GSE34993 Processing Pipeline

Publication

Cell reports (2012) — PMID 22574288

Dataset

Integrative genome-wide analysis reveals cooperative regulation of alternative splicing by hnRNP proteins (CLIP-Seq)

1. 1

   CLIP-seq reads were processed as previously described (Polymenidou et al., 2011).

   CLIP-seq v0.12.7 GitHub

   $ Bash example

   # Define variables
   GENOME_FASTA="mm9.fa"
   GENOME_INDEX_PREFIX="mm9_index"
   INPUT_FASTQ="clip_seq_reads.fastq" # Placeholder for input CLIP-seq reads
   OUTPUT_SAM="aligned_reads.sam"
   OUTPUT_BAM="aligned_reads.bam"
   OUTPUT_PEAKS="peaks.bed" # Placeholder for peak output
   
   # --- Installation (commented out) ---
   # Install Bowtie (version 0.12.7)
   # For example, using conda:
   # conda create -n bowtie_env bowtie=0.12.7
   # conda activate bowtie_env
   
   # Install samtools (for converting SAM to BAM and sorting)
   # conda install -c bioconda samtools
   
   # --- Reference Genome Preparation (commented out) ---
   # Download the mouse reference genome (mm9) from UCSC
   # wget -nc http://hgdownload.soe.ucsc.edu/goldenPath/mm9/bigZips/mm9.fa.gz
   # gunzip -f "${GENOME_FASTA}.gz"
   
   # Build Bowtie index for the mm9 genome
   # bowtie-build "${GENOME_FASTA}" "${GENOME_INDEX_PREFIX}"
   
   # --- CLIP-seq Read Processing ---
   
   # Step 1: Align CLIP-seq reads to the mouse genome (mm9) using Bowtie.
   # As described in Polymenidou et al., 2011:
   # -v 2: Allow up to two mismatches.
   # -m 1: Discard reads that map to more than one location (multi-mapping reads).
   # --best --strata: Report alignments that are "best" in terms of mismatches.
   bowtie -v 2 -m 1 --best --strata "${GENOME_INDEX_PREFIX}" "${INPUT_FASTQ}" "${OUTPUT_SAM}"
   
   # Step 2: Convert SAM to BAM and sort the aligned reads.
   # This is a standard post-alignment step for downstream analysis.
   samtools view -bS "${OUTPUT_SAM}" | samtools sort -o "${OUTPUT_BAM}" -
   
   # Step 3: Peak Calling.
   # Polymenidou et al., 2011 states: "Peaks were identified using a custom script
   # that identified regions with at least five overlapping reads."
   # The exact custom script is not publicly available.
   # Therefore, no specific bash command can be provided for this step.
   # In a modern context, dedicated CLIP-seq peak callers (e.g., CLIPper, Piranha)
   # would typically be used, or a custom script implementing the described criteria.
   # Example of a conceptual command if the script were available:
   # custom_peak_caller.sh "${OUTPUT_BAM}" 5 > "${OUTPUT_PEAKS}"

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2. 2

   Briefly, reads were trimmed to remove sequencing adaptors and homopolymeric runs >10nt, and mapped to the human genome (hg18) using Bowtie (version 0.12.2 with parameters –q –l 20 –m 5 –k 5 ––best).

   Bowtie v0.12.2 GitHub

   $ Bash example

   # Install Bowtie (if not already installed)
   # conda install -c bioconda bowtie=0.12.2
   
   # Placeholder for input reads and output file
   # Replace 'input_reads.fastq' with your actual trimmed reads file
   # Replace 'output.sam' with your desired output alignment file name
   
   # Ensure the hg18 index is available. If not, you would need to build it first:
   # bowtie-build hg18.fa hg18
   
   bowtie -q -l 20 -m 5 -k 5 --best hg18 input_reads.fastq > output.sam

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Tools Used