kpLogo: positional k-mer analysis reveals hidden specificity in biological sequences
Name
kpLogo.pdf
Size
941.71 KB
Format
Adobe PDF
Checksum (MD5)
c59f28ecfb0ed25d63bfd18f03c56291
Author(s)
Wu, Xuebing
Bartel, David
Date Issued
April 2017
Journal
Nucleic Acids Research
Publisher
Oxford University Press
Citation
Wu, Xuebing, and David P. Bartel. “kpLogo: Positional k-Mer Analysis Reveals Hidden Specificity in Biological Sequences.” Nucleic Acids Research (April 29, 2017).
Version
Final published version
Abstract
Motifs of only 1–4 letters can play important roles when present at key locations within macromolecules. Because existing motif-discovery tools typically miss these position-specific short motifs, we developed kpLogo, a probability-based logo tool for integrated detection and visualization of position-specific ultra-short motifs from a set of aligned sequences. kpLogo also overcomes the limitations of conventional motif-visualization tools in handling positional interdependencies and utilizing ranked or weighted sequences increasingly available from high-throughput assays. kpLogo can be found at http://kplogo.wi.mit.edu/.
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Biology
Terms of Use
Creative Commons Attribution-NonCommercial 4.0 International
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1093/nar/gkx323
