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.

SampleSubjectGender
AgeDTH-HRDY
SMAT-SSCR
SMRIN
SMTS
SMUBRID
Isch. time
Time point
Net.
All All - - - - - - - - -
Edg78 GB
GTEX-1117F-1326-SM-5EGHH GTEX-1117F 2 60-69 4 1 5.9 Adipose Tissue 10414 1277 Actual Death
Adj369 MBVis
GTEX-111CU-1026-SM-5EGIL GTEX-111CU 1 50-59 0 0 7.4 Adipose Tissue 10414 84 Actual Death
Adj369 MBVis
GTEX-111YS-1326-SM-5EGGK GTEX-111YS 1 60-69 0 0 7.9 Adipose Tissue 10414 156 Actual Death
Adj369 MBVis
GTEX-1122O-0926-SM-5N9C9 GTEX-1122O 2 60-69 0 0 5.8 Adipose Tissue 10414 93 Actual Death
Adj369 MBVis
GTEX-1128S-0926-SM-5GZZU GTEX-1128S 2 60-69 2 1 6.5 Adipose Tissue 10414 844 Actual Death
Adj369 MBVis
GTEX-113JC-0726-SM-5GZZR GTEX-113JC 2 50-59 2 1 7 Adipose Tissue 10414 639 Actual Death
Adj369 MBVis
GTEX-117YW-0826-SM-5H11O GTEX-117YW 1 50-59 3 0 6.4 Adipose Tissue 10414 838 Actual Death
Adj369 MBVis
GTEX-117YX-0726-SM-5GIET GTEX-117YX 1 50-59 0 0 8.8 Adipose Tissue 10414 91 Actual Death
Adj369 MBVis
GTEX-1192X-1526-SM-5H11I GTEX-1192X 1 50-59 4 1 5.8 Adipose Tissue 10414 910 Actual Death
Adj369 MBVis
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