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Psoriasis Transcriptomics: Differential Expression Analysis

Python R Data: RNA-seq Shell Script

A complete RNA-seq data analysis pipeline to characterize the transcriptomic differences and functional implications between healthy skin controls and conventional psoriasis.

About the Report Language

Note: The comprehensive final report associated with this repository (SalazarMendez_Pablo_ProyectoFinal.pdf) is written in Spanish, as it is an academic requirement for the Transcriptomics course at the undergraduate program in Genomic Sciences.

Overview

Psoriasis is a chronic inflammatory skin disease with a complex etiology. This project aims to identify differentially expressed genes (DEGs) between conventional psoriatic skin lesions and normal healthy skin. The analysis reveals a transcriptomic pattern dominated by epidermal and inflammatory activation in psoriasis, alongside a relative decrease in extracellular matrix organization genes.

Dataset

The data was obtained from the Gene Expression Omnibus (GEO) under the accession number GSE117405.

  • Total Samples: 17
  • Conditions: * 8 Conventional Psoriatic Skin (PS) samples
    • 9 Normal Skin (NS) control samples
  • Sequencing Platforms: Illumina HiSeq 2000 & Illumina HiSeq 4000

Pipeline & Methodology

The standard RNA-seq bioinformatics workflow was implemented as follows:

  • Quality Control & Trimming: FastQC and fastp (removed 13 initial biased bases).
  • Alignment: Reads were aligned to the human reference genome (GRCh38) using STAR.
  • Quantification: Read assignment to annotated genomic regions was performed using featureCounts.
  • Batch Effect Correction: pyCombat (from the inmoose suite) was used to correct technical variability arising from the different sequencing instruments.
  • Differential Expression Analysis: Executed using the DESeq2 implementation in the inmoose Python suite ($FDR < 10^-5$ and $|LFC| > 1$).
  • Functional Enrichment: DAVID and STRING were used to analyze DEGs for biological process enrichment and protein-protein interaction (PPI) networks.

Key Results

  • Upregulated in Psoriasis: Enrichment in processes related to keratinization, cornified envelope formation, epidermal development, keratinocyte differentiation, innate immunity, and antimicrobial defense (e.g., S100, LCE, and SPRR gene families).
  • Downregulated in Psoriasis: Relative reduction in programs associated with extracellular matrix architecture, collagen, cell adhesion, and tissue structural maintenance (e.g., COL5A1, ADAMTS members).

Author: Pablo Salazar-Méndez

About

Repository dedicated to the final project for the Transcriptomics course taught by Dr. David Valle as part of the Bachelor of Science in Genomic Sciences program at UNAM. This project analyzed bulk RNA-seq data from patients with psoriasis in both normal and affected tissue

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