Quantifying uniformity of mapped reads

TL;DR

This paper introduces a new statistical tool for quantifying the uniformity of mapped reads in high-throughput sequencing, helping to identify biases in protocols and mapping procedures.

Contribution

The authors present a novel statistic and p-value computation method for assessing read uniformity, applicable to various sequencing experiments like RNA-Seq.

Findings

Provides a new measure for read uniformity

Enables comparison of sequencing protocols

Offers an open-source Python tool

Abstract

Summary: We describe a tool for quantifying the uniformity of mapped reads in high-throughput sequencing experiments. Our statistic directly measures the uniformity of both read position and fragment length, and we explain how to compute a p-value that can be used to quantify biases arising from experimental protocols and mapping procedures. Our method is useful for comparing different protocols in experiments such as RNA-Seq. Availability and Implementation: We provide a freely available and open source python script that can be used to analyze raw read data or reads mapped to transcripts in BAM format at http://www.math.miami.edu/~vhower/ReadSpy.html . Contact: lpachter@math.berkeley.edu