Large-scale bioinformatics for Immuno-Oncology http://gtpb.igc.gulbenkian.pt/bicourses/2017/IO17/index.html
Informatics for cancer immunotherapy https://www.annalsofoncology.org/article/S0923-7534(19)54150-3/fulltext
IOBR: Immuno-Oncology Biological Research. R package to perform comprehensive analysis of tumor microenvironment and signatures for immuno-oncology. https://github.com/IOBR/IOBR
Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology https://academic.oup.com/bioinformatics/article/35/14/i436/5529146
Bioinformatics for precision oncology https://academic.oup.com/bib/article/20/3/778/4758621
Bioconductor. Packages found under ImmunoOncology: https://www.bioconductor.org/packages/release/BiocViews.html#___ImmunoOncology
OmniPath: intra- & intercellular signaling knowledge https://omnipathdb.org/
GTPB (Gulbenkian Training Programme in Bioinformatics) http://gtpb.igc.gulbenkian.pt/bicourses/Course_materials.html
YeoLab / single-cell-bioinformatics https://github.com/YeoLab/single-cell-bioinformatics
Data Carpentry - Genomics https://datacarpentry.org/lessons/#genomics-workshop
Applied Bioinformatics - The Scripps Research Institute ( SuLab ) https://github.com/SuLab/Applied-Bioinformatics
https://github.com/kipkurui/Python4Bioinformatics
https://github.com/guma44/GEOparse https://github.com/czbiohub/learn-bioinformatics
Shiny-iAtlas is an interactive web portal that provides multiple analysis modules to visualize and explore immune response characterizations across cancer types. https://isb-cgc.shinyapps.io/shiny-iatlas/
EstimAte Systems ImmunE Response (EaSIeR) https://github.com/olapuentesantana/easier_manuscript
https://www.nature.com/articles/s41568-020-0290-x
TCGA Cancers Selected for Study https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga/studied-cancers
Analyzing and visualizing TCGA data https://bioconductor.org/packages/devel/bioc/vignettes/TCGAbiolinks/inst/doc/analysis.html#TCGAanalyze_DEA__TCGAanalyze_LevelTab:_Differential_expression_analysis_(DEA)
Computational Genomics with R https://compgenomr.github.io/book/
Liquid Brain https://www.youtube.com/channel/UCrpq9hzMQSq0ldVcXlLgpvQ
Survival Analysis on Cancer data | RStudio Tutorial https://www.youtube.com/watch?v=oyAn5B-vLus https://github.com/brandonyph/Survival-Analysis-demo
https://bbisr.shinyapps.winship.emory.edu/SurvivalGenie/
https://github.com/zwj-tina/GEPIA2021
The Python package gepia http://gepia2.cancer-pku.cn/#api
Introduction to R programming for data science (Dr. Francesca Finotello) https://github.com/FFinotello/Rcourse
The Easiest Way to Create an Interactive Dashboard in Python Turn Pandas pipelines into a dashboard using hvPlot .interactive https://towardsdatascience.com/the-easiest-way-to-create-an-interactive-dashboard-in-python-77440f2511d1
Single Sample Gene Enrichment Analysis Taskforce https://enrichmentmap.readthedocs.io/en/docs-2.2/Tutorial_GSEA.html
Single Sample Gene Enrichment Analysis https://ayguno.github.io/curious/portfolio/GSEAtaskforce.html
https://www.gsea-msigdb.org/gsea/index.jsp
SSGSEA https://rpubs.com/pranali018/SSGSEA
Using RNA-seq Datasets with GSEA https://software.broadinstitute.org/cancer/software/gsea/wiki/index.php/Using_RNA-seq_Datasets_with_GSEA
Converting Expression Data into a GenePattern input file format https://www.youtube.com/watch?v=_zpH-DgE33U&ab_channel=GenePattern
GSVA: gene set variation analysis http://bioconductor.org/packages/release/bioc/vignettes/GSVA/inst/doc/GSVA.html http://bioconductor.org/packages/release/bioc/html/GSVA.html https://rdrr.io/bioc/GSVA/
Overall Survival Curves for TCGA and Tothill by RD Status https://bioinformatics.mdanderson.org/Supplements/ResidualDisease/Reports/osCurves.html
TCGAportal http://tumorsurvival.org/index.html