gsvaTest: Perform GSVA tests

In qzhang503/proteoQ: Processing and Informatic Analysis of Mass Spectrometrirc Data

Perform GSVA tests

Description

logFC_cutoff subsets data for adjusted pvals

Usage

gsvaTest(
  df = NULL,
  id = "entrez",
  label_scheme_sub = NULL,
  filepath = NULL,
  filename = NULL,
  scale_log2r = TRUE,
  complete_cases = FALSE,
  impute_na = FALSE,
  gset_nms = "go_sets",
  lm_method = "limma",
  padj_method = "BH",
  var_cutoff = 0.5,
  pval_cutoff = 1e-04,
  logFC_cutoff = log2(1.1),
  anal_type = "GSVA",
  ...
)

Arguments

df	The name of a primary data file. By default, it will be determined automatically after matching the types of data and analysis with an id among c("pep_seq", "pep_seq_mod", "prot_acc", "gene"). A primary file contains normalized peptide or protein data and is among c("Peptide.txt", "Peptide_pVal.txt", "Peptide_impNA_pVal.txt", "Protein.txt", "Protein_pVal.txt", "protein_impNA_pVal.txt"). For analyses require the fields of significance p-values, the df will be one of c("Peptide_pVal.txt", "Peptide_impNA_pVal.txt", "Protein_pVal.txt", "protein_impNA_pVal.txt").
id	Character string; one of pep_seq, pep_seq_mod, prot_acc and gene.
label_scheme_sub	A data frame. Subset entries from label_scheme for selected samples.
filepath	Use system default.
filename	A representative file name to outputs. By default, it will be determined automatically by the name of the current call.
scale_log2r	Logical; if TRUE, adjusts log2FC to the same scale of standard deviation across all samples. The default is TRUE. At scale_log2r = NA, the raw log2FC without normalization will be used.
complete_cases	Logical; if TRUE, only cases that are complete with no missing values will be used. The default is FALSE.
impute_na	Logical; if TRUE, data with the imputation of missing values will be used. The default is FALSE.
gset_nms	Character string or vector containing the shorthanded name(s), full file path(s), or both, to gene sets for enrichment analysis. For species among "human", "mouse", "rat", the default of c("go_sets", "c2_msig", "kinsub") will utilize terms from gene ontology (GO), molecular signatures (MSig) and kinase-substrate network (PSP Kinase-Substrate). Custom GO, MSig and other data bases at given species are also supported. See also: prepGO for the preparation of custom GO; prepMSig for the preparation of custom MSig. For other custom data bases, follow the same format of list as GO or MSig.
lm_method	Character string indicating the linear modeling method for significance assessment of GSVA enrichment scores. The default is limma. At method = lm, the lm() in base R will be used for models without random effects and the lmer will be used for models with random effects.
padj_method	Character string; the method of multiple-test corrections for uses with p.adjust. The default is "BH". See ?p.adjust.methods for additional choices.
var_cutoff	Numeric; the cut-off in the variances of protein log2FC. Entries with variances smaller than the threshold will be removed from GSVA. The default is 0.5.
pval_cutoff	Numeric; the cut-off in enrichment pVals. Terms with enrichment pVals smaller than the threshold will be removed from multiple test corrections. The default is 1e-04.
logFC_cutoff	Numeric; the cut-off in enrichment log2FC. Terms with absolute log2FC smaller than the threshold will be removed from multiple test corrections. The default is at log2(1.1).
anal_type	Character string; the type of analysis that are preset for method dispatch in function factories. The value will be determined automatically. Exemplary values include anal_type = c("PCA", "Corrplot", "EucDist", "GSPA", "Heatmap", "Histogram", "MDS", "Model", "NMF", "Purge", "Trend", "LDA", ...).
...	filter_: Logical expression(s) for the row filtration against data in a primary file of /Model/Protein[_impNA]_pVals.txt. See also normPSM for the format of filter_ statements. arrange_: Variable argument statements for the row ordering against data in a primary file linked to df. See also prnHM for the format of arrange_ statements. Additional arguments for gsva

qzhang503/proteoQ documentation built on Dec. 14, 2024, 12:27 p.m.