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Takes a list of integration matrices referring to different qunatification
types and merges them in a single data frame that has multiple
value columns, each renamed according to their quantification type
of reference.
| comparison_matrix {ISAnalytics} | R Documentation |
Takes a list of integration matrices referring to different qunatification
types and merges them in a single data frame that has multiple
value columns, each renamed according to their quantification type
of reference.
comparison_matrix( x, fragmentEstimate = "fragmentEstimate", seqCount = "seqCount", barcodeCount = "barcodeCount", cellCount = "cellCount", ShsCount = "ShsCount" )
x |
A named list of integration matrices, ideally obtained via import_parallel_Vispa2Matrices_interactive or import_parallel_Vispa2Matrices_auto. Names must be quantification types. |
fragmentEstimate |
The name of the output column for fragment estimate values |
seqCount |
The name of the output column for sequence count values |
barcodeCount |
The name of the output column for barcode count values |
cellCount |
The name of the output column for cell count values |
ShsCount |
The name of the output column for Shs count values |
A tibble
Other Analysis functions:
CIS_grubbs(),
compute_abundance(),
cumulative_count_union(),
sample_statistics(),
separate_quant_matrices(),
threshold_filter(),
top_integrations()
op <- options("ISAnalytics.widgets" = FALSE)
path <- system.file("extdata", "ex_association_file.tsv",
package = "ISAnalytics"
)
root_pth <- system.file("extdata", "fs.zip", package = "ISAnalytics")
root <- unzip_file_system(root_pth, "fs")
matrices <- import_parallel_Vispa2Matrices_auto(
association_file = path, root = root,
quantification_type = c("fragmentEstimate", "seqCount"),
matrix_type = "annotated", workers = 2, patterns = NULL,
matching_opt = "ANY",
dates_format = "dmy", multi_quant_matrix = FALSE
)
total_matrix <- comparison_matrix(matrices)
options(op)