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 | - | - | - | - | - | - | - | - | - | Edg82 GB |
GTEX-111YS-0526-SM-5GZXJ | GTEX-111YS | 1 | 60-69 | 0 | 1 | 7.9 | Blood Vessel | 1496 | 128 | Actual Death | |
GTEX-1122O-1126-SM-5NQ8X | GTEX-1122O | 2 | 60-69 | 0 | 0 | 7.1 | Blood Vessel | 1496 | 64 | Actual Death | |
GTEX-1128S-0326-SM-5GZZF | GTEX-1128S | 2 | 60-69 | 2 | 1 | 6 | Blood Vessel | 1496 | 828 | Actual Death | |
GTEX-117XS-0426-SM-5GZZN | GTEX-117XS | 1 | 60-69 | 2 | 1 | 6.6 | Blood Vessel | 1496 | 857 | Actual Death | |
GTEX-117YW-0226-SM-5N9CM | GTEX-117YW | 1 | 50-59 | 3 | 1 | 6.5 | Blood Vessel | 1496 | 815 | Actual Death | |
GTEX-11DXX-0426-SM-5EQ5F | GTEX-11DXX | 2 | 60-69 | 0 | 0 | 7.2 | Blood Vessel | 1496 | 90 | Actual Death | |
GTEX-11DXZ-0426-SM-5987Y | GTEX-11DXZ | 1 | 50-59 | 0 | 1 | 6.1 | Blood Vessel | 1496 | 270 | Actual Death | |
GTEX-11DYG-1226-SM-5N9DC | GTEX-11DYG | 1 | 60-69 | 2 | 1 | 6.7 | Blood Vessel | 1496 | 858 | Actual Death | |
GTEX-11EM3-0226-SM-5985Y | GTEX-11EM3 | 2 | 20-29 | 0 | 1 | 7 | Blood Vessel | 1496 | 104 | Actual Death |