Dataset Open Access

Gene regulatory networks for 38 human tissues

Sonawane, Abhijeet R; Platig, John; Fagny, Maud; Chen, Cho-Yi; Paulson, Joseph N; Lopes-Ramos, Camila M; DeMeo, Dawn L; Quackenbush, John; Glass, Kimberly; Kuijjer, Marieke Lydia

Contact person(s)
Kuijjer, Marieke Lydia; Glass, Kimberly

We reconstructed gene regulatory networks for 38 tissues from the Genotype-Tissue Expression project (GTEx), and used these networks to investigate gene expression and regulation across these tissues. In the RData file, we share the following objects:

- edges: an 19,476,492 by 3 data.frame including three columns: TF (the transcription factor's gene symbol), Gene (Ensembl ID), Prior (whether an edge is canonical (1) or non-canonical (0)).

- exp: a 30,243 by 9,435 matrix including normalized expression data for each sample.

- expTS: a 30,243 by 38 matrix including, for each gene and each tissue, information on whether the gene is expressed in a tissue-specific manner in that tissue (1) or not (0).

- genes: a 30,243 by 4 data.frame that includes annotation information (Symbol) for Ensembl gene IDs (Name). This data.frame also includes information on whether genes are also transcription factors (AlsoTF), with options: no, yes/motif (TF with a known DNA-binding motif) yes/nomotif (TF without a known DNA-binding motif). In addition, the multiplicity of the gene (Multiplicity) is given.

- net:  a 19,476,492 by 38 matrix that includes edge weights for each tissue. Edge order corresponds to edge order in the the object "edges".

- netTS: a 19,476,492 by 38 matrix that includes information of whether edges are specific to a tissue (1) or not (0).

- samples: a 9,435 by 2 data.frame that includes sample identifiers (matching the identifiers in "exp") and the tissue to which these samples belong.

This work was supported by grants from the US National institutes of Health, including grants from the National Heart, Lung, and Blood Institute (5P01HL105339, 5R01HL111759, 5P01HL114501, K25HL133599), the National Cancer Institute (5P50CA127003, 1R35CA197449, 1U01CA190234, 5P30CA006516, P50CA165962), the National Institute of Allergy and Infectious Disease (5R01AI099204), and the Charles A. King Trust Postdoctoral Research Fellowship Program, Bank of America, N.A., Co-Trustees and Sara Elizabeth O'Brien Trust, Bank of America, N.A., Trustee. Additional funding was provided through a grant from the NVIDIA foundation. This work was conducted under dbGaP approved protocol #9112 (accession phs000424.v6.p1).
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