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", key = c(mandatory_IS_vars(), annotation_IS_vars(), "CompleteAmplificationID") )
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 |
key |
Key columns to perform the joining operation |
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)