Gene Expression and Splicing Counts from Yepez and Gusic Study: 135 Fibroblast Samples

Gene-level and splice junction counts from 135 human fibroblast RNA-Seq samples, aligned to the hg19 genome. The data was generated by researchers at the Technical University of Munich using GENCODE release 34 annotation. Samples include individuals with various metabolic and neurological disorders, with a median of 116 million mapped reads per sample.

Use Cases

• Detect expression outliers in fibroblast RNA-Seq data based on provided gene-level counts.
• Analyze alternative splicing patterns using the provided split and non-split junction counts.
• Merge with other RNA-Seq datasets for meta-analysis, provided tissue and sequencing parameters match.
• Benchmark splicing quantification pipelines using the annotated junction counts from GENCODE 34.

Strengths

• Includes 135 fibroblast samples with detailed disease annotations based on ICD-10 codes.
• High sequencing depth with a median of 116 million mapped reads per sample.
• Strand-specific and paired-end sequencing improves accuracy for transcriptome analysis.
• Counts are derived from a standard annotation source (GENCODE release 34).

Limitations

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

Provenance

Source

Technical University of Munich, from the study by Yepez, Gusic et al.

Collection Method

RNA sequencing of fibroblast cells, with counts generated using the DROP analysis pipeline.