RNA-seq Workflow on Drosophila

This is my RNA-seq analysis pipeline for Drosophila melanogaster.
It goes from raw reads → QC/trimming → genome index → alignment → counting reads per gene with featureCounts.

i didn’t upload the large fastq/bam files to github because they’re too big.
if you want to run this yourself, you can download the same data i used from the links below. :)

This dataset contained approximately 50 million base pairs of sequence data, with an 81.7% alignment rate to the annotated drosophila melanogaster genome.

Data I used

Paired-end FASTQ files (subsampled)

• Read 1: https://ftp.sra.ebi.ac.uk/vol1/fastq/SRR070/SRR070412/SRR070412_1.fastq.gz
• Read 2: https://ftp.sra.ebi.ac.uk/vol1/fastq/SRR070/SRR070412/SRR070412_2.fastq.gz

Reference genome (Ensembl Release 113, BDGP6.46)

• Genome FASTA: https://ftp.ensembl.org/pub/release-113/fasta/drosophila_melanogaster/dna/Drosophila_melanogaster.BDGP6.46.dna.toplevel.fa.gz
• GTF annotation: https://ftp.ensembl.org/pub/release-113/gtf/drosophila_melanogaster/Drosophila_melanogaster.BDGP6.46.113.gtf.gz

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Tools I used

• fastqc – for quality check
• fastp – for trimming
• bwa – for alignment
• samtools – for sorting and indexing BAM files
• featureCounts (from subread) – for counting reads per gene

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How I ran it (short version)

1. QC + trimming – fastqc + fastp
2. Genome index – built with bwa index genome.fa
3. Alignment – bwa mem with paired reads
4. Sort + index – samtools sort and samtools index
5. Counting – featureCounts -T 4 -p -B -C ...

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Output

• Results/counts/featurecounts.txt – counts per gene
• Results/counts/featurecounts.txt.summary – mapping/counting summary