LFQ: LFQ workflow

In DEP: Differential Enrichment analysis of Proteomics data

Description

LFQ is a wrapper function running the entire differential enrichment/expression analysis workflow for label free quantification (LFQ)-based proteomics data. The protein table from MaxQuant is used as direct input.

Usage

LFQ(proteins, expdesign, fun = c("man", "bpca", "knn", "QRILC", "MLE",
  "MinDet", "MinProb", "min", "zero", "mixed", "nbavg"), type = c("all",
  "control", "manual"), control = NULL, test = NULL,
  filter = c("Reverse", "Potential.contaminant"), name = "Gene.names",
  ids = "Protein.IDs", alpha = 0.05, lfc = 1)

Arguments

proteins	Data.frame, The data object.
expdesign	Data.frame, The experimental design object.
fun	"man", "bpca", "knn", "QRILC", "MLE", "MinDet", "MinProb", "min", "zero", "mixed" or "nbavg", Function used for data imputation based on manual_impute and impute.
type	'all', 'control' or 'manual', The type of contrasts that will be generated.
control	Character(1), The sample name to which the contrasts are generated (the control sample would be most appropriate).
test	Character, The contrasts that will be tested if type = "manual". These should be formatted as "SampleA_vs_SampleB" or c("SampleA_vs_SampleC", "SampleB_vs_SampleC").
filter	Character, Name(s) of the column(s) to be filtered on.
name	Character(1), Name of the column representing gene names.
ids	'Character(1), Name of the column representing protein IDs.
alpha	Numeric(1), sets the false discovery rate threshold.
lfc	Numeric(1), sets the log fold change threshold.

Value

A list of 9 objects:

data	data.frame containing the original data
se	SummarizedExperiment object containing the original data
filt	SummarizedExperiment object containing the filtered data
norm	SummarizedExperiment object containing the normalized data
imputed	SummarizedExperiment object containing the imputed data
diff	SummarizedExperiment object containing FDR estimates of differential expression
dep	SummarizedExperiment object annotated with logical columns indicating significant proteins
results	data.frame containing containing all results variables from the performed analysis
param	data.frame containing the test parameters

Examples

data <- UbiLength
expdesign <- UbiLength_ExpDesign
results <- LFQ(data, expdesign, 'MinProb', 'control', 'Ctrl')

DEP documentation built on Nov. 8, 2020, 7:49 p.m.