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 | - | - | - | - | - | - | - | - | - | Edg118 GB |
GTEX-1117F-0526-SM-5EGHJ | GTEX-1117F | 2 | 60-69 | 4 | 0 | 8 | Blood Vessel | 7610 | 1221 | Actual Death | |
GTEX-111FC-0426-SM-5N9CV | GTEX-111FC | 1 | 60-69 | 1 | 1 | 7.8 | Blood Vessel | 7610 | 1046 | Presumed Death | |
GTEX-111YS-2226-SM-5987P | GTEX-111YS | 1 | 60-69 | 0 | 1 | 7.8 | Blood Vessel | 7610 | 292 | Actual Death | |
GTEX-1128S-2526-SM-5H11N | GTEX-1128S | 2 | 60-69 | 2 | 0 | 6.1 | Blood Vessel | 7610 | 889 | Actual Death | |
GTEX-113IC-0426-SM-5HL5O | GTEX-113IC | 1 | 60-69 | - | 0 | 8.3 | Blood Vessel | 7610 | 101 | Presumed Death | |
GTEX-117YW-2726-SM-5GZZT | GTEX-117YW | 1 | 50-59 | 3 | 1 | 7.7 | Blood Vessel | 7610 | 984 | Actual Death | |
GTEX-117YX-2626-SM-5EQ53 | GTEX-117YX | 1 | 50-59 | 0 | 1 | 7.1 | Blood Vessel | 7610 | 151 | Actual Death | |
GTEX-11DXW-0526-SM-5H127 | GTEX-11DXW | 1 | 40-49 | 2 | 1 | 7.8 | Blood Vessel | 7610 | 1096 | Actual Death | |
GTEX-11DXX-2626-SM-5Q5A3 | GTEX-11DXX | 2 | 60-69 | 0 | 1 | 7.2 | Blood Vessel | 7610 | 165 | Actual Death |