GSE201891 Processing Pipeline

Publication

Science translational medicine (2022) — PMID 35767654

Dataset

MECP2-related pathways are dysregulated in a cortical organoid model of Myotonic dystrophy [scRNA-Seq]

1. 1

   Alignment, cell barcode processing, umis processing, abundance measurements: cellranger count (version 3.0.2)

   Cell Ranger v3.0.2

   $ Bash example

   # Cell Ranger 3.0.2 is typically installed by downloading the tarball and extracting it.
   # Example:
   # wget https://cf.10xgenomics.com/releases/cell-exp/cellranger-3.0.2.tar.gz
   # tar -xzf cellranger-3.0.2.tar.gz
   # export PATH=/path/to/cellranger-3.0.2:$PATH
   
   # Download a reference transcriptome (e.g., GRCh38) if not already available.
   # Example:
   # wget https://cf.10xgenomics.com/releases/cell-exp/refdata-gex-GRCh38-2020-A.tar.gz
   # tar -xzf refdata-gex-GRCh38-2020-A.tar.gz
   # mv refdata-gex-GRCh38-2020-A /path/to/your/references/
   
   # Define variables (replace with actual paths and sample ID)
   SAMPLE_ID="my_sample_id"
   FASTQ_DIR="/path/to/your/fastqs" # Directory containing FASTQ files for the sample
   TRANSCRIPTOME_REF="/path/to/your/references/refdata-gex-GRCh38-2020-A" # Example GRCh38 reference
   
   # Execute cellranger count for alignment, cell barcode processing, UMI processing, and abundance measurements
   cellranger count \
       --id="${SAMPLE_ID}" \
       --transcriptome="${TRANSCRIPTOME_REF}" \
       --fastqs="${FASTQ_DIR}" \
       --sample="${SAMPLE_ID}" # Use --sample if multiple samples are in FASTQ_DIR and you want to process a specific one
   

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2. 2

   MD tags were added to alignments with samtools calmd --threads 15 -rb possorted_genome_bam.bam refdata-cellranger-hg19-3.0.0/fasta/genome.fa > possorted_genome_bam_MD.bam

   Cell Ranger v3.0.0 GitHub

   $ Bash example

   # Install samtools (e.g., using conda)
   # conda install -c bioconda samtools=1.9
   
   # Define input and output files
   INPUT_BAM="possorted_genome_bam.bam"
   OUTPUT_BAM="possorted_genome_bam_MD.bam"
   REFERENCE_FASTA="refdata-cellranger-hg19-3.0.0/fasta/genome.fa"
   
   # Add MD tags to alignments
   samtools calmd --threads 15 -rb "${INPUT_BAM}" "${REFERENCE_FASTA}" > "${OUTPUT_BAM}"

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3. 3

   Reads were split based on the CB:Z tag, resulting in one BAM file per barcode.

   samtools (Inferred with models/gemini-2.5-flash) v1.19.1 GitHub

   $ Bash example

   # Install samtools if not already installed
   # conda install -c bioconda samtools
   
   # Define input BAM file and output directory
   INPUT_BAM="input.bam"
   OUTPUT_DIR="split_bams"
   
   # Create output directory if it doesn't exist
   mkdir -p "${OUTPUT_DIR}"
   
   # Extract unique CB:Z tags from the input BAM file
   # This command pipes the SAM output, extracts the CB:Z tag using grep,
   # cuts the barcode value, sorts it, and gets unique entries.
   samtools view "${INPUT_BAM}" | \
       grep -o 'CB:Z:[^[:space:]]*' | \
       cut -d':' -f3 | \
       sort -u > unique_barcodes.list
   
   # Loop through each unique barcode and split the BAM file
   while IFS= read -r BARCODE; do
       if [ -n "$BARCODE" ]; then # Ensure the barcode is not empty
           echo "Splitting reads for barcode: ${BARCODE}"
           # Filter the BAM file for reads containing the specific CB:Z tag
           # and write them to a new BAM file.
           # samtools view -h: output header and SAM format
           # grep -P "\tCB:Z:${BARCODE}\t": filter for lines containing the exact tag
           # samtools view -bS -: convert filtered SAM stream back to BAM
           samtools view -h "${INPUT_BAM}" | \
               grep -P "\tCB:Z:${BARCODE}\t" | \
               samtools view -bS - > "${OUTPUT_DIR}/${BARCODE}.bam"
           
           # Index the newly created BAM file (optional, but good practice for downstream tools)
           samtools index "${OUTPUT_DIR}/${BARCODE}.bam"
       fi
   done < unique_barcodes.list
   
   # Clean up the temporary file containing unique barcodes
   rm unique_barcodes.list

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