henhaobio
Sign in

Bioinformatics AdvancesGenomicsPeer-reviewed journal article

AmalgaMo: flexible DNA motif merging

Orsolya LapohosiD, Gregory J. FonsecaiD

PDFDOIPreprintCode

Abstract

MotivationInference of candidate upstream regulators via motif enrichment analysis is a common step in the interpretation of genomic data. However, redundancy in motif databases can negatively impact predictive value, especially when relying on regression-based motif enrichment analysis. Although various forms of motif clustering have been used to mitigate problems caused by redundancy, an algorithm optimized for downstream regression-based analysis is needed. ResultsWe introduce AmalgaMo, an efficient and flexible command line tool for merging highly similar motifs. Using publicly available human datasets, we demonstrate that merging motifs with our optimized settings greatly benefits regression-based motif enrichment analysis and provide detailed documentation that can serve as a reference for researchers inferring upstream regulators from genomic data. AvailabilitySource code is available on GitHub at https://github.com/lapohosorsolya/AmalgaMo.

Citations
0
FWCI
0.00
Field percentile
7th percentile

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISNielsen '18Bailey '21Amezquita '18Fang '19Grant '21Khan '22
60% semantic matchBioinformatics
Morten Muhlig Nielsen, Paula Tataru, Tobias Madsen+2 more·Algorithms for Molecular Biology·Dec 8, 2018