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The function separates a single multi-quantification integration
matrix, obtained via comparison_matrix, into single
quantification matrices as a named list of tibbles.
| separate_quant_matrices {ISAnalytics} | R Documentation |
The function separates a single multi-quantification integration
matrix, obtained via comparison_matrix, into single
quantification matrices as a named list of tibbles.
separate_quant_matrices( x, fragmentEstimate = "fragmentEstimate", seqCount = "seqCount", barcodeCount = "barcodeCount", cellCount = "cellCount", ShsCount = "ShsCount" )
x |
Single integration matrix with multiple quantification value columns, likely obtained via comparison_matrix. |
fragmentEstimate |
Name of the fragment estimate values column in input |
seqCount |
Name of the sequence count values column in input |
barcodeCount |
Name of the barcode count values column in input |
cellCount |
Name of the cell count values column in input |
ShsCount |
Name of the shs count values column in input |
A named list of tibbles, where names are quantification types
Other Analysis functions:
CIS_grubbs(),
comparison_matrix(),
compute_abundance(),
cumulative_count_union(),
sample_statistics(),
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")
association_file <- import_association_file(path = path, root = root,
dates_format = "dmy")
matrices <- import_parallel_Vispa2Matrices_auto(
association_file = association_file,
quantification_type = c("seqCount", "fragmentEstimate"),
matrix_type = "annotated", workers = 2, patterns = NULL,
matching_opt = "ANY"
)
separated_matrix <- separate_quant_matrices(matrices)
options(op)