GSE232519 Processing Pipeline

Publication

Nature communications (2024) — PMID 39152130

Dataset

Expanded repertoire of RNA-editing-based detection for RNA binding protein interactions (5)

1. 1

   remove adapter with Cutadapt

   cutadapt v4.0 GitHub

   $ Bash example

   # Install Cutadapt (if not already installed)
   # conda create -n cutadapt_env cutadapt=4.0 -y
   # conda activate cutadapt_env
   
   # Define input and output file paths
   INPUT_READ1="input_R1.fastq.gz"
   INPUT_READ2="input_R2.fastq.gz" # Required for paired-end
   OUTPUT_READ1="trimmed_R1.fastq.gz"
   OUTPUT_READ2="trimmed_R2.fastq.gz" # Required for paired-end
   
   # Define adapter sequences (replace with actual adapters for your library prep)
   # Example placeholder adapters (replace with actual sequences, e.g., from library prep kit or sequencing facility)
   # For Illumina, common forward adapter: AGATCGGAAGAGCACACGTCTGAACTCCAGTCA
   # For Illumina, common reverse adapter: AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT
   ADAPTER_FWD="AGATCGGAAGAGCACACGTCTGAACTCCAGTCA"
   ADAPTER_REV="AGATCGGAAGAGCGTCGTGTAGGGAAAGAGTGT"
   
   # Run Cutadapt for paired-end reads
   cutadapt -a "${ADAPTER_FWD}" -A "${ADAPTER_REV}" \
            -o "${OUTPUT_READ1}" -p "${OUTPUT_READ2}" \
            "${INPUT_READ1}" "${INPUT_READ2}" \
            --minimum-length 15 \
            --quality-cutoff 20 \
            --trim-n
   

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2. 2

   align to genome using bowtie2 or bwa-mem

   Bowtie2 v2.4.5 GitHub

   $ Bash example

   # Install Bowtie2 (if not already installed)
   # conda install -c bioconda bowtie2
   
   # Example: Build Bowtie2 index (if not already available)
   # Replace 'path/to/genome.fa' with your reference genome FASTA file (e.g., hg38.fa)
   # bowtie2-build path/to/genome.fa path/to/genome_index
   
   # Align reads to the genome using Bowtie2
   # Replace 'path/to/genome_index' with the path to your Bowtie2 index (e.g., hg38_index)
   # Replace 'path/to/reads.fastq.gz' with your input FASTQ file (e.g., sample_R1.fastq.gz for single-end)
   # Replace 'output_aligned.sam' with your desired output SAM file name
   # Using common parameters for single-end reads and 8 threads.
   # For paired-end reads, use -1 <reads_1.fastq.gz> -2 <reads_2.fastq.gz> instead of -U.
   
   bowtie2 -x path/to/genome_index -U path/to/reads.fastq.gz -S output_aligned.sam --threads 8

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3. 3

   generate count tables along reporter sequence using Pysamstats

   Pysamstats v1.1.2

   $ Bash example

   # Install pysamstats if not already installed
   # pip install pysamstats
   
   # Define input and output files
   INPUT_BAM="aligned_reads.bam" # Placeholder for the input alignment file
   REPORTER_BED="reporter_sequences.bed" # Placeholder for the BED file defining reporter sequences
   OUTPUT_COUNTS="reporter_counts.tsv"
   REFERENCE_FASTA="GRCh38.p14.genome.fa" # Placeholder for the latest human reference genome FASTA
   
   # Generate count tables (e.g., coverage) along reporter sequences using pysamstats
   # The --type parameter can be adjusted based on the specific "count" desired (e.g., coverage, reads, gc, tlen, etc.)
   # 'coverage' is a common and reasonable default for "generate count tables along reporter sequence".
   pysamstats --type coverage --fasta "${REFERENCE_FASTA}" --regions "${REPORTER_BED}" "${INPUT_BAM}" > "${OUTPUT_COUNTS}"

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Tools Used