Tools & Resources maintained by us
A web-based toolbox and resource for integrative analysis of the human neuronal genome, transcriptome, and more.
An R package and R shiny application for calculating sample size and power of bulk tissue and single-cell eQTL analysis.
One Tip Per Day
Learning notes for R, Unix, Perl, statistics, tools/resources, biology, etc. everything about Bioinformatics
Local mirror of UCSC Genome Browser
Bioinformatics primer articles
Nature Methods and Nature Biotechnology have this super-great monthly column in bioinformatics for years. For example, Nature Methods has both the “Points of Significance” covering topics in statistics and “Points of View” in data visualization. And Nature Biotechnology‘s Primer column covers a collection of topics in Bioinformatics, such as “What’s a hidden Markov model?“. We strongly recommend everyone who works in bioinformatics should read them. Here we compiled all the articles from above three columns together and made a PDF for you. Here is the link.
Tools & Resources recommended by us
- Applied Computational Genomics Course (by Dr. Aaron Quinlan et al.)
- Genomic Data Science Specialization (by Dr. Steven Salzberg et al.)
- Data Analysis for the Life Sciences (by Dr. Rafael Irizarry et al.)
- Genomics Data Analysis (by Dr. Rafael Irizarry et al.)
- Using Python for Research (by Dr. Jukka-Pekka “JP” Onnela)
- CRUK Bioinformatics Summer School 2020: Functional Genomics
- The Linux Foundation: Introduction to Linux (LFS101x): This an introduction course to the operating system (OS) Linux which is the core OS of bioinformatics and generally for data science.
- PH525x series – Biomedical Data Science (by Rafael Irizarry and Michael Love)
- R for Data Science, by Hadley Wickham & Garrett Grolemund, introduces the key tools for doing data science with R.
- ggplot2: elegant graphics for data analysis, by Hadley Wickham, shows you how to use ggplot2 to create graphics that help you understand your data.
- Advanced R, by Hadley Wickham, helps you master R as a programming language, teaching you what makes R tick.
- R packages, by Hadley Wickham, teaches good software engineering practices for R, using packages for bundling, documenting, and testing your code.
- Data Science at the Command Line, by Jeroen Janssens, demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist.
- Actually, most books on https://bookdown.org
- Genomics in Cloud: Using Docker, GATK, and WDL in Terra, by Brian D. O’Connor @ UCSC and Geraldine A. Van der Auwera @ Broad. Free access with Harvard ID.
- Educational papers in Bioinformatics from Nature Methods and Nature Biotechnology
- A tutorial on conducting GWAS: Quality control and statistical analysis
- Genetic Association Analysis
- A tutorial for Survival analysis in R
- Making Your First R Package
- Bioinformatics learning and data analysis tips and tricks (Other notes in Mikhail’s blog are highly recommended!)
- kent utilities: Over 400 genomics commands developed by UCSC Jim Kent etc.
- bedtools: A powerful toolset for genome arithmetic
- GNU tools, incl. coreutils, parallel, rsync etc.
- All about microRNA (https://www.gene-quantification.de/micro-rna-index.html)