Free Resources for Teaching Yourself to Analyze Next Gen Sequencing Data

If you’re new to next gen sequencing, figuring out what to do with your results can be a daunting process. Luckily, you’re not alone—plenty of people have been in your shoes, and there is tons of information about data analysis out there. Here are some free resources you can use to get up to speed on data analysis.

Take a Class Online

EdX: Data Analysis for Genomics

This is an 8-week crash course on the analysis of genomic data. It will familiarize you with R, Bioconductor, github, and how to analyze various types of genomic data. The book that goes along with the course is also freely accessible.

Reluctant to commit to a whole class? You may want to check out the Case Studies on EdX. There is one on RNA-seq data analysis and another on ChIP-seq data analysis.

Note: Even if a class is not in progress, you can access archived courses to work through the materials.

Take a Class In-Person

Is taking a class in-person more your speed? You may want to check out the Summer Institute in Statistical Genetics, held every summer at the University of Washington. The institute is made up of 2.5 day modules (most people take a few), and they offer the chance to learn from leaders in the field. Although technically these modules are not free, the institute offers generous scholarships to assist trainees that require funding assistance.

Relevant classes offered in the past include Gene Expression Profiling, Elements of R for Genetics and Bioinformatics, Advanced R Programming for Bioinformatics, Introduction to Metagenomic Data Analysis, and Pathway & Network Analysis for Omics Data.

You may also want to check out your own organization’s offerings. Courses, workshops, and working groups are all great places to learn about data analysis.

Read All About It

There are many helpful articles on the Internet for anyone interested in next gen sequencing. Here is just a smattering to get you started:

The Hitchhiker’s Guide to Next Generation Sequencing offers a fun overview of the history and uses of next gen sequencing.

There are also plenty of journal articles that can help walk you through your options, including:

• An overview of the analysis of next generation sequencing data by Gogol-Döring and Chen.
• A survey of tools for variant analysis of next-generation genome sequencing data by Pabinger et al.
• A whole supplement on next-generation sequencing data analysis in Nature Methods.

Want to delve a little deeper? There are entire books devoted to analyzing genomic data using R and RNA-seq analysis.

Ask Somebody

As you get started, you will often find that you have very specific questions, often having to do with coding or data manipulation. It’s easy to get stuck. What do you do in this situation? If you can’t think of any colleagues to approach for help, consider searching or posting in BioStars, a forum for biologists to ask one another questions. Chances are that someone out there has already encountered your problem and has a solution.

A Skill Well Worth It

Next gen data analysis is a skill that is increasingly in demand, so learning how to analyze these data is likely to be a worthwhile investment. We hope these resources prove helpful, but we would love to hear about any additional aids you have found useful for learning to perform next gen data analysis.

In addition, if your forays into data analysis have convinced you that you need to learn to code, check out our article on resources for leaning an NGS programming language.