Scroll down or click on any of these topics to see suggested resources for learning more:

• Biology
• Next Generation Sequencing
• RNA-seq
• Statistics
• Machine Learning
• R

Crash Course has several videos explaining biology concepts. We recommend the following videos in particular if you’d like to work on sequence analysis:

• Animal Cells
• Biological Molecules
• DNA structure
• Transcription and Translation

Some additional videos on genes and genomes:

• Harvard, “An Introduction to the Human Genome”
• Scientific American, “Genes vs. DNA vs. Chromosomes”

• Rafa Irizarry, “Intro to Next Generation Sequencing”
• Ben Langmead, “Intro to Alignment”
• Visualizing genomic data with IGV
• NCBI, “The FASTQ File Format”: A common, standard format for sequencing data

Sequencing Technologies:

The following videos give an overview of the technical process of different modern sequencing strategies

• Illumina: Short reads, high accuracy, high throughput
• Nanopore: Very long reads, lower accuracy, moderate throughput
• Sanger: Long reads, high accuracy, very low throughput

Introductory videos

• Rafa Irizarry, “Intro to RNA-seq” (5 min)
• Kasper Hansen, “Introduction to RNAseq” (1 hr 17 min)

Online texts

• RNA-seqlopedia: “The RNA-seqlopedia provides an overview of RNA-seq and of the choices necessary to carry out a successful RNA-seq experiment.” It provides a good background and overview but does not go into the practical details of how to do the various data analysis steps (what programs to use and how to use them).
• COMBINE-Australia, “RNAseq analysis in R“: Materials from a workshop on RNA-seq analysis in R.
• HarvardX, “Data Analysis for the Life Sciences Series“: A data-science heavy series of lessons on analyzing biological data, with an emphasis on gene expression. A good resource if you want to dive deeper into the statistics.

Videos

• StatQuest: A collection of videos explaining a variety of statistics concepts and methods.
• Rafa Irizarry, “Introduction to Statistics”

Online textbooks

• Modern Statistics for Modern Biology
• Statistical Modeling: A Fresh Approach

• The Elements of Statistical Learning
• Convolutional Neural Networks for Visual Recognition
• fast.ai
• Google AI

• R for Data Science “This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it.”
• swirl: “swirl teaches you R programming and data science interactively, at your own pace, and right in the R console!”
• DataCamp Introduction to R: “In this introduction to R, you will master the basics of this beautiful open source language, including factors, lists and data frames. With the knowledge gained in this course, you will be ready to undertake your first very own data analysis.”
• Chromebook Data Science: “Chromebook Data Science (CBDS) is a free, massive open online educational program offered through Leanpub to help anyone who can read, write, and use a computer to move into data science, the number one rated job.”