Cancer In silico Drug Discovery (cidd) is a Python and R application that identifies candidate drug therapies using large cancer data sets. cidd allows for the creation of a tumor gene signature (or an expression profile) based on clinical phenotypes or tumor characteristics such as specific somatic mutations. cidd identifies candidate drugs that induce negatively correlated gene expression profiles when compared to provided tumor gene signatures. cidd also proposes cell-lines that most closely represent the tumors being studied to perform subsequent experimental drug screens on.
This C++ tool provides probabilities of allelic imbalance events (e.g., LOH and copy number aberrations) along genomes from next-generation sequencing data. haplohseq is especially designed for identifying events where only a small proportion of the cells in a sample harbor the allelic imbalance events.
This Python framework allows users to easily construct reproducible analysis pipelines.
This Python tool facilitates the download, pre-processing and local management of TCGA data. This tool helps bioinformaticists to easily locate and prepare TCGA data for downstream analysis using tools like R. tcga_util is a command-line tool that leverages firehose_get (from the Broad Institute) and is easy to integrate into analytical pipelines.