Lu Lab Docs
Edit

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:

  • ~/genomes/human_hg38

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

    • index/ # indexed genome sequences

    • gtf/ #annotation of reference genome

Make your own project dir:

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:

Last updated