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Bioinformatics: RNA-Seq/Differential expression in Bash & R!

Bioinformatics: RNA-Seq/Differential expression in Bash & R!

Carry out a RNA-seq pipeline in the command line in Colab and use R to carry out differential expression & GO analysis!

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RNA-Seq (short for "RNA sequencing") is a powerful technique used in bioinformatics to study gene expression. It involves sequencing the RNA molecules present in a sample, which can provide insights into which genes are active in a particular tissue or cell type.

Differential expression is the study of how gene expression changes between two or more conditions. For example, researchers may be interested in comparing gene expression in cancerous versus healthy tissue, or in understanding how gene expression changes in response to a particular drug or treatment.

RNA-Seq and differential expression analysis can be performed using a combination of bash and R scripts. Bash is a Unix shell and command language that can be used to automate tasks and run programs on a computer. R is a programming language and software environment for statistical computing and graphics.

To perform RNA-Seq and differential expression analysis, researchers typically follow a series of steps including:

  1. Obtain RNA samples from the tissues or cells of interest
  2. Prepare the samples for sequencing by extracting and purifying the RNA
  3. Sequence the RNA using an NGS platform
  4. Process and align the raw sequencing data to a reference genome
  5. Perform quality control checks on the data
  6. Identify differentially expressed genes between the conditions of interest
  7. Visualize and interpret the results

By combining bash and R scripts, researchers can automate and streamline these steps, making it easier to perform large-scale RNA-Seq and differential expression analyses.

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