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  LSTrAP: efficiently combining RNA sequencing data into co-expression networks

Proost, S., Krawczyk, A., & Mutwil, M. (2017). LSTrAP: efficiently combining RNA sequencing data into co-expression networks. BMC Bioinformatics, 18(1): 444. doi:10.1186/s12859-017-1861-z.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002E-089E-5 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002E-089F-3
Genre: Journal Article

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Proost, Sebastian1, Author              
Krawczyk, Agnieszka2, Author
Mutwil, M.1, Author              
Affiliations:
1Regulatory Networks, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753332              
2External Organizations, ou_persistent22              

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 Abstract: Since experimental elucidation of gene function is often laborious, various in silico methods have been developed to predict gene function of uncharacterized genes. Since functionally related genes are often expressed in the same tissues, conditions and developmental stages (co-expressed), functional annotation of characterized genes can be transferred to co-expressed genes lacking annotation. With genome-wide expression data available, the construction of co-expression networks, where genes are nodes and edges connect significantly co-expressed genes, provides unprecedented opportunities to predict gene function. However, the construction of such networks requires large volumes of high-quality data, multiple processing steps and a considerable amount of computation power. While efficient tools exist to process RNA-Seq data, pipelines which combine them to construct co-expression networks efficiently are currently lacking.

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 Dates: 2017-10
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1186/s12859-017-1861-z
BibTex Citekey: Proost2017
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Title: BMC Bioinformatics
Source Genre: Journal
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Publ. Info: BioMed Central
Pages: - Volume / Issue: 18 (1) Sequence Number: 444 Start / End Page: - Identifier: ISSN: 1471-2105
CoNE: https://pure.mpg.de/cone/journals/resource/111000136905000