Extraction and replacement methods for objects of class daFrame

Description

Methods for accessing slots in a daFrame.

Usage

n_cells(x)

marker_classes(x)

type_markers(x)

state_markers(x)

sample_ids(x)

cluster_codes(x)

cluster_ids(x)

## S4 method for signature 'daFrame'
exprs(object)

## S4 method for signature 'daFrame'
n_cells(x)

## S4 method for signature 'daFrame'
marker_classes(x)

## S4 method for signature 'daFrame'
type_markers(x)

## S4 method for signature 'daFrame'
state_markers(x)

## S4 method for signature 'daFrame'
sample_ids(x)

## S4 method for signature 'daFrame'
cluster_codes(x)

## S4 method for signature 'daFrame'
cluster_ids(x)

Arguments

Value

exprs

extracts the arcsinh-transformed expressions.

n_cells

extracts the number of events measured per sample.

type_markers

extracts the antigens used for clustering.

state_markers

extracts antigens that were not used for clustering.

sample_ids

extracts the sample IDs as specified in the metadata-table.

cluster_codes

extracts a data.frame containing cluster codes for the FlowSOM clustering, the ConsensusClusterPlus metaclustering, and all mergings done through mergeClusters.

cluster_ids

extracts the numeric vector of cluster IDs as inferred by FlowSOM.

Author(s)

Helena Lucia Crowell crowellh@student.ethz.ch

Examples

# construct daFrame
data(PBMC_fs, PBMC_panel, PBMC_md)
re <- daFrame(PBMC_fs, PBMC_panel, PBMC_md)

# run clustering
lineage <- c("CD3", "CD45", "CD4", "CD20", "CD33", 
    "CD123", "CD14", "IgM", "HLA_DR", "CD7")
re <- cluster(re, cols_to_use=lineage)

# view data summary
library(SummarizedExperiment)
cbind(metadata(re)$experiment_info, cells=n_cells(re))

# access row / cell data
head(rowData(re))
plot(table(cluster_ids(re)))

# access marker information
type_markers(re)
state_markers(re)

# get cluster ID correspondece between 2 clusterings
old_ids <- seq_len(20)
m <- match(old_ids, cluster_codes(re)$`20`)
new_ids <- cluster_codes(re)$`12`[m]
data.frame(old_ids, new_ids)

# plot relative change in area under CDF curve vs. k
metadata(re)$delta_area