This repository keeps track of several useful bioinformatics resources.
Several Useful Links
- Explore a variety of example analyses like clustering, differential expression, pathway analysis, etc., for refine.bio datasets: https://alexslemonade.github.io/refinebio-examples/
- A tutorial to help scientists design their projects and analyze their data: https://bioinformaticsworkbook.org/#gsc.tab=0
- TCGA Data Analysis: https://rpubs.com/tiagochst/TCGAworkshop4
- Analysis of Cancer Genome Atlas in R: https://costalab.ukaachen.de/open_data/Bioinformatics_Analysis_in_R_2019/BIAR_D3/handout.html
- TCGA: https://benbermanlab.com/assets/code/Workshop%20-%20TCGA%20data%20analysis.html
- Using the GEOquery Package: https://www.bioconductor.org/packages/devel/bioc/vignettes/GEOquery/inst/doc/GEOquery.html#getting-all-series-records-for-a-given-platform
- GitHub Bioinfo_Trianing: https://github.com/Bioinformatics-Research-Network/training-requirements
- Introduction to Linux for bioinformatics: https://wiki.bits.vib.be/index.php/Introduction_to_Linux_for_bioinformatics
- Bioinformatics in the terminal-Tips and tricks to make your life easier: https://www.youtube.com/watch?v=m9gJD64Hsc8
- Getting started in linux-Bioinformatics: https://omicstutorials.com/getting-started-in-linux-bioinformatics/
- Setting Up Your First Bioinformatics Computer: https://www.youtube.com/channel/UCYDIJ7Mlsdmotfd3uM6lh8Q/videos
- http://omgenomics.com/
- Getting started in Bioinformatics-A step-by-step guide: https://medium.com/@rebelCoderBio/getting-started-in-bioinformatics-a-step-by-step-guide-6337843a03b5
- RNA-seq analysis in R: https://combine-australia.github.io/RNAseq-R/06-rnaseq-day1.html#Data_files_and_Resources
- VIB Bioinformatics Core Wiki: https://wiki.bits.vib.be/index.php/Category:Training
- https://www.google.com/search?q=how+to+identify+the+head+and+neck++cancer+normal+data+r+scripts&ei=N6VfYsPmKZ6VseMPyNej2AE&ved=0ahUKEwiD3pP2_qH3AhWeSmwGHcjrCBsQ4dUDCA4&uact=5&oq=how+to+identify+the+head+and+neck++cancer+normal+data+r+scripts&gs_lcp=Cgdnd3Mtd2l6EAM6BwgAEEcQsAM6BAghEApKBAhBGABKBAhGGABQywJYvxdgjBtoAXABeACAAZkBiAHGDpIBBDAuMTWYAQCgAQHIAQjAAQE&sclient=gws-wiz
- Differential gene expression (DGE) analysis Materials for short, half-day workshops: https://hbctraining.github.io/Training
- modules/planning_successful_rnaseq/lessons/sample_level_QC.html
- https://genviz.org/module-04-expression/0004/02/01/DifferentialExpression/
- https://www.melbournebioinformatics.org.au/tutorials/tutorials/rna_seq_dge_in_r/rna_seq_r/
- https://angus.readthedocs.io/en/2019/diff-ex-and-viz.html#why-do-we-need-to-normalize-and-transform-read-counts
- https://www.bioconductor.org/packages/devel/workflows/vignettes/rnaseqGene/inst/doc/rnaseqGene.html
- https://www.bioconductor.org/packages/release/workflows/vignettes/TCGAWorkflow/inst/doc/TCGAWorkflow.html
- Bioinformatics Coach: https://www.youtube.com/channel/UCOJM9xzqDc6-43j2x_vXqCQ/playlists
- Introduction to gene expression microarray analysis in R and Bioconductor: https://gtk-teaching.github.io/Microarrays-R/
- https://www.bioconductor.org/packages/devel/workflows/vignettes/maEndToEnd/inst/doc/MA-Workflow.html#1_Introduction
- https://www.biostars.org/p/53870/
- https://www.biostars.org/p/224904/
- Network analysis of TCGA and GTEx gene expression datasets for identification of trait-associated biomarkers in human cancer: https://star-protocols.cell.com/protocols/1425
- https://www.frontiersin.org/articles/10.3389/fgene.2021.663787/full
- https://www.spandidos-publications.com/10.3892/mco.2018.1728