make_sparse_matrix: Convert the Output of 'kallisto bus' into Gene by Gell Matrix

View source: R/sparse_matrix.R

make_sparse_matrixR Documentation

Convert the Output of kallisto bus into Gene by Gell Matrix


This function takes the output file of kallisto bus, after being sorted and converted into text with bustools. See vignettes on the website of this package for a tutorial. The bustools output has 4 columns: barcode, UMI, equivalence class, and counts. This function converts that file into a sparse matrix that can be used in downstream analyses.


  whitelist = NULL,
  gene_count = TRUE,
  single_gene = TRUE,
  verbose = TRUE,
  progress_unit = 5e+06



Path to the sorted text bus output file.


A Data frame with columns gene and transcript, in the same order as in the transcriptome index for kallisto. This argument can be missing or is ignored if only the TCC matrix, not the gene count matrix, is made.


Estimated number of cells; providing this argument will speed up computation as it minimizes memory reallocation as vectors grow.


Estimated number of genes or equivalence classes.


A character vector with valid cell barcodes. This is an optional argument, that defaults to NULL. When it is NULL, all cell barcodes present that have some UMI assignable to genes or ECs will be included in the sparse matrix whether they are known to be valid or not. Barcodes with only UMIs that are not assignable to genes or ECs will still be excluded.


Logical, whether the gene count matrix should be returned.


Logical, whether the TCC matrix should be returned.


Logical, whether to use single gene mode. In single gene mode, only UMIs that can be uniquely mapped to one gene are kept. Without single gene mode, UMIs mapped to multiple genes will be evenly distributed to those genes.


Whether to display progress.


How many iteration to print one progress update when reading in the kallisto bus file.


This function can generate both the gene count matrix and the transcript compatibility count (TCC) matrix. The TCC matrix has barcodes in the columns and equivalence classes in the rows. See Ntranos et al. 2016 for more information about the RCC matrix.

For 10x data sets, you can find a barcode whitelist file that comes with CellRanger installation. You don't need to run CellRanger to get that. An example path to get the whitelist file is cellranger-2.1.0/cellranger-cs/2.1.0/lib/python/cellranger/barcodes/737K-august-2016.txt for v2 chemistry.


If both gene count and TCC matrices are returned, then this function returns a list with two matrices, each with genes/equivalence classes in the rows and barcodes in the columns. If only one of gene count and TCC matrices is returned, then a dgCMatrix with genes/equivalence classes in the rows and barcodes in the columns. These matrices are unfiltered. Please filter the empty droplets before downstream analysis.

See Also



# Load toy example for testing
toy_path <- system.file("testdata", package = "BUSpaRse")
load(paste(toy_path, "toy_example.RData", sep = "/"))
out_fn <- paste0(toy_path, "/output.sorted.txt")
# With whitelist
m <- make_sparse_matrix(out_fn, tr2g_toy, 10, 3, whitelist = whitelist,
  gene_count = TRUE, TCC = FALSE, single_gene = TRUE,
  verbose = FALSE)

lambdamoses/BUStoolsR documentation built on Aug. 28, 2022, 1:35 p.m.