Cloud-scale SNP detection from RNA-Seq data

Next generation sequencing (NGS) is a powerful method increasing in popularity for the study of human variation and disease. This paper proposes a cloud-computing algorithm that detects SNPs from high-throughput RNA sequence data. By executing in parallel using Hadoop, it identifies SNPs by carefully considering the alignment method and sequencing errors inherent in real data. The analysis results containing the RNA reads and SNP calls can be imported directly into Sequence_Analyzer for the visualization and validation of results.