GSE77700 Processing Pipeline

Publication

Nature communications (2016) — PMID 27378374

Dataset

Distinct and shared molecular targets and functions of ALS-associated TDP-43, FUS, and TAF15 revealed by comprehensive multi-system integrative analy…

1. 1

   Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence, then mapped to mm9 or hg18 whole genome using bowtie v0.12.2 with parameters -q -p 4 -e 100 -y -a -m 10 --best --strata

   Bowtie v0.12.2 GitHub

   $ Bash example

   # Install Bowtie (version 0.12.2 is quite old, may require specific channels or manual compilation)
   # conda install -c bioconda bowtie=0.12.2
   
   # Define the genome assembly to use (mm9 or hg18)
   # Replace with your actual indexed genome path
   GENOME_ASSEMBLY="mm9" # or "hg18"
   BOWTIE_INDEX_BASE="/path/to/bowtie_indexes/${GENOME_ASSEMBLY}"
   
   # Define input reads file (after trimming and masking)
   INPUT_READS="trimmed_and_masked_reads.fastq"
   
   # Define output SAM file
   OUTPUT_SAM="${GENOME_ASSEMBLY}_alignments.sam"
   
   # Run Bowtie with specified parameters
   bowtie -q -p 4 -e 100 -y -a -m 10 --best --strata "${BOWTIE_INDEX_BASE}" "${INPUT_READS}" > "${OUTPUT_SAM}"

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2. 2

   wig files are strand specific read densities generated using custom scripts from duplicate removed bam files.

   bedtools (Inferred with models/gemini-2.5-flash) v2.29.2 GitHub

   $ Bash example

   # conda install -c bioconda bedtools
   
   # Define input and output paths
   INPUT_BAM="input.dedup.bam" # Path to the duplicate-removed BAM file
   OUTPUT_PREFIX="output"      # Prefix for output wiggle files
   
   # Define reference genome files
   # Replace 'hg38.fa' with the actual path to your reference genome FASTA file.
   # Replace 'hg38.chrom.sizes' with the actual path to your chromosome sizes file.
   # If chrom.sizes is not available, it can be generated from the FASTA index:
   # samtools faidx hg38.fa
   # cut -f1,2 hg38.fa.fai > hg38.chrom.sizes
   GENOME_FASTA="hg38.fa" # Placeholder for reference genome FASTA
   CHROM_SIZES="hg38.chrom.sizes" # Placeholder for chromosome sizes file
   
   # --- Placeholder for generating chrom.sizes if needed ---
   # # Ensure samtools is installed: conda install -c bioconda samtools
   # if [ ! -f "${CHROM_SIZES}" ]; then
   #     echo "Generating ${CHROM_SIZES} from ${GENOME_FASTA}..."
   #     samtools faidx "${GENOME_FASTA}"
   #     cut -f1,2 "${GENOME_FASTA}".fai > "${CHROM_SIZES}"
   # fi
   # --------------------------------------------------------
   
   # Generate plus strand specific read densities in WIG format
   # The 'track' line is added to make it a valid WIG file.
   # bedtools genomecov -bg outputs bedGraph format (chr start end score),
   # which is essentially the data part of a variableStep WIG file.
   echo 'track type=wiggle_0 name="plus_strand_coverage" description="Plus strand read densities" visibility=full autoScale=on color=0,0,255' > "${OUTPUT_PREFIX}_plus.wig"
   bedtools genomecov -ibam "${INPUT_BAM}" -bg -strand + | sort -k1,1 -k2,2n >> "${OUTPUT_PREFIX}_plus.wig"
   
   # Generate minus strand specific read densities in WIG format
   echo 'track type=wiggle_0 name="minus_strand_coverage" description="Minus strand read densities" visibility=full autoScale=on color=255,0,0' > "${OUTPUT_PREFIX}_minus.wig"
   bedtools genomecov -ibam "${INPUT_BAM}" -bg -strand - | sort -k1,1 -k2,2n >> "${OUTPUT_PREFIX}_minus.wig"

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3. 3

   bed files represent CLIP-seq peaks and were generated using an in-house peak finding algorithm.

   CLIP-seq vNot specified (Inferred with models/gemini-2.5-flash) GitHub

   $ Bash example

   # Install clipper (if not already installed)
   # It's a Python script, typically run by cloning the repository or installing via pip if available.
   # For example, if cloning:
   # git clone https://github.com/yeolab/clipper.git
   # cd clipper
   
   # Placeholder variables - replace with actual file paths and species
   # INPUT_BAM: Path to the CLIP-seq alignment file (BAM format)
   # CONTROL_BAM: Path to the control alignment file (e.g., input, IgG, or size-matched input) (BAM format)
   # SPECIES: Genome assembly identifier (e.g., hg38, mm10)
   # OUTPUT_PREFIX: Prefix for output files (e.g., peak_calls)
   
   INPUT_BAM="path/to/your/clip_seq_sample.bam"
   CONTROL_BAM="path/to/your/control_sample.bam"
   SPECIES="hg38" # Using hg38 as a common placeholder
   OUTPUT_PREFIX="clip_seq_peaks"
   
   # Execute clipper peak calling
   # Assuming clipper.py is in the current directory or in your PATH
   python clipper.py \
       -s "${SPECIES}" \
       -o "${OUTPUT_PREFIX}" \
       "${INPUT_BAM}" \
       "${CONTROL_BAM}"
   
   # The output will typically be a BED file named ${OUTPUT_PREFIX}.bed

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Tools Used