GSE152033 Processing Pipeline

RNA-Seq code_examples 8 steps

Publication

The sustained expression of Cas9 targeting toxic RNAs reverses disease phenotypes in mouse models of myotonic dystrophy type 1.

Nature biomedical engineering (2021) — PMID 32929188

Dataset

GSE152033

RNA-targeting Cas9 corrects molecular and physiological features in pre-clinical model of myotonic dystrophy type 1

Warning: Pipeline descriptions and code snippets may be inferred or AI-generated. Use them only as a starting point to guide analysis, and validate before use.

Processing Steps

Generate Jupyter Notebook
  1. 1

    RNA-seq data was aligned to the mouse mm10 genome build using Olego aligner, expression and alternative splicing were estimated using quantas as described below.

    RNA-seq
  2. 2

    Quantas software as described in Charizanis et al, 2012, Neuron, was used to estimate gene expression and alternative splicing.

  3. 3

    Olego aligned alignment files were used to count observed junction reads (for splicing) for each exon or RPKMs for each gene expression.

  4. 4

    Weighted number of exon or exon-junction fragments uniquely supporting the inclusion or skipping isoform of each cassette exon and a probability score was assigned to each isoform.

  5. 5

    A Fisher’s exact test was used to evaluate the statistical significance of splicing changes using both exon and exon-junction fragments, followed by Benjamini multiple testing correction to estimate the false discovery rate (FDR).

  6. 6

    In addition, inclusion or exclusion junction reads were used to calculate the proportional change of exon inclusion (dI).

  7. 7

    Forcalculate gene expression between various groups edgeR was used which is a part of the Quantas suite.

    edgeR
  8. 8

    See documentation at http://zhanglab.c2b2.columbia.edu/index.php/Quantas_Documentation.

Tools Used

RNA-seq
Raw Source Text 
RNA-seq data was aligned to the mouse mm10 genome build using Olego aligner, expression and alternative splicing were estimated using quantas as described below.
Quantas software as described in Charizanis et al, 2012, Neuron, was used to estimate gene expression and alternative splicing. Olego aligned alignment files were used to count observed junction reads (for splicing) for each exon or RPKMs for each gene expression. Weighted number of exon or exon-junction fragments uniquely supporting the inclusion or skipping isoform of each cassette exon and a probability score was assigned to each isoform. A Fisher’s exact test was used to evaluate the statistical significance of splicing changes using both exon and exon-junction fragments, followed by Benjamini multiple testing correction to estimate the false discovery rate (FDR). In addition, inclusion or exclusion junction reads were used to calculate the proportional change of exon inclusion (dI). Forcalculate  gene expression between various groups edgeR was used which is a part of the Quantas suite. See documentation at http://zhanglab.c2b2.columbia.edu/index.php/Quantas_Documentation.
Genome_build: mm10
Supplementary_files_format_and_content: xlsx
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