marislab's repositories
create-pptc-pdx-oncoprints
As part of an overall strategy for improving therapies for childhood cancers, the PPTC seeks to develop models for the types of tumors that will be encountered in early phase clinical testing by establishing patient derived xenografts (PDXs) from high-risk childhood cancers refractory to current standard of care treatments. Genomic profiling of these models is required to enable PPTC investigators to develop robust "responder hypotheses" when drug activity is observed. With funding provided by Alex's Lemonade Stand Foundation, we genomically characterize a major subset of 286 PDX models. We use whole exome sequencing, transcriptome sequencing, and SNPArray to characterize the tumor models. The focus on DNA and RNA sequencing data mirrors the current standard practice in most clinical diagnostics lab that use these technologies to detect the spectrum of targetable mutations, gene amplifications, and gene fusion events relevant to preclinical drug development.
pdx-classification
Applying Machine Learning Ras, NF1, and TP53 Classifiers to PDX model gene expression
pptx-pdx-fusion-analysis
Fusion pipeline and figures
create-pptc-pdx-pie
Pie chart for Figure 1 of Manuscript
mosse-lab-tools
Various QoL tools and script snippets to aid researchers in the Mosse lab
gmkf-nbl-fusion-analysis
Fusion analysis for GMKF Neuroblastoma
immunoprofile_shinyapp
Shiny app for immunoprofiling across pediatric and adult tumors
pptc-pdx-copy-number-and-SVs
Indel and Breakpoints plots
pptc-pdx-ethnicity-inference
Ethnicity inference for Pediatric Preclinical Testing Consortium (PPTC) patient-derived xenograft models
sCRAP_CommandLine
selective Cross Reactive Antigen Presentation (command line version)
tad_pathways_pipeline
Pipeline to implement a "TAD_Pathways" analysis. Discover candidate genes based on association signals in TADs