RNA-Seq Workflow

RNA-Seq with Bioconductor in R

Mary Piper

Bioinformatics Consultant and Trainer

RNA-Seq Workflow: RNA-Seq Experimental Design

  biological replicates

  • Technical replicates: Generally low technical variation, so unnecessary.

  • Biological replicates: Crucial to the success of RNA-Seq differential expression analyses. The more replicates the better, but at the very least have 3.

  • Batch effects: Avoid as much as possible and note down all experimental variables.

RNA-Seq with Bioconductor in R

workflow

RNA-Seq with Bioconductor in R

RNA-Seq prep

RNA-Seq with Bioconductor in R

QC

RNA-Seq with Bioconductor in R

RNA-Seq Workflow: Quality control

Sequence quality

RNA-Seq with Bioconductor in R

Alignment

RNA-Seq with Bioconductor in R

RNA-Seq Workflow: Alignment

Alignment to genome

RNA-Seq with Bioconductor in R

Quantitation

RNA-Seq with Bioconductor in R

RNA-Seq Workflow: Count matrix

wt_rawcounts <- read.csv("fibrosis_wt_rawcounts.csv")

Count matrix

RNA-Seq with Bioconductor in R

Full workflow

RNA-Seq with Bioconductor in R

example results

RNA-Seq with Bioconductor in R

Full workflow

RNA-Seq with Bioconductor in R

Back to you!

RNA-Seq with Bioconductor in R

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