Regulated Cell Death

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This is a collection of analysis scripts and notebooks related to regulated cell death, as part of the "Investigating regulated necrotic cell death in colorectal cancer using a multi-omics approach" project funded by the Department of Science and Technology – Philippine Council for Health Research and Development (DOST-PCHRD).

For more details and instructions on setting up dependencies, refer to https://github.com/bioinfodlsu/regulated-cell-death-playground


Analysis Description Results Code
1 Gene Expression Analysis
Human Dermal Fibroblasts, Neonatal (HDFn)
GSE32581
Necroptosis, Ferroptosis & Pyroptosis
  1. Download the following RNA-seq data from GSE32581: GSM807459.
    • The normalized count matrices are part of the user-submitted data (the authors reported performing average normalization).
  2. Download RCD gene sets for necroptosis, ferroptosis, and pyroptosis from RCDdb.
  3. For each RCD type:
    • Plot the normalized expression data per RCD-related gene for each RCD type.
Results Code
2 Gene Expression Analysis
Human Dermal Fibroblasts, Neonatal (HDFn)
GSE84144
Necroptosis, Ferroptosis & Pyroptosis
  1. Download the following RNA-seq data from GSE84144: GSM2227697, GSM2227698, and GSM2227699.
    • The normalized count matrices are part of the user-submitted data (the authors reported performing quantile normalization).
  2. Download RCD gene sets for necroptosis, ferroptosis, and pyroptosis from RCDdb.
  3. For each RCD type:
    • Plot the normalized expression data per RCD-related gene for each RCD type.
Results Code
3 Gene Expression Analysis
Fetal Colon Cell Line (FHC)
GSE232211
Necroptosis, Ferroptosis & Pyroptosis
  1. Download the following RNA-seq data from GSE232211: GSM7320966, GSM7320967, and GSM7320968.
  2. Download RCD gene sets for necroptosis, ferroptosis, and pyroptosis from RCDdb.
  3. For each RCD type:
    • Plot the TPM value per RCD-related gene for each RCD type.
Results Code
Analysis Description Results Code
1 Exploratory Data Analysis
  1. Download TPM data from the Genotype-Tissue Expression (GTEx) Portal.
  2. Filter data to include to those from colon tissues.
  3. Download RCD gene sets from the Human MSigDB Collections:
  4. Plot the median TPM value per RCD-related gene for each RCD type.
Results Code
2 Differential Gene Expression Analysis
Colorectal Cancer
Necroptosis, Ferroptosis & Pyroptosis
  1. Download RNA-seq data from The Cancer Genome Atlas (TCGA).
  2. Filter data to include normal and malignant pairs from TCGA-COAD.
  3. Download RCD gene sets from the Human MSigDB Collections:
  4. For each RCD type:
    • Filter the count matrix to include only genes related to the RCD type of interest.
    • Perform differential gene expression analysis using DESeq2.
Results Code
3 Differential miRNA Expression Analysis
Colorectal Cancer
Necroptosis, Ferroptosis & Pyroptosis
  1. Download miRNA expression data from The Cancer Genome Atlas (TCGA).
  2. Filter data to include normal and malignant pairs from TCGA-COAD.
  3. Download RCD gene sets from the Human MSigDB Collections:
  4. Map miRNAs to target mRNAs using miRDB.
  5. For each RCD type:
    • Filter the count matrix to include only miRNAs that target genes related to the RCD type of interest.
    • Perform differential gene expression analysis using DESeq2.
Results Code
4 Differential Gene Expression Analysis
Pan-Cancer (Partial)
Necroptosis, Ferroptosis & Pyroptosis
  1. Download RNA-seq data from The Cancer Genome Atlas (TCGA).
  2. Filter data to include normal and malignant pairs from multiple TCGA studies.
  3. Download RCD gene sets from the Human MSigDB Collections:
  4. For each RCD type:
    • Filter the count matrix to include only genes related to the RCD type of interest.
    • Perform differential gene expression analysis using DESeq2.
Results Code
5 Differential Gene Expression Analysis
Pan-Cancer (Partial)
Multiple RCD Types (Including NETosis, Cuproptosis, etc.)
  1. Download RNA-seq data from The Cancer Genome Atlas (TCGA).
  2. Filter data to include normal and malignant pairs from multiple TCGA studies.
  3. Download RCD gene sets for all the RCD types in RCDdb.
  4. For each RCD type:
    • Filter the count matrix to include only genes related to the RCD type of interest.
    • Perform differential gene expression analysis using DESeq2.
Results Code
6 Differential Gene Expression Analysis
Pan-Cancer (Complete)
Necroptosis, Ferroptosis & Pyroptosis
Unique Genes
  1. Download RNA-seq data from The Cancer Genome Atlas (TCGA).
  2. Filter data to include normal and malignant pairs from all TCGA studies in this list.
  3. Download RCD gene sets for necroptosis, ferroptosis, and pyroptosis in RCDdb.
  4. For each RCD type:
    • Get only the genes unique to the RCD type of interest.
    • Filter the count matrix to include only genes related to the RCD type of interest.
    • Perform differential gene expression analysis using DESeq2.
Results Code
7 Survival Analysis
Colorectal Cancer
Necroptosis, Ferroptosis & Pyroptosis
Unique Genes
Tumor Samples
  1. Download RNA-seq and clinical data from The Cancer Genome Atlas (TCGA).
  2. Filter data to include normal and malignant pairs from TCGA-COAD.
  3. Download RCD gene sets for necroptosis, ferroptosis, and pyroptosis in RCDdb.
  4. For each RCD type:
    • Get only the genes unique to the RCD type of interest.
    • Filter the count matrix to include only genes related to the RCD type of interest.
    • Perform variance-stabilizing transformation on the counts, and use these variance-stabilized counts for the survival analysis.
    • For each gene:
      • Divide the patient cohort into patients with low versus high expression of the gene of interest.
        • "Low" is defined as lower than Q1 while "high" is defined as higher than Q3 of the gene expression of the tumor samples.
        • The gene expression data considered are only those from the tumor samples.
      • Plot the Kaplan-Meier survival curves.
      • Test for significant difference between these curves using the Gρ family of Harrington and Fleming tests.
      • Perform Cox proportional hazards regression analysis.
Necroptosis
Ferroptosis
Pyroptosis 		Necroptosis
Ferroptosis
Pyroptosis
8 Survival Analysis
Colorectal Cancer
Necroptosis, Ferroptosis & Pyroptosis
Unique Genes
Normal Samples
  1. Download RNA-seq and clinical data from The Cancer Genome Atlas (TCGA).
  2. Filter data to include normal and malignant pairs from TCGA-COAD.
  3. Download RCD gene sets for necroptosis, ferroptosis, and pyroptosis in RCDdb.
  4. For each RCD type:
    • Get only the genes unique to the RCD type of interest.
    • Filter the count matrix to include only genes related to the RCD type of interest.
    • Perform variance-stabilizing transformation on the counts, and use these variance-stabilized counts for the survival analysis.
    • For each gene:
      • Divide the patient cohort into patients with low versus high expression of the gene of interest.
        • "Low" is defined as lower than Q1 while "high" is defined as higher than Q3 of the gene expression of the normal samples.
        • The gene expression data considered are only those from the normal samples.
      • Plot the Kaplan-Meier survival curves.
      • Test for significant difference between these curves using the Gρ family of Harrington and Fleming tests.
      • Perform Cox proportional hazards regression analysis.
Necroptosis
Ferroptosis
Pyroptosis 		Necroptosis
Ferroptosis
Pyroptosis
9 Survival Analysis
Colorectal Cancer
Necroptosis, Ferroptosis & Pyroptosis
Unique Genes
Log Fold Change
  1. Download RNA-seq and clinical data from The Cancer Genome Atlas (TCGA).
  2. Filter data to include normal and malignant pairs from TCGA-COAD.
  3. Download RCD gene sets for necroptosis, ferroptosis, and pyroptosis in RCDdb.
  4. For each RCD type:
    • Get only the genes unique to the RCD type of interest.
    • Filter the count matrix to include only genes related to the RCD type of interest.
    • For each gene:
      • Divide the patient cohort into patients with low versus high log fold change of the gene of interest.
        • If the absolute value of the log fold change between the gene expression in tumor samples and the gene expression in normal samples is less than 1.5, then it is classified as "low." Otherwise, it is classified as "high."
      • Plot the Kaplan-Meier survival curves.
      • Test for significant difference between these curves using the Gρ family of Harrington and Fleming tests.
      • Perform Cox proportional hazards regression analysis.
Necroptosis
Ferroptosis
Pyroptosis 		Necroptosis
Ferroptosis
Pyroptosis