Software by Katerina J. Kechris

• SmCCNet (R package: J. Shi) Link to CRAN Link to GitHub

  Correlation analysis based method for discovering (quantitative) trait-specific multi-omics networks.

• miR-MaGiC (Java/Snakemake pipeline: P. Russell) Link to GitHub

  Pipeline for miRNA expression quantification from small RNA-seq see Russell et al., 2018

• HeritSeq (R package: J. Shi, P. Rudra, B. Vestal, P. Russell) Link to CRAN

  Calculate heritability of count based expression traits derived from high-throughput sequencing experiments. see Rudra, Wen, Vestal et al., 2017

• Discordant (R package: C. Siska) Link to Bioconductor Link to GitHub

  Identify pairs of features that differentially correlate between phenotypic groups, with application to -omics data. see Siska et al., 2016 and Siska & Kechris, 2017.

• multiMiR (R package: Y. Ru) Link to webserver Link to GitHub Link to Bioconductor

  Comprehensive collection of predicted and validated miRNA-target interactions and their associations with diseases and drugs. see Ru et al., 2014.

• MSPrep (R package: G. Hughes) Link to SourceForge

  Post processing of LC/MS metabolomic data: Performs summarization of replicates, filtering, imputation, normalization, generates diagnostic plots and outputs final analytic datasets for downstream analysis. see Hughes et al., 2014.

• lcmix (R package: D. Dvorkin) Link to R-Forge

  Hierarchical mixture models for genomic data integration. see Dvorkin et al., 2013.

• comb-p (Python code: B. Pedersen) Link to GitHub

  Combining genome-wide p-values using a modified Stouffer-Liptak test corrected for spatial correlations. see Kechris et al., 2010 and Pedersen et al., 2012

• SULDEX (ANSI C++ code) Link to SULDEX Software at Pollock Lab

  Simultaneously analyze binding dissociation constants for large repertoires of sequences based on high throughput sequencing. see Pollock et al., 2011

• c-REDUCE (ANSI C code: assisted by D. Dvorkin) Available upon request

  c(onservation)-REDUCE: Extension of the REDUCE algorithm that incorporates conservation across multiple species to detect motifs that correlate with expression. see Kechris & Li, 2009

• OR-MEME (ANSI C code: M. Richards) Available upon request

  OR-MEME (Order Restricted MEME): Detecting DNA regulatory motifs by constraining the order of information content. see van Zwet et al., 2005

• TFEM (ANSI C code: M. Richards) Available upon request

  TFEM (Transcription Factor Expectation Maximization): Detecting DNA regulatory motifs by incorporating positional trends in information content. see Kechris et al., 2004