GSE51741 Processing Pipeline
code_examples
4 steps
Warning: Pipeline descriptions and code snippets may be inferred or AI-generated. Use them only as a starting point to guide analysis, and validate before use.
Processing Steps
Generate Jupyter Notebook-
1
Illumina Casava1.8.2 software used for basecalling.
Illumina Casava v1.8.2$ Bash example
# Illumina Casava 1.8.2 is proprietary software run on Illumina sequencing instruments # for basecalling and demultiplexing. This step is performed by the sequencer itself. # No user-executable command-line tool is typically run for Casava basecalling post-sequencing. # The output of this step would be raw sequencing data in FASTQ format, which serves as input for downstream bioinformatics analysis.
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2
Demultiplexing based on index sequences
bcl2fastq (Inferred with models/gemini-2.5-flash) v2.20.0.422 (Inferred with models/gemini-2.5-flash) GitHub$ Bash example
# Install bcl2fastq (example using conda) # conda install -c bioconda bcl2fastq2 # Define input and output directories and sample sheet RUN_FOLDER_DIR="/path/to/illumina/run/directory" # Directory containing BCL files OUTPUT_FASTQ_DIR="/path/to/output/fastq/directory" SAMPLE_SHEET="/path/to/sample_sheet.csv" # This file defines samples and their index sequences # Execute bcl2fastq for demultiplexing based on index sequences bcl2fastq --runfolder-dir "${RUN_FOLDER_DIR}" \ --output-dir "${OUTPUT_FASTQ_DIR}" \ --sample-sheet "${SAMPLE_SHEET}" \ --no-lane-splitting \ --barcode-mismatches 1 \ --minimum-trimmed-read-length 8 \ --mask-short-adapter-reads 8 \ --ignore-missing-bcl \ --ignore-missing-stats \ --ignore-missing-positions -
3
Sequenced reads were mapped to Refseq RNA sequences using bowtie v0.12.7 with parameters -q -e 100 -m 10 --best --strata
$ Bash example
# Install Bowtie v0.12.7 if not already installed # conda install -c bioconda bowtie=0.12.7 # Placeholder for Refseq RNA index. This index needs to be built beforehand # using bowtie-build from your Refseq RNA FASTA file (e.g., refseq_rna.fasta). # Example: bowtie-build refseq_rna.fasta refseq_rna_index # Placeholder for input sequenced reads (e.g., a FASTQ file) # Placeholder for output SAM file # Execute Bowtie mapping bowtie -q -e 100 -m 10 --best --strata refseq_rna_index reads.fastq > output.sam
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4
Count reads for each genes
$ Bash example
# Install Subread (which includes featureCounts) # conda install -c bioconda subread # Define input and output files # Replace 'aligned_reads.bam' with your actual aligned BAM file(s) # Replace 'Homo_sapiens.GRCh38.109.gtf' with your specific gene annotation GTF file INPUT_BAM="aligned_reads.bam" GENE_ANNOTATION_GTF="Homo_sapiens.GRCh38.109.gtf" # Example: Ensembl GRCh38 release 109 OUTPUT_COUNTS="gene_counts.txt" # Execute featureCounts to count reads per gene # -a: Annotation file # -o: Output file # -F GTF: Specify annotation file format # -t exon: Feature type to count (e.g., 'exon') # -g gene_id: Attribute type to group features (e.g., 'gene_id') # -s 2: Strandedness (0=unstranded, 1=forward, 2=reverse). eCLIP often uses reverse stranded. # -T 8: Number of threads featureCounts \ -a "${GENE_ANNOTATION_GTF}" \ -o "${OUTPUT_COUNTS}" \ -F GTF \ -t exon \ -g gene_id \ -s 2 \ -T 8 \ "${INPUT_BAM}"
Tools Used
Raw Source Text
Illumina Casava1.8.2 software used for basecalling. Demultiplexing based on index sequences Sequenced reads were mapped to Refseq RNA sequences using bowtie v0.12.7 with parameters -q -e 100 -m 10 --best --strata Count reads for each genes Supplementary_files_format_and_content: tab-delimited text files include counts for each genes in each samples.