Memes: A motif analysis environment in R using tools from the MEME Suite

Identification of biopolymer motifs represents a key step in the analysis of biological sequences. The MEME Suite is a widely used toolkit for comprehensive analysis of biopolymer motifs; however, these tools are poorly integrated within popular analysis frameworks like the R/Bioconductor project, c...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:PLoS computational biology Jg. 17; H. 9; S. e1008991
Hauptverfasser: Nystrom, Spencer L., McKay, Daniel J.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: San Francisco Public Library of Science 27.09.2021
Public Library of Science (PLoS)
Schlagworte:
Binding sites
Biological analysis
Biology and life sciences
Biopolymers
Computer and Information Sciences
Data structures
Data visualization
Engineering and Technology
Identification and classification
Integrated software
Metadata
Multidimensional data
Physical Sciences
R (Programming language)
Research and Analysis Methods
Scientific visualization
Social Sciences
Source code
Structure
Toolkits
Transcription factors
United States
ISSN:1553-7358, 1553-734X, 1553-7358
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Identification of biopolymer motifs represents a key step in the analysis of biological sequences. The MEME Suite is a widely used toolkit for comprehensive analysis of biopolymer motifs; however, these tools are poorly integrated within popular analysis frameworks like the R/Bioconductor project, creating barriers to their use. Here we present memes, an R package that provides a seamless R interface to a selection of popular MEME Suite tools. memes provides a novel “data aware” interface to these tools, enabling rapid and complex discriminative motif analysis workflows. In addition to interfacing with popular MEME Suite tools, memes leverages existing R/Bioconductor data structures to store the multidimensional data returned by MEME Suite tools for rapid data access and manipulation. Finally, memes provides data visualization capabilities to facilitate communication of results. memes is available as a Bioconductor package at https://bioconductor.org/packages/memes , and the source code can be found at github.com/snystrom/memes.
Bibliographie:new_version
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
The authors have declared that no competing interests exist.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1008991