GSE106493 Processing Pipeline

Publication

iScience (2024) — PMID 38495826

Dataset

Live-cell mapping of organelle-associated RNAs via proximity biotinylation combined with protein-RNA crosslinking

1. 1

   Reads were mapped to human genome using TopHat v2.1.1 with the flags, "--no-coverage-search" and "--GTF gencode.v19.annotation.gtf".

   TopHat v2.1.1 GitHub

   $ Bash example

   # Install TopHat (example using conda)
   # conda install -c bioconda tophat=2.1.1
   
   # Define variables for reference files and input/output
   # Replace with actual paths to your reference genome index and GTF file
   GENOME_INDEX="/path/to/human_genome/hg19/bowtie2_index/hg19" # TopHat uses Bowtie2 index
   GTF_FILE="/path/to/gencode.v19.annotation.gtf"
   READS_FILE="reads.fastq" # Replace with your input FASTQ file(s)
   OUTPUT_DIR="tophat_output"
   
   # Create output directory if it doesn't exist
   mkdir -p "${OUTPUT_DIR}"
   
   # Run TopHat mapping
   tophat2 \
     --no-coverage-search \
     --GTF "${GTF_FILE}" \
     -o "${OUTPUT_DIR}" \
     "${GENOME_INDEX}" \
     "${READS_FILE}"

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2. 2

   Gene expression was quantified against the Gencode v19 reference transcriptome (gencode.v19.annotation.gtf, genecodegenes.org) with Cufflinks v2.2.1.

   Cufflinks v2.2.1 GitHub

   $ Bash example

   # Install Cufflinks (example using conda)
   # conda install -c bioconda cufflinks=2.2.1
   
   # Define reference transcriptome
   GENCODE_GTF="gencode.v19.annotation.gtf" # Source: genecodegenes.org
   
   # Assume input BAM file and output directory
   INPUT_BAM="aligned_reads.bam" # Placeholder for your aligned RNA-seq reads
   OUTPUT_DIR="cufflinks_output"
   
   # Create output directory if it doesn't exist
   mkdir -p "${OUTPUT_DIR}"
   
   # Run Cufflinks for gene expression quantification
   # -o: output directory
   # -g: reference annotation GTF file
   cufflinks -o "${OUTPUT_DIR}" -g "${GENCODE_GTF}" "${INPUT_BAM}"

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3. 3

   The statistical significance of differential expression was assessed using CuffDiff2, with the flags, "--dispersion-method per-condition" and "--seed 42".

   CuffDiff2 v2.2.1 GitHub

   $ Bash example

   # Install Cufflinks (which includes cuffdiff2)
   # conda install -c bioconda cufflinks=2.2.1
   
   # Define input files and output directory
   GTF_FILE="path/to/annotation.gtf" # Placeholder: e.g., Gencode, Ensembl GTF file
   CONDITION_A_BAMS="path/to/conditionA_rep1.bam,path/to/conditionA_rep2.bam" # Placeholder: Comma-separated BAM files for condition A replicates
   CONDITION_B_BAMS="path/to/conditionB_rep1.bam,path/to/conditionB_rep2.bam" # Placeholder: Comma-separated BAM files for condition B replicates
   OUTPUT_DIR="cuffdiff_output"
   
   # Create output directory if it doesn't exist
   mkdir -p "${OUTPUT_DIR}"
   
   # Run CuffDiff2 for differential expression analysis
   cuffdiff2 \
     --dispersion-method per-condition \
     --seed 42 \
     -o "${OUTPUT_DIR}" \
     "${GTF_FILE}" \
     "${CONDITION_A_BAMS}" \
     "${CONDITION_B_BAMS}"

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4. 4

   ROC analysis was perfomed in Microsoft Excel, using true positive and false positive gene lists culled from the literature.

   Microsoft Excel GitHub

Tools Used