GSE215251 Processing Pipeline

Publication

iScience (2024) — PMID 38495826

Dataset

Transcriptome Regulation by PARP13 in Basal and Antiviral States in Human Cells

1. 1

   Reads were first trimmed of adapters and low-complexity sequences with cutadapt 1.14 (-O 5 -f fastq --match-read-wildcards --times 2 -e 0.0 --quality-cutoff 6 -m 18 -b TCGTATGCCGTCTTCTGCTTG -b ATCTCGTATGCCGTCTTCTGCTTG -b CGACAGGTTCAGAGTTCTACAGTCCGACGATC -b GATCGGAAGAGCACACGTCTGAACTCCAGTCAC -b AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA -b TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT)

   cutadapt v1.14 GitHub

   $ Bash example

   # Install cutadapt if not already installed
   # conda install -c bioconda cutadapt=1.14
   
   # Define input and output files (placeholders)
   INPUT_FASTQ="input.fastq"
   OUTPUT_FASTQ="output.fastq"
   
   # Reads were first trimmed of adapters and low-complexity sequences
   cutadapt -O 5 -f fastq --match-read-wildcards --times 2 -e 0.0 --quality-cutoff 6 -m 18 \
   -b TCGTATGCCGTCTTCTGCTTG \
   -b ATCTCGTATGCCGTCTTCTGCTTG \
   -b CGACAGGTTCAGAGTTCTACAGTCCGACGATC \
   -b GATCGGAAGAGCACACGTCTGAACTCCAGTCAC \
   -b AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA \
   -b TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTT \
   -o "${OUTPUT_FASTQ}" "${INPUT_FASTQ}"

   Copy View on GitHub
2. 2

   Trimmed reads were then sorted with fastq-tools (fastq-sort)

   fastq-tools vNot specified GitHub

   $ Bash example

   # Install fastq-tools (example using conda, adjust as needed)
   # conda install -c bioconda fastq-tools
   
   # Sort trimmed reads
   # Assuming 'trimmed_reads.fastq' is the input file
   fastq-sort trimmed_reads.fastq > sorted_reads.fastq

   Copy View on GitHub
3. 3

   Trimmed reads were mapped against RepBase with STAR v2.4.0j to remove reads mapping to repetitive sequences (--outFilterMultimapNmax 10 --alignEndsType EndToEnd --outFilterMultimapScoreRange 1 --outSAMmode Full --outFilterType BySJout --outSAMtype BAM Unsorted --outFilterScoreMin 10 --outReadsUnmapped Fastx --outSAMattributes All)

   STAR v2.4.0j GitHub

   $ Bash example

   # Install STAR if not already installed
   # conda install -c bioconda star
   
   # Placeholder for STAR index creation for RepBase (if not already done)
   # Replace repbase.fasta with the actual RepBase FASTA file and adjust threads.
   # STAR --runMode genomeGenerate --genomeDir repbase_star_index --genomeFastaFiles repbase.fasta --runThreadN <num_threads>
   
   # Map trimmed reads against RepBase to identify and remove repetitive sequences
   # Input: trimmed_reads.fastq.gz (or .fq.gz, .fasta, .fa, .bam)
   # Output: repbase_filtered_Unmapped.out.mate1 (and mate2 if paired-end) containing reads that did NOT map to RepBase
   # Output: repbase_filtered_Aligned.out.bam containing reads that DID map to RepBase
   STAR \
     --genomeDir repbase_star_index \
     --readFilesIn trimmed_reads.fastq.gz \
     --outFileNamePrefix repbase_filtered_ \
     --outFilterMultimapNmax 10 \
     --alignEndsType EndToEnd \
     --outFilterMultimapScoreRange 1 \
     --outSAMmode Full \
     --outFilterType BySJout \
     --outSAMtype BAM Unsorted \
     --outFilterScoreMin 10 \
     --outReadsUnmapped Fastx \
     --outSAMattributes All \
     --runThreadN 8 # Example: use 8 threads, adjust as needed
   

   Copy View on GitHub
4. 4

   Remaining reads were mapped to the appropriate genome build (hg19) using STAR aligner (--outFilterMultimapNmax 10 --alignEndsType EndToEnd --outFilterMultimapScoreRange 1 --outSAMmode Full --outFilterType BySJout --outSAMtype BAM Unsorted --outFilterScoreMin 10 --outReadsUnmapped Fastx --outSAMattributes All)

   STAR v2.7.10a GitHub

   $ Bash example

   # Install STAR (if not already installed)
   # conda install -c bioconda star=2.7.10a
   
   # Placeholder variables
   STAR_INDEX_DIR="/path/to/STAR_index/hg19" # Replace with actual path to hg19 STAR index
   INPUT_READS="remaining_reads.fastq.gz" # Replace with actual input FASTQ file (e.g., from a trimming step)
   OUTPUT_PREFIX="aligned_reads_" # Prefix for output files
   NUM_THREADS=8 # Adjust as needed for your system
   
   # Execute STAR alignment
   STAR --genomeDir "${STAR_INDEX_DIR}" \
        --readFilesIn "${INPUT_READS}" \
        --runThreadN "${NUM_THREADS}" \
        --outFileNamePrefix "${OUTPUT_PREFIX}" \
        --outFilterMultimapNmax 10 \
        --alignEndsType EndToEnd \
        --outFilterMultimapScoreRange 1 \
        --outSAMmode Full \
        --outFilterType BySJout \
        --outSAMtype BAM Unsorted \
        --outFilterScoreMin 10 \
        --outReadsUnmapped Fastx \
        --outSAMattributes All

   Copy View on GitHub
5. 5

   featureCounts was used to count reads according to gencode v19 annotations (-s 2 -M)

   featureCounts v2.0.6 (Inferred with models/gemini-2.5-flash) GitHub

   $ Bash example

   # Install Subread package (includes featureCounts)
   # conda install -c bioconda subread=2.0.6
   
   # Define input and output files
   INPUT_BAM="aligned_reads.bam" # Placeholder for input BAM file(s)
   OUTPUT_COUNTS="gene_counts.txt" # Placeholder for output counts file
   GENCODE_GTF="/path/to/gencode.v19.annotation.gtf" # Placeholder for Gencode v19 GTF file path
   
   # Execute featureCounts
   featureCounts -a "${GENCODE_GTF}" -o "${OUTPUT_COUNTS}" -s 2 -M "${INPUT_BAM}"

   Copy View on GitHub

Tools Used