S. cerevisiae Ribosome Profiling and RNA-Seq Data for Oxidative Stress Response

Transcriptomic and ribosome profiling data for Saccharomyces cerevisiae yeast under normal and oxidative stress conditions. The dataset includes assembled transcriptomes, read counts for RNA-Seq and Ribo-Seq experiments across two replicates, and lists of significantly up- and down-regulated genes. Data was generated by Mar Albà and is available via the paperswithcode platform under an Open Access license.

Use Cases

• Identify differentially expressed genes based on RNA-Seq and Ribo-Seq count data.
• Study translational regulation during oxidative stress using lists of genes with changed translational efficiency.
• Compare protein expression levels inferred from ribosome profiling to mRNA levels from RNA-Seq.
• Analyze 5'UTR annotations for S. cerevisiae S288C to investigate regulatory sequence elements.

Strengths

• Includes paired-end strand-specific sequencing reads for improved transcript assembly accuracy.
• Provides data from two biological replicates (Rep1 and Rep2) for control and treated conditions.
• Combines multiple data types: RNA-Seq, Ribo-Seq, and mass spectrometry protein data in supplementary files.

Limitations

• Row count and dataset size are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

paperswithcode

Collection Method

RNA-Seq and Ribo-Seq experiments on S. cerevisiae S288C yeast grown in normal and hydrogen peroxide-induced oxidative stress conditions, with transcriptome assembly performed using Trinity.