runTPCA: Run the TPCA analysis

In nkurzaw/Rtpca: Thermal proximity co-aggregation with R

Run the TPCA analysis

Description

Run the TPCA analysis

Usage

runTPCA(
  objList,
  complexAnno = NULL,
  ppiAnno = NULL,
  rownameCol = NULL,
  summaryMethodStr = "median",
  distMethodStr = "euclidean",
  doRocAnalysis = TRUE,
  minCount = 3,
  nSamp = 10000,
  p_adj_method = "BH"
)

Arguments

objList	inout list of objects, e.g. ExpressionSets retrieved after TPP data import or matrices or data frames
complexAnno	data frame annotating known protein complexes of interest to test
ppiAnno	data frame annotation known protein-protein interactions (PPI) to test
rownameCol	in case the input objects are tibbles this parameter takes in the name (character) of the column specifying protein names or ids
summaryMethodStr	character string indicating a method to use to summarize measurements across replicates, default is "median", other options are c("mean", "rbind")
distMethodStr	method to use within dist function, default is 'euclidean'
doRocAnalysis	logical indicating whether a ROC analysis should be performed which can be used to assess the predictive power of the dataset for protein-protein interactions / protein complexes based on distanc between melting curves of protein interactions partners
minCount	integer indicating how many subunits of a complex should be qunatified to inlucde it into the analysis, default is 3
nSamp	integer indicating the number of random samples which should be performed to estimate empirical null distributions, default is 10000
p_adj_method	character string indicating a valid method to be used for multiple testing adjusment, default is "BH" which makes p.adjust use benjamini-hochberg, for additional options check ?p.adjust

Value

an object of class tpcaResult with the following slots: 1) ObjList: containing the supplied list of objects

Examples

 
m1 <- matrix(1:12, ncol = 4)
m2 <- matrix(2:13, ncol = 4)
m3 <- matrix(c(2:10, 1:7), ncol = 4)

rownames(m1) <- 1:3
rownames(m2) <- 2:4
rownames(m3) <- 2:5

colnames(m1) <- paste0("X", 1:4)
colnames(m2) <- paste0("X", 1:4)
colnames(m3) <- paste0("X", 1:4)

mat_list <- list(
    m1, m2, m3
)

ppi_anno <- tibble(
    x = "2",
    y = "3",
    combined_score = 700,
    pair = "2:3")

runTPCA(
    objList = mat_list,
    complexAnno = NULL,
    ppiAnno = ppi_anno
)

nkurzaw/Rtpca documentation built on May 12, 2023, 2:10 p.m.