Published December 14, 2022 | Version 1.1
Dataset Open

Gene expression and splicing counts from the Yepez, Gusic et al study - fibroblast, hg19, strand-specific, high seq depth

Description

File description:

  1. geneCounts: gene-level counts 

  2. k_j: split counts spanning from one exon to another.

  3. k_theta: non-split counts covering a splice site

  4. n_psi3: total split counts from a given acceptor site

  5. n_psi5: total split counts from a given donor site

  6. n_theta: total split and non-split counts for a given splice site

  7. Sample annotation describing each sample from the dataset

  8. Description file with global information from the dataset

 

The gene counts were originated using the GTF file from release 34 of GENCODE https://www.gencodegenes.org/human/release_34, and the split and non-split counts contain only the annotated junctions from the same release.

Use: The count matrices are intended to help researchers that are interested in using RNA-Seq data with the purpose of diagnostics. Researchers can merge their own dataset with the downloaded ones, provided the tissue, genome build, strand, and paired-end specifications match. Afterwards, DROP can be used to compute expression and splicing outliers (https://github.com/gagneurlab/drop).

Number of samples: 135
Tissue: Fibroblast
Organism: Homo sapiens
Genome assembly: hg19
Gene annotation: gencode34

Median mapped reads: 116 million
Disease (ICD-10: N): E88: 112, G31: 8, NONE: 5, K72: 2, G71: 2, E72: 1, G93: 1, I42: 1, F82: 1, E75: 1, F89: 1
Strand specific: True
Paired end: True
Dataset contact: Vicente Yepez, yepez at in.tum.de; Christian Mertes, mertes at in.tum.de; Julien Gagneur, gagneur at in.tum.de; Holger Prokisch, prokisch at helmholtz-muenchen.de

Citation: Cite both the resource using Zenodo's citation and the publication under References

 

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Additional details

References

  • YĆ©pez, V. A., Gusic, M., Kopajtich, R., Mertes, C., et al. (2022). Clinical implementation of RNA sequencing for Mendelian disease diagnostics. Genome Med 14, 38. doi: 10.1186/s13073-022-01019-9.