trib2.nat.sci.data

{trib2.nat.sci.data} is a repository providing the R code used for the exploratory data analysis of the RNA-seq data related to the study of the role of TRIB2 in melanoma tumor progression using UACC-62 melanoma cells. Briefly, three cell types were analyzed: wild-type (WT) and two independent TRIB2 knockout (KO) clones (clone 28 and clone 31). Single-end 61 bp RNA-seq was performed to assess gene expression differences.

Authors

Isabel Duarte, Victor Mayoral-Varo, Rebeca Álvarez, Ana Dopazo, Wolfgang Link, and Bibiana I. Ferreira.

Citation

TBA after data descriptor paper publication.

Run the data analysis

This repository contains code to reproduce the analyses reported in the accompanying data descriptor manuscript. Gene expression data were generated from raw RNA-seq reads using the nf-core/rnaseq pipeline.

Two alternative workflows are supported:

• A. Reprocess the raw RNA-seq reads using nf-core/rnaseq (full reproducibility from FASTQ files).
• B. Analyse the processed gene expression data reported in the manuscript (recommended for most users).

Requirements

A. Reprocessing raw RNA-seq reads with nf-core/rnaseq

Use this option if you wish to reproduce the full processing workflow starting from the raw sequencing data.

1. Install Nextflow and the nf-core/rnaseq pipeline, following the official nf-core installation guidelines.

2. Download the FASTQ files from the BioStudies ArrayExpress repository E-MTAB-16439 and place them in a data/ directory within the project root.

3. Download a human reference genome assembly and the corresponding annotation file (GTF) of your choice, and place them in a genomes/ directory within the project root.

4. Edit the scripts run_nf-core_rnaseq_pipeline.sh and samplesheet.sh to match your local filesystem layout and reference genome choices, then execute the pipeline from the project root directory.

B. Analysing the processed gene expression data (recommended)

Use this option if you wish to reproduce the analyses and figures reported in the manuscript without reprocessing the raw reads.

1. Install R and RStudio (optional but recommended).

2. Download the processed gene expression files salmon.merged.gene_tpm.tsv and salmon.merged.gene_counts.tsv from the BioStudies ArrayExpress repository E-MTAB-16439 and place them in the data/ directory within the project root.

3. Open and run the R Markdown file trib2_nat_sci_data.Rmd, updating file paths if necessary to match your local filesystem.