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

PairwiseDESeq2,GetContrasts

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))


[Package grandR version 0.2.5 Index]