RNA biology 2017


ile>Dataset: K562 RNAseq from the Encode project. In this experiment, poly-A RNAs were sequenced using paired-end protocol.


Session 1: Quality Control

When you get your sequences back from a sequencing facility, it’s important to check that they are high quality (garbage in, garbage out). In this tutorial, we’ll use software called FastQC which checks whether a set of sequence reads in a .fastq file exhibit any unusual qualities.

FastQC consists of a single simple command line. Once the prompt is localized in the proper folder (use the command cd), we just need to execute the software with the file to analyze as an argument:

>fastqc k562-rnaseq.fastq

FastQC can be also used on any computer using a graphical interface (JAVA is required).

To run the software, double-click on the FastQC icon, then go to File>Open.

FastQC returns as results a web page describing several quality features, here are example of good and bad quality datasets:

 

Session 2: Alignment

 

Session 3: Gene Expression Quantification

Session 4: Gene differentially expressed

Session 5: Visualization