Recommended resources to learn bioinformatics

–ENTRY IN PROGRESS–

This is a list of some resources I find useful to conduct data analysis in Life Sciences Research, some of them more specific to the field of Genomics, Transcriptomics, and RNA-seq derived methods.

General programming

• Command Line Tools for Genomic Data Science by Liliana Florea. Great course to learn the most essential tools included in UNIX systems, unlocking a powerfull digital workbench.
• Algorithms for DNA Sequencing. A great course into key concepts of DNA sequence data analysis, which are useful as well for RNA-seq data analysis.
• The Data Scientist’s Toolbox. A course that introduces to a set of tools for scientific work in data analyis, centering in the programming language R, Rstudio, and Git’s version control. I highly recommend this course, especially if you plan to use R and Rstudio as your main workbench. Version control good practices will make your work more organized and keep track of changes to all your code; and Rmarkdown will show you that communicable and reproducible scientific results are possible and should be painless.

R

• R programming by Roger D. Peng. A nicely paced introductory course to R. After this course you will be able to use R for many basic data analyisi tasks
  • You can also find hiss ebooks at Leanpub, (Beginner lvl.).

• R for data science by Hadley Wickham & Garrett Grolemund. An amazing guide on how to explore, manipulate, program, model, and communicate for Data Science, (Intermediate lvl.).

• R packages by Hadley Wickham A great practical reference to creating R packages using the R package devtools. It has been the main source of help to develop my R packages.

• [Advanced R]

  Bioconductor

• Rsamtools
• GenomicAlignments
• txtools. This is a package I developed to retrieve count data from alignment files (BAM) to perform analysis that requires single-nucleotide resolution.

Bioinformatics

Just found this nice Introduction to Bioinformatics and Computational Biology. It is a collection of videos of lectures in bioinformatics and statistics for Harvard students. The lecturers are from top institutes (Harvard, Broad, etc) And it seems very well structured.

Unix

• Make: a minimal tutorial on make

Ebooks

Coursera guided projects?

• Using probability distributions for real world problems in R