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Setup RNA-Seq Pipeline from scratch: fastq (reads) to counts | Step-by-Step Tutorial 2 года назад


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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] #bioinformagician #bioinformatics #rnaseq #omics #rnastar #ensembl #affymetrix #microarray #affy #ncbi #genomics #beginners #tutorial #howto #research #biology #GEO #ngs

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