GSE122649 Processing Pipeline

Publication

Acta neuropathologica (2022) — PMID 35778567

Dataset

Postmortem Cortex Samples Identify Distinct Molecular Subtypes of ALS: Retrotransposon Activation, Oxidative Stress, and Activated Glia [motor cortex]

1. 1

   Base calling performed with bcl2fastq conversion software v2.17

   bcl2fastq v2.17 GitHub

   $ Bash example

   # Install bcl2fastq (example using conda, adjust as needed)
   # conda install -c bioconda bcl2fastq
   
   # Base calling performed with bcl2fastq conversion software v2.17
   # Replace /path/to/illumina/run/folder with the actual path to your BCL data
   # Replace /path/to/output/fastq with your desired output directory for FASTQ files
   bcl2fastq --runfolder-dir /path/to/illumina/run/folder --output-dir /path/to/output/fastq

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2. 2

   Reads were aligned to hg19 genome using STAR v2.5.2b with the following configurations: --outFilterMultimapNmax 100; --outFilterMismatchNoverReadLmax 0.04

   STAR v2.5.2b GitHub

   $ Bash example

   # Install STAR (if not already installed)
   # conda install -c bioconda star=2.5.2b
   
   # Placeholder for reference genome index
   # Ensure the hg19 STAR index is built and available at this path.
   # Example: STAR --runMode genomeGenerate --genomeDir /path/to/STAR_index/hg19 --genomeFastaFiles /path/to/hg19.fa --sjdbGTFfile /path/to/hg19.gtf --runThreadN <num_threads>
   HG19_STAR_INDEX="/path/to/STAR_index/hg19"
   
   # Placeholder for input reads (e.g., a FASTQ file)
   INPUT_READS="input_reads.fastq.gz" # Use "input_reads_R1.fastq.gz input_reads_R2.fastq.gz" for paired-end
   
   # Output prefix for alignment files
   OUTPUT_PREFIX="aligned_star_"
   
   STAR --genomeDir "${HG19_STAR_INDEX}" \
        --readFilesIn "${INPUT_READS}" \
        --outFileNamePrefix "${OUTPUT_PREFIX}" \
        --outFilterMultimapNmax 100 \
        --outFilterMismatchNoverReadLmax 0.04 \
        --outSAMtype BAM SortedByCoordinate \
        --outSAMattributes Standard \
        --runThreadN 8 # Example: use 8 threads, adjust as needed
   
   # The primary output BAM file will be named: ${OUTPUT_PREFIX}Aligned.sortedByCoord.out.bam

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3. 3

   Genes and TE were quantified using TEcount (from TEtranscripts v2.0.3) with the following configurations: hg19 genic GTF from refGene (Jan 2018), custom hg19 TE GTF generated from repeatMasker; --stranded reverse

   TEcount (from TEtranscripts) v2.0.3

   $ Bash example

   # Install TEtranscripts (which includes TEcount) if not already installed
   # conda create -n tetranscripts python=3.7
   # conda activate tetranscripts
   # pip install TEtranscripts==2.0.3
   
   # Placeholder for input BAM file (e.g., aligned RNA-seq reads)
   INPUT_BAM="input_aligned_reads.bam"
   # Placeholder for output prefix for quantification results
   OUTPUT_PREFIX="te_quantification_results"
   
   # Reference GTF files based on description
   # hg19 genic GTF from refGene (Jan 2018)
   GENE_GTF="hg19_refgene_genic_jan2018.gtf"
   # custom hg19 TE GTF generated from repeatMasker
   TE_GTF="hg19_repeatmasker_TEs.gtf"
   
   # Execute TEcount with specified configurations
   # --mode union and --format BAM are common defaults for TEcount with BAM input
   TEcount --mode union --format BAM --stranded reverse -b "${INPUT_BAM}" -g "${GENE_GTF}" -t "${TE_GTF}" --out "${OUTPUT_PREFIX}"

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Tools Used