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VAM - Variance-Adjusted Mahalanobis

Contains logic for cell-specific gene set scoring of single cell RNA sequencing data.

Last updated

5.18 score 4 dependents 25 scripts 545 downloads

RESET - Reconstruction Set Test

Contains logic for sample-level variable set scoring using randomized reduced rank reconstruction error. Frost, H. Robert (2023) "Reconstruction Set Test (RESET): a computationally efficient method for single sample gene set testing based on randomized reduced rank reconstruction error" <doi:10.1101/2023.04.03.535366>.

Last updated

2.30 score 10 scripts 242 downloads

TPAC - Tissue-Adjusted Pathway Analysis of Cancer (TPAC)

Contains logic for single sample gene set testing of cancer transcriptomic data with adjustment for normal tissue-specificity. Frost, H. Robert (2023) "Tissue-adjusted pathway analysis of cancer (TPAC)" <doi:10.1101/2022.03.17.484779>.

Last updated

2.00 score 162 downloads

EESPCA - Eigenvectors from Eigenvalues Sparse Principal Component Analysis (EESPCA)

Contains logic for computing sparse principal components via the EESPCA method, which is based on an approximation of the eigenvector/eigenvalue identity. Includes logic to support execution of the TPower and rifle sparse PCA methods, as well as logic to estimate the sparsity parameters used by EESPCA, TPower and rifle via cross-validation to minimize the out-of-sample reconstruction error. H. Robert Frost (2021) <doi:10.1080/10618600.2021.1987254>.

Last updated

2.00 score 1 stars 2 scripts 232 downloads

TPACData - Human Protein Atlas Data for Tissue-Adjusted Pathway Analysis of Cancer (TPAC)

Contains summary data on gene expression in normal human tissues from the Human Protein Atlas for use with the Tissue-Adjusted Pathway Analysis of cancer (TPAC) method. Frost, H. Robert (2023) "Tissue-adjusted pathway analysis of cancer (TPAC)" <doi:10.1101/2022.03.17.484779>.

Last updated

1.48 score 1 dependents 178 downloads

PCGSE - Principal Component Gene Set Enrichment

Contains logic for computing the statistical association of variable groups, i.e., gene sets, with respect to the principal components of genomic data.

Last updated

1.48 score 1 stars 3 scripts 205 downloads