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motifDiff v1.0: Ultra-fast Variant Effect Prediction with probNorm

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@rezwanhosseini rezwanhosseini released this 24 Jun 16:57
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v1.0.0
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Learn about vigilant mode.

MotifDiff is a fast and scalable tool for predicting the impact of genetic variants on transcription factor (TF) binding using both mono- and dinucleotide PWMs. It supports single nucleotide variants (SNVs) and indels of any length, and introduces a interpretable new normalization strategy (probNorm) that improves performance in variant effect prediction.

This release includes:

  • Support for multiple PWM formats: .meme, .pwm, .pfm, .pcm, .ppm

  • Options for normalization strategies (--method): None, FABIAN, probNorm

  • Support for mono- and dinucleotide motifs (--nuc): mono, di

  • Support for Indels as well as SNVs in .vcf format

  • Supports strand-aware scroing (--strand): +, -, if not passed the max score between the two strands is picked

  • Multiple output scores:

    • binding score on reference sequence (.ref),
    • binding score on alternative sequence (.alt),
    • difference in the binding on the ref and alt sequences (.diff)

  • Reproducible test case included

Paper: Ultra-fast variant effect prediction using biophysical transcription factor binding models

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