In:
PLOS ONE, Public Library of Science (PLoS), Vol. 15, No. 11 ( 2020-11-6), p. e0242030-
Abstract:
Sequence logos have been widely used as graphical representations of conserved nucleic acid and protein motifs. Due to the complexity of the amino acid (AA) alphabet, rich post-translational modification, and diverse subcellular localization of proteins, few versatile tools are available for effective identification and visualization of protein motifs. In addition, various reduced AA alphabets based on physicochemical, structural, or functional properties have been valuable in the study of protein alignment, folding, structure prediction, and evolution. However, there is lack of tools for applying reduced AA alphabets to the identification and visualization of statistically significant motifs. To fill this gap, we developed an R/Bioconductor package dagLogo, which has several advantages over existing tools. First, dagLogo allows various formats for input sets and provides comprehensive options to build optimal background models. It implements different reduced AA alphabets to group AAs of similar properties. Furthermore, dagLogo provides statistical and visual solutions for differential AA (or AA group) usage analysis of both large and small data sets. Case studies showed that dagLogo can better identify and visualize conserved protein sequence patterns from different types of inputs and can potentially reveal the biological patterns that could be missed by other logo generators.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0242030
DOI:
10.1371/journal.pone.0242030.g001
DOI:
10.1371/journal.pone.0242030.g002
DOI:
10.1371/journal.pone.0242030.g003
DOI:
10.1371/journal.pone.0242030.g004
DOI:
10.1371/journal.pone.0242030.s001
DOI:
10.1371/journal.pone.0242030.s002
DOI:
10.1371/journal.pone.0242030.s003
DOI:
10.1371/journal.pone.0242030.s004
DOI:
10.1371/journal.pone.0242030.s005
DOI:
10.1371/journal.pone.0242030.s006
DOI:
10.1371/journal.pone.0242030.s007
DOI:
10.1371/journal.pone.0242030.s008
DOI:
10.1371/journal.pone.0242030.r001
DOI:
10.1371/journal.pone.0242030.r002
DOI:
10.1371/journal.pone.0242030.r003
DOI:
10.1371/journal.pone.0242030.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2020
detail.hit.zdb_id:
2267670-3