Read Oarfish single-cell quantifications

With --single-cell, Oarfish quantifies a transcriptome-aligned BAM whose reads carry a cell barcode (CB:Z tag) and writes, next to its output prefix, <prefix>.count.mtx (a Matrix Market table of cells by transcripts), <prefix>.barcodes.txt, <prefix>.features.txt and <prefix>.meta_info.json. It draws no replicates in this mode.

Usage

read_oarfish_sc_counts(path, ignore_after_bar = TRUE)

read_oarfish_sc(
  path,
  cells,
  annot_path,
  col_data = NULL,
  experiment_name = NULL,
  min_cells = 1L,
  ignore_after_bar = TRUE,
  drop_unannotated = FALSE
)

Arguments

path

The output prefix of Oarfish (the value of -o), the .count.mtx file, or a directory holding a single .count.mtx file.

ignore_after_bar

Logical. Keep only the part of transcript names before the first | (GENCODE FASTA headers used as Salmon references).

cells

A data frame with a barcode column and a sample_id column.

annot_path

Annotation directory or GFF3/GTF file (see prepare_isoformic_annotation()).

col_data

Optional sample metadata with a sample_id column; the number of cells and reads of each sample are added as n_cells and n_reads.

experiment_name

Optional experiment name.

min_cells

Samples with fewer cells are dropped.

drop_unannotated

Logical. Drop transcripts absent from the annotation (with a message) instead of failing.

Value

read_oarfish_sc_counts(): a tibble with barcode, transcript_id and count. read_oarfish_sc(): an IsoformicExperiment.

Details

• read_oarfish_sc_counts() returns the non-zero counts as a long table, one row per cell and transcript.

• read_oarfish_sc() sums the cells of each sample (a pseudobulk) and returns an IsoformicExperiment with counts, length (from the annotation) and abundance (TPM computed from both) assays, so the isoform analyses of the package apply to single-cell data at the level of samples or cell types. cells says which sample each barcode belongs to; barcodes absent from it are dropped. To compare cell types, give each combination of sample and cell type its own sample_id and describe it in col_data.

Examples

dir <- system.file("extdata", "oarfish_sc", package = "isoformic")
counts <- read_oarfish_sc_counts(file.path(dir, "out"))
head(counts)
#> # A tibble: 6 × 3
#>   barcode          transcript_id     count
#>   <chr>            <chr>             <dbl>
#> 1 CGGCGCGAACCACCTC ENST00000512351.5  1   
#> 2 CGGCGCGAACCACCTC ENST00000345843.7  1.26
#> 3 CGGCGCGAACCACCTC ENST00000342295.5  5.86
#> 4 CGGCGCGAACCACCTC ENST00000514380.5  1.13
#> 5 CGGCGCGAACCACCTC ENST00000355476.7  5.63
#> 6 CGGCGCGAACCACCTC ENST00000511401.5  6   
cells <- read.delim(file.path(dir, "cells.tsv"))
iso <- read_oarfish_sc(
  file.path(dir, "out"),
  cells = cells,
  annot_path = system.file(
    "extdata", "example_experiment", "annotation",
    package = "isoformic"
  )
)
col_data(iso)
#> # A tibble: 3 × 3
#>   sample_id n_cells n_reads
#>   <chr>       <int>   <dbl>
#> 1 control_1      20   3000.
#> 2 control_2      20   3000.
#> 3 treated_1      20   3000.