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DESeq2 workflow tutorial | Differential Gene Expression Analysis | Bioinformatics 101

A walk-through of steps to perform differential gene expression analysis in a dataset with human airway smooth muscle cell lines to understand transcriptome changes in response to asthma medications. DESeq2 Vignette: http://bioconductor.org/packages/rele... Link to Code: Code to get data: https://github.com/kpatel427/YouTubeT... DESeq2 workflow: https://github.com/kpatel427/YouTubeT... Additional resources: 1. https://bioc.ism.ac.jp/packages/2.14/... 2. https://bioconductor.org/packages/rel... 3. https://lashlock.github.io/compbio/R_... 4. https://genviz.org/module-04-expressi... Chapters 0:00 Intro 0:45 Study design 2:30 Preparing counts data 5:41 Create DESeqDataSet (dds) object 9:51 Setting reference level 11:20 Run DESeq() 12:35 results after running DESeq() 14:14 Multiple testing correction (adjust p-values) 15:06 Exploring results 16:07 Contrasts 17:53 MA plot (Visualize DE genes) 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 #deseq2 #differentialgeneexpressionanalysis #rnaseq #fpkm #rpkm #tpm #normalization #rna #ncbi #genomics #beginners #tutorial #howto #omics #research #biology #ngs