dbFrame-methods {CATALYST} | R Documentation |
dbFrame
Methods for replacing and accessing slots in a dbFrame
.
bc_key(x) bc_ids(x) deltas(x) normed_bcs(x) mhl_dists(x) sep_cutoffs(x) mhl_cutoff(x) counts(x) yields(x) ## S4 method for signature 'dbFrame' exprs(object) ## S4 method for signature 'dbFrame' bc_key(x) ## S4 method for signature 'dbFrame' bc_ids(x) ## S4 method for signature 'dbFrame' deltas(x) ## S4 method for signature 'dbFrame' normed_bcs(x) ## S4 method for signature 'dbFrame' mhl_dists(x) ## S4 method for signature 'dbFrame' sep_cutoffs(x) ## S4 method for signature 'dbFrame' mhl_cutoff(x) ## S4 method for signature 'dbFrame' counts(x) ## S4 method for signature 'dbFrame' yields(x) ## S4 replacement method for signature 'dbFrame,numeric' mhl_cutoff(x) <- value ## S4 replacement method for signature 'dbFrame,ANY' mhl_cutoff(x) <- value ## S4 replacement method for signature 'dbFrame,numeric' sep_cutoffs(x) <- value ## S4 replacement method for signature 'dbFrame,ANY' sep_cutoffs(x) <- value
x, object |
a |
value |
the replacement value. |
exprs
extracts the raw data intensities.
bc_key
extracts the barcoding scheme.
bc_ids
extracts currently made event assignments.
deltas
extracts barcode separations computed from normalized
intensities. sep_cutoffs
apply to these values
(see applyCutoffs
).
normed_bcs
extracts normalized barcode intensities
(see assignPrelim
).
sep_cutoffs
, sep_cutoffs<-
extracts or replaces
separation cutoffs. If option sep_cutoffs
is not specified, these will
be used by applyCutoffs
. Replacement value must be a non-
negative numeric with length one or same length as the number of barcodes.
mhl_cutoff
, mhl_cutoff<-
extracts or replaces the Mahalanobis distance threshold above which events are to be unassigned. Replacement value must be a single non-negative and non-zero numeric.
counts
extract the counts matrix (see dbFrame
).
yields
extract the yields matrix (see dbFrame
).
Helena Lucia Crowell helena.crowell@uzh.ch
data(sample_ff, sample_key) re <- assignPrelim(x = sample_ff, y = sample_key) # set global cutoff parameter sep_cutoffs(re) <- 0.4 re <- applyCutoffs(x = re) # subset a specific population, e.g. A1: 111000 a1 <- bc_ids(re) == "A1" head(exprs(sample_ff[a1, ])) # subset unassigned events unassigned <- bc_ids(re) == 0 head(exprs(sample_ff[unassigned, ]))