Für unsere Aufgaben benutzen wir vor allem R und Bioconductor-Softwarepakete.
Folgende Softwarepakete haben wir im Rahmen unserer Forschungsarbeiten entwickelt:
pcaExplorer (https://bioconductor.org/packages/pcaExplorer/), “Interactive Visualization of RNA-seq Data Using a Principal Components Approach”, doi.org/10.1186/s12859-019-2879-1
ideal (https://bioconductor.org/packages/ideal/), “Interactive Differential Expression AnaLysis”, doi.org/10.1186/s12859-020-03819-5
GeneTonic (https://bioconductor.org/packages/GeneTonic/), “GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data”, doi.org/10.1186/s12859-021-04461-5
iSEE (https://bioconductor.org/packages/iSEE/), “iSEE: Interactive SummarizedExperiment Explorer”, doi.org/10.12688/f1000research.14966.1
iSEEu (https://bioconductor.org/packages/iSEEu/), “The iSEE Universe”
simrec (https://cran.r-project.org/package=simrec), “Simulating Recurrent Event Data with Hazard Functions Defined on a Total Time Scale”, doi.org/10.1186/s12874-015-0005-2
annoFuse (https://github.com/d3b-center/annoFuse), “annoFuse: an R Package to annotate, prioritize, and interactively explore putative oncogenic RNA fusions”, https://doi.org/10.1186/s12859-020-03922-7
TREND-DB (http://shiny.imbei.uni-mainz.de:3838/trend-db), “TREND-DB—a transcriptome-wide atlas of the dynamic landscape of alternative polyadenylation”, doi.org/10.1093/nar/gkaa722
netmeta (https://cran.r-project.org/package=netmeta), “A graphical tool for locating inconsistency in network meta-analyses”, https://doi.org/10.1186/1471-2288-13-35
SteppedPower (https://cran.r-project.org/package=SteppedPower), “Power Calculation for Stepped Wedge Designs”
Rhineland-Palatinate Mortality Monitoring, http://shiny.imbei.uni-mainz.de:3838/rlp_mm/