Literature DB >> 33964128

TieBrush: an efficient method for aggregating and summarizing mapped reads across large datasets.

Ales Varabyou1,2, Geo Pertea3, Christopher Pockrandt1,4, Mihaela Pertea1,2,4.   

Abstract

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: TieBrush is provided as a C ++ package under the MIT License. Pre-compiled binaries, source code and example data are available on GitHub (https://github.com/alevar/tiebrush). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) (2021). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Year:  2021        PMID: 33964128      PMCID: PMC8545345          DOI: 10.1093/bioinformatics/btab342

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  8 in total

1.  The Sequence Alignment/Map format and SAMtools.

Authors:  Heng Li; Bob Handsaker; Alec Wysoker; Tim Fennell; Jue Ruan; Nils Homer; Gabor Marth; Goncalo Abecasis; Richard Durbin
Journal:  Bioinformatics       Date:  2009-06-08       Impact factor: 6.937

2.  BEDTools: a flexible suite of utilities for comparing genomic features.

Authors:  Aaron R Quinlan; Ira M Hall
Journal:  Bioinformatics       Date:  2010-01-28       Impact factor: 6.937

3.  The Genotype-Tissue Expression (GTEx) project.

Authors: 
Journal:  Nat Genet       Date:  2013-06       Impact factor: 38.330

4.  Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration.

Authors:  Helga Thorvaldsdóttir; James T Robinson; Jill P Mesirov
Journal:  Brief Bioinform       Date:  2012-04-19       Impact factor: 11.622

5.  The UCSC Genome Browser database: 2015 update.

Authors:  Kate R Rosenbloom; Joel Armstrong; Galt P Barber; Jonathan Casper; Hiram Clawson; Mark Diekhans; Timothy R Dreszer; Pauline A Fujita; Luvina Guruvadoo; Maximilian Haeussler; Rachel A Harte; Steve Heitner; Glenn Hickey; Angie S Hinrichs; Robert Hubley; Donna Karolchik; Katrina Learned; Brian T Lee; Chin H Li; Karen H Miga; Ngan Nguyen; Benedict Paten; Brian J Raney; Arian F A Smit; Matthew L Speir; Ann S Zweig; David Haussler; Robert M Kuhn; W James Kent
Journal:  Nucleic Acids Res       Date:  2014-11-26       Impact factor: 19.160

6.  Mosdepth: quick coverage calculation for genomes and exomes.

Authors:  Brent S Pedersen; Aaron R Quinlan
Journal:  Bioinformatics       Date:  2018-03-01       Impact factor: 6.937

7.  Alternative isoform regulation in human tissue transcriptomes.

Authors:  Eric T Wang; Rickard Sandberg; Shujun Luo; Irina Khrebtukova; Lu Zhang; Christine Mayr; Stephen F Kingsmore; Gary P Schroth; Christopher B Burge
Journal:  Nature       Date:  2008-11-27       Impact factor: 49.962

8.  Snaptron: querying splicing patterns across tens of thousands of RNA-seq samples.

Authors:  Christopher Wilks; Phani Gaddipati; Abhinav Nellore; Ben Langmead
Journal:  Bioinformatics       Date:  2018-01-01       Impact factor: 6.937

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.