Quantifying uniformity of mapped reads

Abstract

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.

Fig. 1

An illustration of the method. Fragments aligning to the Yeast genes YJL140W (A) and YKL041W (B) using dUTP protocol for RNA-Seq are depicted before (t, l-coordinates) and after (x, y-coordinates) our transformation. The horizontal boundaries in the (x, y)-plane are selected by requiring at least C = 200 points fall in each subdivision while the D = 20 vertical subdivisions are equally spaced. When comparing the these dUTP data sets to those from other RNA-Seq protocols, the point set in A is highly biased with a p-value of 1.2e−19 while B appears to be a random collection of points (p = 0.27)