LFC {grandR} | R Documentation |
Estimation of log2 fold changes
Description
Estimate the log fold changes based on a contrast matrix, requires the LFC package.
Usage
LFC(
data,
name.prefix = mode,
contrasts,
slot = "count",
LFC.fun = lfc::PsiLFC,
mode = "total",
normalization = NULL,
compute.M = TRUE,
genes = NULL,
verbose = FALSE,
...
)
Arguments
data |
the grandR object |
name.prefix |
the prefix for the new analysis name; a dot and the column names of the contrast matrix are appended; can be NULL (then only the contrast matrix names are used) |
contrasts |
contrast matrix that defines all pairwise comparisons, generated using GetContrasts |
slot |
the slot of the grandR object to take the data from; for PsiLFC, this really should be "count"! |
LFC.fun |
function to compute log fold changes (default: PsiLFC, other viable option: NormLFC) |
mode |
compute LFCs for "total", "new", or "old" RNA |
normalization |
normalize on "total", "new", or "old" (see details) |
compute.M |
also compute the mean expression (in log10 space) |
genes |
restrict analysis to these genes; NULL means all genes |
verbose |
print status messages? |
... |
further arguments forwarded to LFC.fun |
Details
Both PsiLFC and NormLFC) by default perform normalization by subtracting the median log2 fold change from all log2 fold changes. When computing LFCs of new RNA, it might be sensible to normalize w.r.t. to total RNA, i.e. subtract the median log2 fold change of total RNA from all the log2 fold change of new RNA. This can be accomplished by setting mode to "new", and normalization to "total"!
Normalization can also be a mode.slot! Importantly, do not specify a slot containing normalized values, but specify a slot of unnormalized values (which are used to compute the size factors for normalization!) Can also be a numeric vector of size factors with the same length as the data as columns. Then each value is divided by the corresponding size factor entry.
Value
a new grandR object including a new analysis table. The columns of the new analysis table are
"LFC" |
the log2 fold change |
See Also
Examples
sars <- ReadGRAND(system.file("extdata", "sars.tsv.gz", package = "grandR"),
design=c(Design$Condition,Design$dur.4sU,Design$Replicate))
sars <- subset(sars,Coldata(sars,Design$dur.4sU)==2)
sars<-LFC(sars,mode="total",contrasts=GetContrasts(sars,contrast=c("Condition","Mock")))
sars<-LFC(sars,mode="new",normalization="total",
contrasts=GetContrasts(sars,contrast=c("Condition","Mock")))
head(GetAnalysisTable(sars))