Published December 10, 2018 | Version v1
Journal article Open

A new sequence logo plot to highlight enrichment and depletion

  • 1. University of Chicago

Description

Background: Sequence logo plots have become a standard graphical tool for visualizing sequence motifs in DNA, RNA or protein sequences. However standard logo plots primarily highlight enrichment of symbols, and may fail to highlight interesting depletions. Current alternatives that try to highlight depletion often produce visually cluttered logos.

Results: We introduce a new sequence logo plot, the EDLogo plot, that highlights both enrichment and depletion, while minimizing visual clutter. We provide an easy-to-use and highly customizable R package Logolas to produce a range of logo plots, including EDLogo plots. This software also allows elements in the logo plot to be strings of characters, rather than a single character, extending the range of applications beyond the usual DNA, RNA or protein sequences. And the software includes new Empirical Bayes methods to stabilize estimates of enrichment and depletion, and thus better highlight the most significant patterns in data. We illustrate our methods and software on applications to transcription factor binding site motifs, protein sequence alignments and cancer mutation signature profiles.

Conclusions: Our new EDLogo plots and flexible software implementation can help data analysts visualize both enrichment and depletion of characters (DNA sequence bases, amino acids, etc.) across a wide range of applications.

Data availability

The Logolas package is available for R (≥ 3.4) users as a Github R package (https://github.com/kkdey/Logolas). Code for reproducing figures in this paper is available at https://github.com/kkdey/Logolas-paper. Vignettes and a gallery demonstrating features of Logolas are available at https://github.com/kkdey/Logolas-pages.

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Additional details

Identifiers

DOI
10.1186/s12859-018-2489-3
Other
oai:uchicago.tind.io:5740

Funding

National Institutes of Health
BD2K grant
National Institutes of Health
HG002585

UChicago Information

Division(s)
Biological Sciences Division, Physical Sciences Division
Department(s)
Human Genetics, Statistics