dbFrame-class {CATALYST} | R Documentation |
This class represents the data returned by and used throughout debarcoding.
Objects of class dbFrame
hold all data required for debarcoding:
as the initial step of single-cell deconcolution,
assignPrelim
will return a dbFrame
containing
the input measurement data, barcoding scheme, and preliminary assignments.
assignments will be made final by applyCutoffs
.
Optionally, population-specific separation cutoffs may be estimated
by running estCutoffs
prior to this.
plotYields
, plotEvents
and
plotMahal
aim to guide devoncolution parameter selection,
and to give a sense of the resulting barcode assignment quality.
show(dbFrame)
will display
the dimensionality of the measurement data and number of barcodes
current assignments in order of decreasing population size
current separation cutoffs
the mean & per-population yield that'll be achieved upon debarcoding
exprs
a matrix containing raw intensities of the input flowFrame.
bc_key
binary barcoding scheme with numeric masses as column names and samples names as row names OR a numeric vector of barcode masses.
bc_ids
vector of barcode IDs. If a barcoding scheme is supplied, the respective binary code's row name, else, the mass of the respective barcode channel.
deltas
numeric vector of separations between positive and negative barcode populations computed from normalized barcode intensities.
normed_bcs
matrix containing normalized barcode intensities.
mhl_dists
mahalanobis distances.
sep_cutoffs
numeric vector of distance separation cutoffs between positive and negative barcode populations above which events will be unassigned.
mhl_cutoff
non-negative and non-zero numeric value specifying the Mahalanobis distance below which events will be unassigned.
counts
matrix of dimension (# barcodes)x(101) where each row contains the number of events within a barcode for which positive & negative populations are separated by a distance between in [0,0.01), ..., [0.99,1], respectively.
yields
a matrix of dimension (# barcodes)x(101) where each row contains the percentage of events within a barcode that will be obtained after applying a separation cutoff of 0, 0.01, ..., 1, respectively.
Helena Lucia Crowell helena.crowell@uzh.ch