To get the full list of phenotypic variables, please check the menu below. Please click on the scatter plot to access the network view page.
Tool description
PANDA reconstructs a gene regulatory network using TF PPI, TF DNA binding motif as regulation prior, and gene expression samples. PUMA reconstructs a gene regulatory network with miRNA as regulators using gene expression samples and miRNA predicted targets by miRanda or TargetScan as regulation priors. The Regulator-regulator interaction matrix is set to the identity matrix in the algorithm. LIONESS reconstructs patient-specific PANDA networks for each gene expression sample.
BONOBO is a single-sample network inference method, which can be used to estimate patient-specific co-expression matrices, which are then fed as input for PANDA to build patient-specific GRNs. To adapt BONOBO-PANDA networks for patient's sex, and in addition to sample-specific co-expression, PANDA's motif prior networks are constructed for each sex (accounting for sex chromosomes), while the third input (PPI networks) are generic for all patients. To download sample-specific networks, you can check the phenotypic information and select the networks by clinical variables or download all the samples in a single file.
Variable description
PANDA-LIONESS networks are single-sample networks generated by first estimating an aggregate PANDA network then deriving patient-specific LIONESS networks. You can either download all the networks to get a matrix of size the number of samples by the number of edges. The number of edges is 644 * 30243 (number of miRNA/TFs * number of genes) (~ 106). Otherwise, you can specify the sample network to download and you will get a miRNA/TF-by-gene matrix named after the GTEx sample reference.
Sample | Subject | Gender | Age | DTH-HRDY | SMAT-SSCR | SMRIN | SMTS | SMUBRID | Isch. time | Time point | Net. |
---|---|---|---|---|---|---|---|---|---|---|---|
All | All | - | - | - | - | - | - | - | - | - | Edg59 GB |
GTEX-111CU-0826-SM-5EGIJ | GTEX-111CU | 1 | 50-59 | 0 | 0 | 8 | Esophagus | 4550 | 81 | Actual Death | |
GTEX-111YS-0826-SM-5GZYK | GTEX-111YS | 1 | 60-69 | 0 | 1 | 7.9 | Esophagus | 4550 | 143 | Actual Death | |
GTEX-1122O-1826-SM-5EGIP | GTEX-1122O | 2 | 60-69 | 0 | 0 | 7.1 | Esophagus | 4550 | 119 | Actual Death | |
GTEX-113JC-1026-SM-5H117 | GTEX-113JC | 2 | 50-59 | 2 | 1 | 6.3 | Esophagus | 4550 | 646 | Actual Death | |
GTEX-1192W-0826-SM-5EGHE | GTEX-1192W | 1 | 60-69 | 2 | 1 | 6.3 | Esophagus | 4550 | 711 | Actual Death | |
GTEX-1192X-1826-SM-5GIE2 | GTEX-1192X | 1 | 50-59 | 4 | 1 | 6.2 | Esophagus | 4550 | 928 | Actual Death | |
GTEX-11DXX-1226-SM-5GICD | GTEX-11DXX | 2 | 60-69 | 0 | 1 | 8.1 | Esophagus | 4550 | 109 | Actual Death | |
GTEX-11DXY-1326-SM-5987Z | GTEX-11DXY | 1 | 60-69 | 2 | 0 | 7.1 | Esophagus | 4550 | 915 | Presumed Death | |
GTEX-11DXZ-1026-SM-5N9D5 | GTEX-11DXZ | 1 | 50-59 | 0 | 0 | 8.6 | Esophagus | 4550 | 293 | Actual Death |