The MEME Suite.

Timothy L Bailey,William S Noble,Charles E Grant,James Johnson

doi:10.1093/nar/gkv416

The MEME Suite.

Timothy L Bailey, William S Noble + Show 2 more

Open Access

https://doi.org/10.1093/nar/gkv416

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Abstract

The MEME Suite is a powerful, integrated set of web-based tools for studying sequence motifs in proteins, DNA and RNA. Such motifs encode many biological functions, and their detection and characterization is important in the study of molecular interactions in the cell, including the regulation of gene expression. Since the previous description of the MEME Suite in the 2009 Nucleic Acids Research Web Server Issue, we have added six new tools. Here we describe the capabilities of all the tools within the suite, give advice on their best use and provide several case studies to illustrate how to combine the results of various MEME Suite tools for successful motif-based analyses. The MEME Suite is freely available for academic use at http://meme-suite.org, and source code is also available for download and local installation.

Highlights

A DNA, RNA or protein sequence motif is a short pattern that is conserved by evolution
The MEME Suite is a software toolkit for performing motif-based sequence analysis, which is valuable in a wide variety of scientific contexts
The MEME Suite software has played an important role in the study of biological processes involving DNA, RNA and proteins in over 9800 published studies

Summary

INTRODUCTION

A DNA, RNA or protein sequence motif is a short pattern that is conserved by evolution. The web-based version of the MEME Suite includes 13 tools [1,2,3,4,5,6,7,8,9,10,11,12,13] for performing motif discovery, motif enrichment analysis, motif scanning and motif–motif comparisons (Figure 1). In addition to motif discovery, the MEME Suite provides tools for scanning sequences for matches to motifs (MAST, FIMO and GLAM2Scan), scanning for clusters of motifs (MCAST), comparing motifs to known motifs (Tomtom), finding preferred spacings between DNA motifs (SpaMo), predicting the biological roles of DNA motifs (GOMo), measuring the positional enrichment of sequences for known DNA motifs (CentriMo), and analyzing ChIP-seq and other large DNA datasets (MEME-ChIP).

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