GSE136912 Processing Pipeline

Publication

Circulation (2020) — PMID 32393053

Dataset

Endothelial-AGO1-knockout (EC-AGO1-KO) mice and wild-type (WT) littermates

1. 1

   CLIPSeqTool0.1.8 was used to trim the adapaters, align the reads to the genome and perform deduplications

   CLIPSeqTool v0.1.8 GitHub

   $ Bash example

   # Assuming CLIPSeqTool is installed and available in the PATH
   # For example, it might be a custom script or part of a larger pipeline.
   # If it's a Python script, you might run it with `python CLIPSeqTool.py ...`
   # If it's a compiled binary, `CLIPSeqTool ...`
   
   # Placeholder for input reads, genome index, and output directory
   INPUT_READS="input_reads.fastq.gz"
   GENOME_INDEX_DIR="/path/to/genome/index/hg38"
   OUTPUT_DIR="./clipseq_output"
   
   mkdir -p "${OUTPUT_DIR}"
   
   # Execute CLIPSeqTool to trim adapters, align reads, and perform deduplication
   # The exact parameters are inferred based on the description of its functions.
   # This command assumes a common CLI structure for such a tool.
   CLIPSeqTool0.1.8 \
     --input "${INPUT_READS}" \
     --genome_index "${GENOME_INDEX_DIR}" \
     --output_dir "${OUTPUT_DIR}" \
     --trim_adapters \
     --align_reads \
     --deduplicate
   

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2. 2

   Kallisto0.44.0 was used to quantify transcripts abundance in terms of TPM

   Kallisto v0.44.0 GitHub

   $ Bash example

   # Install Kallisto 0.44.0 (example using conda)
   # conda create -n kallisto_env kallisto=0.44.0 -c bioconda -y
   # conda activate kallisto_env
   
   # Placeholder for Kallisto index (e.g., built from a reference transcriptome like human GRCh38)
   # kallisto index -i transcriptome.idx transcripts.fasta.gz
   
   # Quantify transcripts abundance in terms of TPM
   # Input: Paired-end FASTQ files (read1.fastq.gz, read2.fastq.gz)
   # Output: Quantification results in kallisto_output directory (including abundance.tsv with TPM values)
   kallisto quant -i transcriptome.idx -o kallisto_output read1.fastq.gz read2.fastq.gz

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