UNLABELLED: 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.
UNLABELLED: 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.
Authors: Lauren C Chong; Marco A Albuquerque; Nicholas J Harding; Cristian Caloian; Michelle Chan-Seng-Yue; Richard de Borja; Michael Fraser; Robert E Denroche; Timothy A Beck; Theodorus van der Kwast; Robert G Bristow; John D McPherson; Paul C Boutros Journal: Nat Methods Date: 2014-08-31 Impact factor: 28.547