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kpLogo: positional k-mer analysis reveals hidden specificity in biological sequences

Author(s)
Wu, Xuebing; Bartel, David
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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/.
Date issued
2017-04
URI
http://hdl.handle.net/1721.1/110128
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
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
ISSN
0305-1048
1362-4962

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