Two-pass alignment improves novel splice junction quantification

Brendan Veeneman, Sudhanshu Shukla, Saravana M. Dhanasekaran, Arul M. Chinnaiyan, Alexey I. Nesvizhskii

Bioinformatics · 2015 · 82 citations · 13 references

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Abstract

MOTIVATION: Discovery of novel splicing from RNA sequence data remains a critical and exciting focus of transcriptomics, but reduced alignment power impedes expression quantification of novel splice junctions. RESULTS: Here, we profile performance characteristics of two-pass alignment, which separates splice junction discovery from quantification. Per sample, across a variety of transcriptome sequencing datasets, two-pass alignment improved quantification of at least 94% of simulated novel splice junctions, and provided as much as 1.7-fold deeper median read depth over those splice junctions. We further demonstrate that two-pass alignment works by increasing alignment of reads to splice junctions by short lengths, and that potential alignment errors are readily identifiable by simple classification. Taken together, two-pass alignment promises to advance quantification and discovery of novel splicing events. CONTACT: arul@med.umich.edu, nesvi@med.umich.edu AVAILABILITY AND IMPLEMENTATION: Two-pass alignment was implemented here as sequential alignment, genome indexing, and re-alignment steps with STAR. Full parameters are provided in Supplementary Table 2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

References

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