A novel multi-alignment pipeline for high-throughput sequencing data

摘要: Mapping reads to a reference sequence is common step when analyzing allele effects in high-throughput sequencing data. The choice of critical because its effect on quantitative analysis non-negligible. Recent studies suggest aligning single standard sequence, as practice, can lead an underlying bias depending the genetic distances target sequences from reference. To avoid this bias, researchers have resorted using modified sequences. Even with improvement, various limitations and problems remain unsolved, which include reduced mapping ratios, shifts read mappings selection variants remove biases. address these issues, we propose novel generic multi-alignment pipeline. Our pipeline integrates genomic variations known or suspected founders into separate performs alignments each one. By multiple merging them afterward, are able rescue more diminish caused by Moreover, origin determined annotated during process, providing better source information assess differential expression than simple queries at variant positions. Using RNA-seq diallel cross, compare our single-reference demonstrate advantages aligned higher percentage assigned origins. Database URL: http://csbio.unc.edu/CCstatus/index.py?run=Pseudo.