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    v0.1 cell line networks
    v0.2 aggregate tissue networks
    v0.3 TF enrichement tool
    v0.4 single-sample tissue networks
    v0.5 CLUEreg tool
    v0.6 colon cancer networks
    v0.7 drug networks
    v0.7.1 API v1
    v0.8 liver, cervix, and breast cancer networks
    v0.9 miRNA tissue networks
    v0.9.1 bootstrap 5
    v1.0 glioblastoma networks

    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. 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.

    Publication
    Please check the reference Sonawane et al. (2017) at the following link.
    Publication
    Please check the reference Lopes-Ramos et al. (2020) at the following link.
    Publication
    Please check the reference Kuijjer et al. (2020) at the following link.
    Publication
    Please check the reference Kuijjer et al. (2020) at the following link.
    # Tissue Tool netZoo release Network
    PPI
    Reg. prior Expr.
    Reg.
    nReg
    Genes Samples Precision
    Reference
    1 Skeletal muscle PANDA netZooM 0.1
    coR
    Motif TF 644 30243 469 D
    2 Skeletal muscle PANDA-LIONESS netZooM 0.1
    coR
    Motif TF 644 30243 469 D
    3 Skeletal muscle PUMA netZooM 0.3
    coR
    - miRanda miRNA 643 16161 119 D
    4 Skeletal muscle PUMA netZooM 0.3
    coR
    - TargetScan miRNA 643 16161 119 D

    Variable description

    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.

    Sample Subject Gender
    Age DTH-HRDY
    SMAT-SSCR
    SMRIN
    SMTS
    SMTSD
    SMUBRID
    SMTSISCH
    Network
    Contact

    Department of Biostatistics
    Harvard T.H. Chan School of Public Health

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