GSE234078 Processing Pipeline

Publication

Nature communications (2023) — PMID 37673892

Dataset

A super-enhancer regulated RNA-binding protein cascade drives pancreatic cancer

1. 1

   For human samples, reads were aligned using Bowtie2 to GRCh37 and SE peaks were called using HOMER v4.11.1 default settings (-style super, Fold change >4, p-value <0.0001).

   Bowtie2 vNot specified GitHub

   $ Bash example

   # --- Installation (commented out) ---
   # conda install -c bioconda bowtie2 samtools homer
   
   # --- Reference Data Setup ---
   # Download GRCh37 (hg19) primary assembly FASTA
   # wget -O GRCh37.fa.gz ftp://ftp.ensembl.org/pub/release-75/fasta/homo_sapiens/dna/Homo_sapiens.GRCh37.75.dna.primary_assembly.fa.gz
   # gunzip GRCh37.fa.gz
   GENOME_FASTA="GRCh37.fa" # Path to your unzipped GRCh37 FASTA file
   
   # Build Bowtie2 index for GRCh37
   BOWTIE2_INDEX_PREFIX="GRCh37_index" # Prefix for Bowtie2 index files
   # bowtie2-build "${GENOME_FASTA}" "${BOWTIE2_INDEX_PREFIX}"
   
   # Configure HOMER genome (hg19 is GRCh37)
   HOMER_GENOME="hg19" # HOMER uses UCSC genome names; hg19 corresponds to GRCh37
   # perl /path/to/homer/bin/configureHomer.pl -install "${HOMER_GENOME}"
   
   # --- Input/Output Variables ---
   READS_FASTQ="reads.fastq" # Replace with your actual input FASTQ file
   OUTPUT_SAM="aligned.sam"
   OUTPUT_BAM="aligned.bam"
   OUTPUT_SORTED_BAM="aligned.sorted.bam"
   CONTROL_BAM="control.sorted.bam" # Replace with your actual control BAM file (crucial for Super Enhancer calling)
   OUTPUT_PEAKS_DIR="homer_super_enhancer_peaks"
   OUTPUT_PEAKS_FILE="${OUTPUT_PEAKS_DIR}/super_enhancers.txt"
   
   # --- 1. Alignment using Bowtie2 ---
   # Reads were aligned using Bowtie2 to GRCh37
   echo "Starting Bowtie2 alignment..."
   bowtie2 -x "${BOWTIE2_INDEX_PREFIX}" -U "${READS_FASTQ}" -S "${OUTPUT_SAM}"
   echo "Bowtie2 alignment complete."
   
   # Convert SAM to BAM, sort, and index
   echo "Converting SAM to BAM, sorting, and indexing..."
   samtools view -bS "${OUTPUT_SAM}" > "${OUTPUT_BAM}"
   samtools sort "${OUTPUT_BAM}" -o "${OUTPUT_SORTED_BAM}"
   samtools index "${OUTPUT_SORTED_BAM}"
   echo "BAM processing complete."
   
   # --- 2. Super Enhancer (SE) Peak Calling using HOMER v4.11.1 ---
   # SE peaks were called using HOMER v4.11.1 default settings (-style super, Fold change >4, p-value <0.0001)
   echo "Starting HOMER Super Enhancer peak calling..."
   mkdir -p "${OUTPUT_PEAKS_DIR}"
   findPeaks "${OUTPUT_SORTED_BAM}" -style super -o auto -F 4 -p 0.0001 -g "${HOMER_GENOME}" -input "${CONTROL_BAM}" -o "${OUTPUT_PEAKS_FILE}"
   echo "HOMER Super Enhancer peak calling complete. Results in ${OUTPUT_PEAKS_FILE}"

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2. 2

   For mouse samples, reads were aligned using Bowtie2 to MGSCv37 (mm9) and differential peaks were called using HOMER’s79 default settings (Fold change >4, p-value <0.0001) using '-style factor'.

   Bowtie2 v2.4.5 GitHub

   $ Bash example

   # Install Bowtie2 (example using conda)
   # conda install -c bioconda bowtie2=2.4.5
   
   # Install HOMER (example using conda)
   # conda install -c bioconda homer=4.11
   
   # --- Bowtie2 Alignment ---
   # Define input and output files
   READS_R1="sample_R1.fastq.gz" # Replace with actual R1 reads file
   READS_R2="sample_R2.fastq.gz" # Replace with actual R2 reads file (remove if single-end)
   BOWTIE2_INDEX_PREFIX="/path/to/bowtie2_indexes/mm9" # Path to Bowtie2 index for MGSCv37 (mm9)
   ALIGNED_BAM="aligned_reads.bam"
   
   # Align reads using Bowtie2
   # Assuming paired-end reads based on common practice, adjust if single-end
   bowtie2 -x "${BOWTIE2_INDEX_PREFIX}" -1 "${READS_R1}" -2 "${READS_R2}" \
           -S "aligned_reads.sam" \
           --threads 8 # Example: use 8 threads, adjust as needed
   
   # Convert SAM to BAM and sort
   samtools view -bS "aligned_reads.sam" | samtools sort -o "${ALIGNED_BAM}" -
   
   # Remove intermediate SAM file
   rm "aligned_reads.sam"
   
   # --- HOMER Differential Peak Calling ---
   # Define HOMER genome directory (e.g., where mm9 is installed)
   HOMER_GENOME_DIR="/path/to/homer/data/genomes/mm9" # Path to HOMER genome data for mm9
   
   # Define input BAM files for treatment and control
   TREATMENT_BAM="${ALIGNED_BAM}" # Output from Bowtie2 for treatment sample
   CONTROL_BAM="control_aligned_reads.bam" # Replace with actual control BAM file
   
   # Define output directory and peak file name
   OUTPUT_DIR="homer_peaks"
   PEAK_FILE="${OUTPUT_DIR}/differential_peaks.txt"
   
   mkdir -p "${OUTPUT_DIR}"
   
   # 1. Create Tag Directories for treatment and control
   # This step processes BAM files into HOMER's tag directory format
   makeTagDirectory "${OUTPUT_DIR}/treatment_tags" "${TREATMENT_BAM}" -genome "${HOMER_GENOME_DIR}"
   makeTagDirectory "${OUTPUT_DIR}/control_tags" "${CONTROL_BAM}" -genome "${HOMER_GENOME_DIR}"
   
   # 2. Call differential peaks using findPeaks with specified parameters
   # -style factor: appropriate for transcription factor ChIP-seq
   # -F 4: Fold change > 4
   # -P 0.0001: p-value < 0.0001
   findPeaks "${OUTPUT_DIR}/treatment_tags" \
             -o "${PEAK_FILE}" \
             -i "${OUTPUT_DIR}/control_tags" \
             -style factor \
             -F 4 \
             -P 0.0001 \
             -genome "${HOMER_GENOME_DIR}"

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3. 3

   Data tracks were visualized using IGV v2.3.90.

   IGV v2.3.90 GitHub

   $ Bash example

   # Install IGV via conda (recommended)
   # conda create -n igv_env igv=2.3.90 -c bioconda -y
   # conda activate igv_env
   
   # Alternatively, download the specific version from the Broad Institute archive:
   # wget https://data.broadinstitute.org/igv/projects/downloads/2.3/IGV_2.3.90.zip
   # unzip IGV_2.3.90.zip
   # cd IGV_2.3.90
   # chmod +x igv.sh
   
   # Launch IGV and load a reference genome and data tracks for visualization.
   # Replace 'hg38' with the actual reference genome assembly used.
   # Replace 'your_alignment.bam', 'your_coverage.bigwig', 'your_peaks.bed' with the actual data files that were visualized.
   # IGV is primarily a GUI tool; this command launches the application and loads specified files.
   igv --genome hg38 your_alignment.bam your_coverage.bigwig your_peaks.bed

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Tools Used