Comparative microbial modules resource: generation and visualization of multi-species biclusters.

The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets a...

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Main Authors: Thadeous Kacmarczyk, Peter Waltman, Ashley Bate, Patrick Eichenberger, Richard Bonneau
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-12-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC3228777?pdf=render
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spelling doaj-210b3ce8dc7b490dbb1ddb00e637a8762020-11-25T01:32:25ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582011-12-01712e100222810.1371/journal.pcbi.1002228Comparative microbial modules resource: generation and visualization of multi-species biclusters.Thadeous KacmarczykPeter WaltmanAshley BatePatrick EichenbergerRichard BonneauThe increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures - results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation.http://europepmc.org/articles/PMC3228777?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Thadeous Kacmarczyk
Peter Waltman
Ashley Bate
Patrick Eichenberger
Richard Bonneau
spellingShingle Thadeous Kacmarczyk
Peter Waltman
Ashley Bate
Patrick Eichenberger
Richard Bonneau
Comparative microbial modules resource: generation and visualization of multi-species biclusters.
PLoS Computational Biology
author_facet Thadeous Kacmarczyk
Peter Waltman
Ashley Bate
Patrick Eichenberger
Richard Bonneau
author_sort Thadeous Kacmarczyk
title Comparative microbial modules resource: generation and visualization of multi-species biclusters.
title_short Comparative microbial modules resource: generation and visualization of multi-species biclusters.
title_full Comparative microbial modules resource: generation and visualization of multi-species biclusters.
title_fullStr Comparative microbial modules resource: generation and visualization of multi-species biclusters.
title_full_unstemmed Comparative microbial modules resource: generation and visualization of multi-species biclusters.
title_sort comparative microbial modules resource: generation and visualization of multi-species biclusters.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2011-12-01
description The increasing abundance of large-scale, high-throughput datasets for many closely related organisms provides opportunities for comparative analysis via the simultaneous biclustering of datasets from multiple species. These analyses require a reformulation of how to organize multi-species datasets and visualize comparative genomics data analyses results. Recently, we developed a method, multi-species cMonkey, which integrates heterogeneous high-throughput datatypes from multiple species to identify conserved regulatory modules. Here we present an integrated data visualization system, built upon the Gaggle, enabling exploration of our method's results (available at http://meatwad.bio.nyu.edu/cmmr.html). The system can also be used to explore other comparative genomics datasets and outputs from other data analysis procedures - results from other multiple-species clustering programs or from independent clustering of different single-species datasets. We provide an example use of our system for two bacteria, Escherichia coli and Salmonella Typhimurium. We illustrate the use of our system by exploring conserved biclusters involved in nitrogen metabolism, uncovering a putative function for yjjI, a currently uncharacterized gene that we predict to be involved in nitrogen assimilation.
url http://europepmc.org/articles/PMC3228777?pdf=render
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