RESOURCES WE LOVE
Disclaimer: We do not own or have any relationships with these websites and links. They are simply things we use regularly in our lab that we find useful.
GBM & Cancer Databases
View expression, survival, and correlation data from GBM TCGA.
View protein interactions networks, and get a GO analysis of proteins
View cell/tissue protein levels in cancer and normal tissues.
View pathway analysis of protein set in various different datasets.
A rich viewer for TCGA datasets across all cancer types, with clinical tracks.
Collects DNA mutations, annotations, and key genes across cancers.
A viewer than can create beautiful visualizations of various tumor datasets.
A database where various cancer cell lines’ expression info is stored.
A database that provides in situ hybridization and molecular information.
A database of many cancers with multiple levels of info.
A portal by NCI for accessing and displaying TCGA data.
A cancer patient database providing long-term outcomes
Bioinformatics Analysis Algorithms
For developing coding skills, we recommend codeacademy or datacamp.
For coding environments, Rstudio and Anaconda are useful for R and Python respectively.
For quality analysis of sequencing data, we recommend using FastQC or MultiQC.
For bioinformatic analysis, we have linked some useful pipelines and modules below.
An algorithm used for analysis of RNASeq data for expression
A full pipeline that allows analysis of single cell drop seq datasets
A pipeline that performs CRISPR screening analysis for gene identification
A pipeline for peak calling for ChIP Seq datasets
A software that can perform full annotations of ChIP Seq data
A package for analysis of CRISPR data that backs CRISPRAnalyzR
PDX Cell Lines
Mayo clinic has a large repository of GBM PDX cell lines, along with characterization information for all lines.
