Setup RNA-Seq Pipeline from scratch: fastq (reads) to counts | Step-by-Step Tutorial
This is a detailed workflow tutorial of how to process bulk RNA-Seq reads (fastq) and generate counts matrix which can be used for various downstream analysis. In this video, I walk through setting up a pipeline in bash (linux) and perform steps to process RNA-Seq data including -
• Quality control (fastQC)
• Trimming (Trimmomatic)
• Alignment (HISAT2)
• Quantification (featureCounts)
In addition I also talk about run times, memory requirements and aligner accuracies of various aligners. I hope you find this video helpful! Leave your thoughts in the comment section below!
Link to code:
https://github.com/kpatel427/YouTubeT...
Link to data:
▸ https://drive.google.com/file/d/1DGHj...
Linux Basics
▸ https://ubuntu.com/tutorials/command-...
▸ https://xie186.github.io/Novice2Exper...
▸ https://hackr.io/blog/basic-linux-com...
To Trim or to not Trim?
▸ https://www.ncbi.nlm.nih.gov/pmc/arti...
Strandedness
▸ https://bmcgenomics.biomedcentral.com...
▸ https://chipster.csc.fi/manual/librar...
▸ http://rseqc.sourceforge.net/#infer-e...
Chapters:
0:00 Intro
1:11 - Applications of RNA-Seq data
2:41 Schematic detailed workflow
3:49 What are splice-aware aligners?
5:59 Workflow for this tutorial
6:31 Comparison of run times, memory usage and aligner accuracies for various aligners
8:27 Which aligner should I choose?
9:05 Pre-requistes to build this pipeline (things that will not be covered in this video)
9:40 Set-up before building the pipeline
10:37 Some good practices while building a pipeline
11:21 Quality control: FastQC
15:27 To trim or to not trim?
15:58 Trimming reads: Trimmomatic
19:18 Align reads: HISAT2
24:20 Read quantification: featureCounts
Show your support and encouragement by buying me a coffee:
https://www.buymeacoffee.com/bioinfor...
To get in touch:
Website: https://bioinformagician.org/
Github: https://github.com/kpatel427
Email: [email protected]
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