# AmalgaMo: flexible DNA motif merging

## TL;DR

AmalgaMo is a new tool that merges similar DNA motifs to improve the accuracy of predicting upstream regulators in genomic data.

## Contribution

AmalgaMo introduces a novel motif merging algorithm optimized for regression-based motif enrichment analysis.

## Key findings

- Merging motifs with AmalgaMo improves regression-based motif enrichment analysis.
- AmalgaMo is an efficient and flexible command-line tool for motif merging.
- The tool is supported by detailed documentation for genomic data interpretation.

## Abstract

Inference 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.

We 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.

AmalgaMo is available on GitHub at https://github.com/lapohosorsolya/AmalgaMo.