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. 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.
|1||Skeletal muscle||PANDA||netZooM 0.1||Motif||TF||644||30243||469||D|
|2||Skeletal muscle||PANDA-LIONESS||netZooM 0.1||Motif||TF||644||30243||469||D|
|3||Skeletal muscle||PUMA||netZooM 0.3||-||miRanda||miRNA||643||16161||119||D|
|4||Skeletal muscle||PUMA||netZooM 0.3||-||TargetScan||miRNA||643||16161||119||D|
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 TFs * number of genes) (~ 106). Otherwise, you can specify the sample network to download and you will get a TF-by-gene matrix named after the GTEx sample reference.