software.html

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title: Software
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<br>
For the full list of our labs software, see out <a href="https://github.com/Boyle-Lab">GitHub Account</a>. This page highlights databases, software packages, analysis tools, and reusable workflows
  developed by Boyle Lab members and collaborators.
<br><br>
<div class="Nheader"><a href="https://regulomedb.org/">RegulomeDB</a>, SURF, TURF, and TLand</div>
<p>
  RegulomeDB annotates variants with functional genomics evidence and predictive models to help
  interpret non-coding regulatory variation. RegulomeDB v2 added expanded functional genomics
  data, improved scoring, tissue-aware prediction resources, and visualization support. TURF
  extends the RegulomeDB framework to prioritize regulatory variants in generic and tissue- or
  organ-specific contexts, while TLand provides machine-learning models for cell- and organ-specific
  regulatory variant prioritization.
</p>
<ul>
  <li><a href="https://regulomedb.org/">RegulomeDB web server</a></li>
  <li><a href="https://github.com/Boyle-Lab/RegulomeDB">RegulomeDB code</a></li>
  <li><a href="https://github.com/Boyle-Lab/RegulomeDB-TURF">TURF code and example data</a></li>
  <li><a href="https://github.com/rnsherpa/TLand-predict">TLand-predict workflow</a></li>
</ul>
<p><strong>References:</strong> Boyle et al., <em>Genome Research</em>, 2012. Dong et al., <em>Nature Genetics</em>, 2023. Dong and Boyle, <em>Nucleic Acids Research</em>, 2021. Zhao, Dong, and Boyle, <em>bioRxiv</em>, 2023.</p>

<br>
<div class="Nheader"><a href="https://github.com/Boyle-Lab/Blacklist">ENCODE Blacklist</a></div>
<p>
  The ENCODE Blacklist identifies genomic regions that show anomalous signal across next-generation
  sequencing experiments. Removing these regions is an important quality-control step for functional
  genomics analyses, especially ChIP-seq, DNase-seq, ATAC-seq, and related assays.
</p>
<p><strong>Reference:</strong> Amemiya, Kundaje, and Boyle, <em>Scientific Reports</em>, 2019.</p>

<br>
<div class="Nheader"><a href="https://github.com/Boyle-Lab/SOM-Browser">Human-Mouse SOM Browser</a> and comparative SOM tools</div>
<p>
  The Boyle Lab developed self-organizing map resources to organize and compare genome-wide regulatory
  activity across human and mouse tissues and cell types. The SOM Browser provides an interactive
  web resource for the human-mouse SOM project, and related repositories provide analysis code for the
  manuscript.
</p>
<ul>
  <li><a href="https://github.com/Boyle-Lab/SOM-Browser">SOM Browser</a></li>
  <li><a href="https://github.com/Boyle-Lab/mouse-human-SOM">Mouse-human SOM analysis code</a></li>
</ul>
<p><strong>Reference:</strong> Diehl et al., <em>Nucleic Acids Research</em>, 2018.</p>

<br>
<div class="Nheader"><a href="http://fureylab.web.unc.edu/software/fseq/">F-Seq</a> and <a href="https://github.com/Boyle-Lab/F-Seq2">F-Seq2</a></div>
<p>
  F-Seq is a feature-density estimator for identifying biologically meaningful signal-enriched regions
  from high-throughput sequencing data. F-Seq2 is a Python rewrite and extension that adds dynamic local
  statistics, support for common regulatory genomics assays, and IDR-aware peak-calling workflows.
</p>
<p><strong>References:</strong> Boyle et al., <em>Bioinformatics</em>, 2008. Zhao and Boyle, <em>NAR Genomics and Bioinformatics</em>, 2021.</p>

<br>
<div class="Nheader"><a href="https://github.com/Boyle-Lab/TRACE">TRACE</a> and <a href="https://github.com/Boyle-Lab/TRACE_GPU">TRACE_GPU</a></div>
<p>
  TRACE is a hidden Markov model for transcription factor footprinting and motif matching using
  chromatin-accessibility data, including DNase-seq and ATAC-seq. TRACE_GPU accelerates core TRACE
  computations, including emission-matrix calculation and Viterbi decoding, on GPUs.
</p>
<p><strong>Reference:</strong> Ouyang and Boyle, <em>Genome Research</em>, 2020.</p>

<br>
<div class="Nheader"><a href="https://github.com/Boyle-Lab/SEMpl">SEMpl</a>, <a href="https://github.com/Boyle-Lab/SEMplMe">SEMplMe</a>, and <a href="https://github.com/grkenney/SEMPLR">SEMPLR</a></div>
<p>
  SNP Effect Matrices model the effect of sequence variants on transcription factor binding affinity.
  SEMpl is a command-line implementation of the SEM algorithm, SEMplMe incorporates DNA methylation,
  and SEMPLR provides an R/Bioconductor interface for scoring genomic positions and variants using
  SEMs.
</p>
<p><strong>References:</strong> Nishizaki, et al., <em>Bioinformatics</em>, 2019. Nishizaki and Boyle, <em>BMC Bioinformatics</em>, 2022. Kenney et al., <em>Bioinformatics</em>, 2026.</p>

<br>
<div class="Nheader"><a href="https://github.com/Boyle-Lab/HMMSTR">HMMSTR</a></div>
<p>
  HMMSTR is a modified profile hidden Markov model for determining tandem-repeat copy number from raw
  long-read sequencing data. It is optimized for targeted sequencing experiments.
</p>
<p><strong>Reference:</strong> Van Deynze et al., <em>Nucleic Acids Research</em>, 2025.</p>

<br>
<div class="Nheader"><a href="https://github.com/Boyle-Lab/OnRamp-Web-App">OnRamp</a></div>
<p>
  OnRamp is a bulk plasmid sequencing tool that streamlines pooled plasmid validation. The Boyle Lab
  repository provides the web-enabled version, and the command-line workflow is available through the
  associated bulkPlasmidSeq codebase.
</p>
<ul>
  <li><a href="https://github.com/Boyle-Lab/OnRamp-Web-App">OnRamp web application</a></li>
  <li><a href="https://github.com/Boyle-Lab/bulkPlasmidSeq">bulkPlasmidSeq workflow</a></li>
</ul>
<p><strong>Reference:</strong> Mumm et al., <em>Genome Research</em>, 2023.</p>

<br>
<div class="Nheader"><a href="https://github.com/Boyle-Lab/NanoPal-and-Cas9-targeted-enrichment-pipelines">NanoPal and Cas9 targeted enrichment pipelines</a></div>
<p>
  NanoPal and associated Cas9 targeted enrichment pipelines support long-read enrichment and analysis
  of mobile-element insertions. The repository includes workflows for L1Hs, AluYb, AluYa, SVA_F, and
  SVA_E mobile-element families, plus guide-RNA design, cleavage-site analysis, and methylation analysis
  scripts.
</p>
<ul>
  <li><a href="https://github.com/Boyle-Lab/NanoPal-Snakemake">NanoPal-Snakemake</a></li>
  <li><a href="https://github.com/Boyle-Lab/NanoMEI">NanoMEI</a></li>
</ul>
<p><strong>Reference:</strong> McDonald et al., <em>Nature Communications</em>, 2021.</p>

<br>
<div class="Nheader"><a href="https://github.com/Boyle-Lab/minimera">Minimera</a></div>
<p>
  Minimera detects foldback chimeras in Oxford Nanopore sequencing data using minimizers and is released
  as command-line binaries and Singularity containers.
</p>