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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2011-12-01
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Series: | PLoS Computational Biology |
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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 |
work_keys_str_mv |
AT thadeouskacmarczyk comparativemicrobialmodulesresourcegenerationandvisualizationofmultispeciesbiclusters AT peterwaltman comparativemicrobialmodulesresourcegenerationandvisualizationofmultispeciesbiclusters AT ashleybate comparativemicrobialmodulesresourcegenerationandvisualizationofmultispeciesbiclusters AT patrickeichenberger comparativemicrobialmodulesresourcegenerationandvisualizationofmultispeciesbiclusters AT richardbonneau comparativemicrobialmodulesresourcegenerationandvisualizationofmultispeciesbiclusters |
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