Protocols

Read-Split-Run specifications

Information


Unique identifier OMICS_18038
Name Read-Split-Run
Interface Web user interface
Input data RNA-Seq File
Input format FASTQ
License Apache License version 2.0
Computer skills Basic
Stability Stable
Maintained Yes

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Maintainer


  • person_outline Yongsheng Bai

Information


Unique identifier OMICS_18038
Name Read-Split-Run
Software type Package/Module
Interface Command line interface
Operating system Unix/Linux
Programming languages C
License Apache License version 2.0
Computer skills Advanced
Stability Stable
Maintained Yes

Download


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Versioning


No version available

Maintainer


  • person_outline Yongsheng Bai

Publication for Read-Split-Run

Read-Split-Run citations

 (2)
library_books

Identification of genome wide non canonical spliced regions and analysis of biological functions for spliced sequences using Read Split Fly

2017
BMC Bioinformatics
PMCID: 5629565
PMID: 28984182
DOI: 10.1186/s12859-017-1801-y

[…] using bioinformatics approaches in conjunction with next-generation technologies at a genome-wide level.We have developed a novel bioinformatics pipeline method named the Read-Split-Walk (RSW) [] and Read-Split-Run (RSR) [] for detecting non-canonical, short, splicing regions using RNA-Seq data. In this study, we have advanced the algorithm with an improved running speed and memory usage. We have […]

call_split

Intelligent biology and medicine in 2015: advancing interdisciplinary education, collaboration, and data science

2016
BMC Genomics
PMCID: 5001210
PMID: 27556295
DOI: 10.1186/s12864-016-2893-x
call_split See protocol

[…] s associated with bacterial survival and virulence, and also to establish a disease model to study the immune pathogenesis of bacterial myocarditis. In [], Bai et al. presented an improved algorithm “Read-Split-Run” (RSR) for detecting genome-wide Ire1α-targeted genes with non-canonical spliced regions at a faster speed. They compared the RSR algorithm to the “Read-Split-Walk” (RSW) algorithm when […]

Read-Split-Run institution(s)
Department of Biology, Terre Haute, IN, USA; The Center for Genomic Advocacy, Indiana State University, Terre Haute, IN, USA; Department of Mathematics and Computer Science, Indiana State University, Terre Haute, IN, USA; Sanford-Burnham-Prebys Medical Discovery Institute, La Jolla, CA, USA
Read-Split-Run funding source(s)
This research was supported by ISU start-up funds, NIH grants DK088227, DK042394, DK103183 and CA128814 and the Hevery Foundation.

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