GSE181138 Processing Pipeline

Publication

Cell reports (2022) — PMID 35263585

Dataset

Identification of the Global miR-130a Targetome Reveals a Novel Role for TBL1XR1 in Hematopoietic Stem Cell Self-Renewal and t(8;21) AML [miR-130a OE]

1. 1

   Raw Data was aligned to hg38 using STAR

   STAR v2.7.10a (Inferred with models/gemini-2.5-flash) GitHub

   $ Bash example

   # Install STAR (if not already installed)
   # conda install -c bioconda star
   
   # Reference genome: hg38
   # Before alignment, a STAR genome index for hg38 must be built.
   # Example command to build index (run once):
   # STAR --runMode genomeGenerate \
   #      --genomeDir /path/to/hg38_star_index \
   #      --genomeFastaFiles /path/to/hg38.fa \
   #      --sjdbGTFfile /path/to/hg38.gtf \
   #      --runThreadN 8 # Adjust threads as needed
   
   # Assume hg38 STAR index is available at /path/to/hg38_star_index
   # Assume input raw data is input.fastq.gz (for single-end reads)
   # For paired-end reads, use: --readFilesIn input_R1.fastq.gz input_R2.fastq.gz
   
   STAR --runThreadN 8 \
        --genomeDir /path/to/hg38_star_index \
        --readFilesIn input.fastq.gz \
        --outFileNamePrefix aligned_reads_ \
        --outSAMtype BAM SortedByCoordinate \
        --outBAMcompression 6

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2. 2

   HT-Seq count was used to obtain read counts over all GENCODE 32 genes

   GENCODE v0.11.2

   $ Bash example

   # Install HTSeq if not already available
   # conda install -c bioconda htseq
   
   # Define input and output files
   INPUT_BAM="aligned_reads.bam" # Placeholder for your aligned BAM file
   GENCODE_GTF="gencode.v32.annotation.gtf"
   OUTPUT_COUNTS="read_counts.txt"
   
   # Download GENCODE v32 GTF if not already present
   # mkdir -p references
   # wget -O references/gencode.v32.annotation.gtf.gz ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_32/gencode.v32.annotation.gtf.gz
   # gunzip -f references/gencode.v32.annotation.gtf.gz
   # GENCODE_GTF="references/gencode.v32.annotation.gtf"
   
   # Run htseq-count
   # Parameters:
   # --format=bam: Input file format is BAM.
   # --stranded=no: Assumes unstranded library preparation. Adjust to 'yes' or 'reverse' if applicable.
   # --mode=union: Default mode for counting reads overlapping features.
   # --type=exon: Count reads overlapping 'exon' features.
   # --idattr=gene_id: Use 'gene_id' attribute to group features and report counts.
   htseq-count \
       --format=bam \
       --stranded=no \
       --mode=union \
       --type=exon \
       --idattr=gene_id \
       "${INPUT_BAM}" \
       "${GENCODE_GTF}" \
       > "${OUTPUT_COUNTS}"

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Tools Used