A Suite of Methods for Network-Based Proteomics

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Documentation for package ‘NetProt’ version 0.1

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CR This is the CR colorectal cancer data to be included in my package
essnet Based on the output of internal_substraction, this calculates a p-value for each complex
fsnet Based on the rank weight matrix and the list of complexes, give a matrix of scores per complex
generate_proteomics_sim Proteomics data simulation function
generate_rank_matrix Generates a rank matrix
generate_weight_matrix Generates a weight matrix by applying the generate weight vector function to all columns
generate_weight_vector Generates a weight vector
gsea The original GSEA algorithm based on the Kolmogorov-Smirnov
he The hypergeometric enrichment pipeline
hello Hello, World!
internal_substraction This generates all paired differences, deltas, for each gene between samples in class A and B
my.t.test.p.value A test function for the t-test
pfsnet_theoretical_t_test Uses the original FSNET matrix but applies PFSNET's calculation method
ppfsnet_theoretical_t_test Uses the original FSNET matrix but applies PPFSNET's calculation method
qpsp QPSP rank matrix generation function
qpsp_generate_rank_matrix QPSP rank matrix generation function
qpsp_standard_t_test This generates a vector of p-values for a data matrix using the two-sample t-test
RC This is the RC renal cancer data to be included in my package
RCC This is the RCC renal cancer control data to be included in my package
snet_generate_weight_matrix Generates a matrix of snet weights for a given data matrix
snet_weight_vector Generates a vector of snet weights for a given sample
standard_t_test This generates a vector of p-values for a data matrix using the two-sample t-test
subset_weights Generates a modulated weight matrix