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TieBrush: an efficient method for aggregating and summarizing mapped reads across large datasets
Ales Varabyou1,2, Geo Pertea3, Christopher Pockrandt1,4
1Center for Computational Biology, Johns Hopkins University, Baltimore, MD 21211, USA.
Summary:
Although the ability to programmatically summarize and visually inspect sequencing data is an integral part of genome analysis, currently available methods are not capable of handling large numbers of samples. In particular, making a visual comparison of transcriptional landscapes between two sets of thousands of RNA-seq samples is limited by available computational resources, which can be overwhelmed due to the sheer size of the data. In this work, we present TieBrush, a software package designed to process very large sequencing datasets (RNA, whole-genome, exome, etc.) into a form that enables quick visual and computational inspection. TieBrush can also be used as a method for aggregating data for downstream computational analysis, and is compatible with most software tools that take aligned reads as input.
Availability And Implementation:
TieBrush is provided as a C++ package under the MIT License. Precompiled binaries, source code and example data are available on GitHub (https://github.com/alevar/tiebrush).
Supplementary Information:
Supplementary data are available at Bioinformatics online.
