false positive rate, FPR 1×10⁻⁵). The SRMA package consists of five modules for quality control, data normalization, single array analysis, multi-array analysis and output analysis. The entire workflow is efficient and identifies rare DNA single nucleotide variations and structural changes such as gene deletions with high accuracy and sensitivity.
Availability:
http://cran.r-project.org/, http://odin.mdacc.tmc.edu/~wwang7/SRMAIndex.html
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