I am a consultant for research in pharmaceutical translational medicine, with a heavy emphasis on genomics and bioinformatics. I'm cross-trained in immunology, oncology, bioinformatics, genomics, and chemistry. My training and experience have made able to integrate information and synthesize hypotheses and conclusions across diverse domains of science and medicine.
Below is a small collection of tools I've created to answer questions about cancer and immunology genomic studies, including the analysis of single-cell RNA information.
T2: a new browser for the 2018 release of TCGA (pan-cancer study group)
This tool captures and plots RNA, gene-level mutation events (.mut), position-specific mutations (.fmut), continuous and thresholded copy number estimates (.cnv and .cnc), signature projections, subtype classifications, purity estimates, and much more.
It also contains advanced captilities for adjusting for biases and covariates in multi-model TCGA data.
Partial correlations: a "cell of origin" data mining tool
In an environment of highly correlated data, where are the real correlations? This tool uses partial correlation theory to divine the cellular source of gene expression in tumors, despite the overall correlation of immune infiltrates (UCSC Toil RNA-seq).
Network relationships of genes across TCGA
The PLOS paper (referenced above) used signatures for immune cell types that were derived from a mutual-rank distance network across TCGA. In particular, we discovered the association of CCR8 with tumor Tregs using these networks. The AllNets application will let you interrogate these relationships across all of TCGA, or any specific tumor type.