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DISCOVER
DISCOVER co-occurrence and mutual exclusivity analysis for cancer genomics dataflexgsea-r
Flexible gene set enrichment analysisPRECISE
TRANSACT_manuscript
Scripts supporting TRANSACT manuscriptsobolev_alignment
Sobolev alignment of deep probabilistic models for comparing single cell profilesimfusion
Tool for identifying transposon insertions and their effects from RNA-seq data.MixedIC50
A non-linear mixed effects model for estimating compound sensitivityimagene-analysis
Radiogenomic analysis of breast cancer by linking MRI phenotypes with tumor gene expressionTANDEM
A two-stage regression method that can be used when various input data types are correlated, for example gene expression and methylation in drug response prediction. In the first stage it uses the upstream features (such as methylation) to predict the response variable (such as drug response), and in the second stage it uses the downstream features (such as gene expression) to predict the residuals of the first stage. In our manuscript (Aben et al., 2016), we show that using TANDEM prevents the model from being dominated by gene expression and that the features selected by TANDEM are more interpretable.RUBIC
RUBIC detects recurrent copy number aberrations.TRANSACT
Python implementation of TRANSACT, a tool to transfer non-linear predictors of drug response from model systems to tumors.dids
R package for the Detection of Imbalanced Differential Signal (DIDS) algorithm.multitask_vi
The Multitask Variable Importance (Multitask VI) is a modified version of the permuted variable importance score for Random Forests. Essentially, for a Random Forest trained simultaneously for multiple response vectors, it allows the inference of variable importance scores per variable and per task.iTOP
Infers a topology of relationships between different datasets, such as multi-omics and phenotypic data recorded on the same samples.ppbc
Post-partum breast cancerfuncsfa
Functional Sparse-Factor Analysiscimpl
Common Insertion Site Mapping Platform implemented as an R package for statistical analysis of retroviral insertional mutagenesis screens.won-parafac
Weighted orthogonal non-negative (WON) parallel factor analsyis (PARAFAC)Love Open Source and this site? Check out how you can help us