LFQ {DEP} | R Documentation |
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.
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)
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 |
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. |
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 |
data <- UbiLength expdesign <- UbiLength_ExpDesign results <- LFQ(data, expdesign, 'MinProb', 'control', 'Ctrl')