aggregate | R Documentation |
Aggregate
aggregate(x, ...)
aggregateCols(x, ...)
aggregateRows(x, ...)
## S4 method for signature 'Matrix'
aggregate(x, by, fun = c("sum", "mean", "n"), MARGIN = 1L)
## S4 method for signature 'SummarizedExperiment'
aggregate(x, col = "aggregate", fun = "sum", MARGIN = 1L)
## S4 method for signature 'matrix'
aggregate(
x,
by,
fun = c("sum", "mean", "median", "geometricMean", "n"),
MARGIN = 1L
)
## S4 method for signature 'Matrix'
aggregateCols(x, ...)
## S4 method for signature 'SummarizedExperiment'
aggregateCols(x, ...)
## S4 method for signature 'matrix'
aggregateCols(x, ...)
## S4 method for signature 'Matrix'
aggregateRows(x, ...)
## S4 method for signature 'SummarizedExperiment'
aggregateRows(x, ...)
## S4 method for signature 'matrix'
aggregateRows(x, ...)
x |
Object. |
by |
|
fun |
|
MARGIN |
|
col |
|
... |
Additional arguments. |
Modified object.
aggregate(SummarizedExperiment)
: Arguments pass through to matrix
or Matrix
method, depending on the class
of matrix defined in requested assay
.
matrix
, Matrix
:
Aggregate using a grouping factor
.
SummarizedExperiment
:
Aggregate data slotted in assays()
using an automatically generated
grouping factor
, which is obtained from a user-defined column
(col
argument) in either the rowData()
or colData()
of the object.
Slot an aggregate
column into rowData()
for aggregateRows()
, or into
colData()
for aggregateCols()
. This method will define the groupings
automatically, and perform the aggregation.
Updated 2021-09-13.
Michael Steinbaugh, Rory Kirchner
stats::aggregate()
.
S4Vectors::aggregate()
.
Matrix.utils::aggregate.Matrix()
.
muscat::aggregateData()
.
counts <- matrix(
data = c(
0L, 2L, 2L, 2L,
2L, 0L, 2L, 2L,
2L, 2L, 0L, 2L,
2L, 2L, 2L, 0L
),
nrow = 4L,
ncol = 4L,
byrow = TRUE,
dimnames = list(
paste0("transcript", seq_len(4L)),
paste(
paste0("sample", rep(seq_len(2L), each = 2L)),
paste0("replicate", rep(seq_len(2L), times = 2L)),
sep = "_"
)
)
)
genes <- factor(paste0("gene", rep(seq_len(2L), each = 2L)))
names(genes) <- rownames(counts)
print(genes)
samples <- factor(paste0("sample", rep(seq_len(2L), each = 2L)))
names(samples) <- colnames(counts)
print(samples)
## matrix ====
object <- counts
print(object)
aggregate(object, by = genes, MARGIN = 1L)
aggregateRows(object, by = genes)
aggregate(object, by = samples, MARGIN = 2L)
aggregateCols(object, by = samples)
## Matrix ====
object <- as(counts, "sparseMatrix")
print(object)
aggregate(object, by = genes, MARGIN = 1L)
aggregateRows(object, by = genes)
aggregate(object, by = samples, MARGIN = 2L)
aggregateCols(object, by = samples)
## SummarizedExperiment ====
object <- SummarizedExperiment::SummarizedExperiment(
assays = S4Vectors::SimpleList(
"counts" = counts
),
rowData = S4Vectors::DataFrame(
"aggregate" = genes
),
colData = S4Vectors::DataFrame(
"sampleName" = as.factor(names(samples)),
"aggregate" = samples
)
)
print(object)
aggregate(object, MARGIN = 1L)
aggregateRows(object)
aggregate(object, MARGIN = 2L)
aggregateCols(object)
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