Integrating Multiple Modalities of High Throughput Assays Using Item Response Theory
Calculate the permuted latent trait by gene sampling
Calculate latent traits for a given response matrix and item parameter...
Ovarian Cancer Datasets
A wrapper that is able to dichotomize expression, methylation and CN d...
Dichotomizing copy number data based on segmented data (i.e. log2ratio...
Dichotomize the expression data given both tumor and normal samples.
Dichotomize the methylation data given both tumor and normal controls.
Fit IRT model on a single platform
The easyrun function for integrating multiple modalities of high throu...
The easyrun function for integrating multiple modalities of high throu...
Simulate binary response matrix according to 2-parameter Item Characte...
Provides a systematic framework for integrating multiple modalities of assays profiled on the same set of samples. The goal is to identify genes that are altered in cancer either marginally or consistently across different assays. The heterogeneity among different platforms and different samples are automatically adjusted so that the overall alteration magnitude can be accurately inferred. See Tong and Coombes (2012) <doi:10.1093/bioinformatics/bts561>.