Case Study 1. exRNA-seq

Basic analyses for exRNA-seq

a) Background Introduction

• PPT: 0. Introduction of exRNA-seq.pdf (view on-line only, not downloadable)

• Teaching Video: Week V - Part II. 0. Intr to exRNA-seq.mov

b) Understand your data

Type of RNA-seq

• Default: (whole cell poly-A) RNA-seq (>200nt)

• Other types:

  • small RNA-seq (<50nt)

  • total RNA-seq (ribosome removed) (>200nt)

  • nonpolyA RNA-seq (ribosome removed) (>200nt)

• Different cell localizations:

  • nuc. (total)

  • chromosome (total)

  • cyto. (poly-A)

• Single cell RNA-seq

• exRNA-seq

  • cell free/MV/exosome/RNP

  • small/long

So what RNA-seq we are mapping and analyzing?

• Sequencing machine ?

• Single-strand V.S. Paired-end ?

• Strand specific ?

• Size selection ?

• Poly-A enriched or total (ribosome removed) ?

• Cellular localization ?

c) Organize your data

Data format:

• fasta

• fastaq

• gff/gtf

• bam

• bed

• bigwig

Shared dirs/data:

cd  #go to my home
ln -s /BioII/lulab_b/shared/genomes  .   #shared reference genome sequeunces and annotations
ln -s /BioII/lulab_b/shared/shared_scripts  .  #shared scripts in Lu Lab
ln -s /BioII/lulab_b/shared/projects/exRNA  shared_exRNA_projects   #shared projects' files

• ~/genomes/human_hg38

  • sequences/ #sequences of reference genome (fasta format)

  • index/ # indexed genome sequences

  • gtf/ #annotation of reference genome

Make your own project dir:

cd # go to my home
vim .bashrc # see my example in /home/john/.bashrc (and /home/john/shortcuts)
mkdir github

mkdir -p ~/projects/exRNA
cd ~/projects/exRNA

alias mkpr="mkdir -p {data/mapped,scripts,analysis}"  # you can put this in your ~/.bashrc
mkpr

d) Get the software ready

Install bioinformatics software in Linux (centos)

Video

@Youtube

@Bilibili

Other pipelines for RNA-seq analyses

We also recommend some other Tutorials/Pipelines you can learn from:

• RNA-seq analysis pipeline:: https://github.com/mgonzalezporta/TeachingMaterial

• lncRNA analysis pipeline: http://webhome.weizmann.ac.il/home/igoru/PLAR/

• ENCODE pipelines: https://www.encodeproject.org/pipelines/