init | R Documentation |
This function creates a dataset (an object of class rcongasplus
) by assembling multiple single-cell input measurements
(ATAC and/or RNA data modalities), the input segmentation (from bulk DNA sequencing),
and the per-cell normalisation factors for the data.
All input data are passed as tibbles; the input formats are as follows:
for single-cell ATAC/RNA data, the cell
identifier, the genomic coordinates
(chr
, from
, to
) which refer either to an ATAC peak, or an RNA gene
identifier, and a value
reporting the reads mapped.
for the input segmentation, the genomic coordinates
(chr
, from
, to
) which refer to the segment, and the number of
copies
(i.e., DNA ploidy) of the segment.
for normalization factors the cell
identifier, the actual normalisation_factor
and the modality
to wihch the factor refers to
This function receives also other parameters - e.g., the models likelihoods - which will determine the overall behaviour of the underlying model, and how data are preared for inference.
A Negative Binomial likelihood ("NB"
), which works directly from raw counts data
A Gaussian likelihood ("G"
), which requires a z-score transformation of the data. This consists
in :
scaling raw counts by the input normalization factors;
computing z-scores per cell;
summing up z-scores per segment;
computing z-scores per segment;
center the z-scores mean to the input ploidy.
init(
rna,
atac,
segmentation,
rna_normalisation_factors = rna %>% auto_normalisation_factor(),
atac_normalisation_factors = atac %>% auto_normalisation_factor(),
rna_likelihood = "NB",
atac_likelihood = "NB",
reference_genome = "GRCh38",
description = "(R)CONGAS+ model",
smooth = FALSE,
multiome = FALSE
)
rna |
A tibble with single-cell RNA data. |
atac |
A tibble with single-cell ATAC data. |
segmentation |
A tibble with the input segmentation. |
rna_normalisation_factors |
The RNA tibble with the input per-cell normalisation factors.
By default these are computed by function |
atac_normalisation_factors |
The ATAC tibble with the input per-cell normalisation factors.
By default these are computed by function |
rna_likelihood |
Type of likelihood used for RNA data ( |
atac_likelihood |
Type of likelihood used for ATAC data, with default |
reference_genome |
Either |
description |
A model in-words description. |
smooth |
If yes, input segments are smootheed by joining per chromosome segments that have the same ploidy. |
mutiome |
Default to FALSE. Flag indicating whether the RNA and ATAC observations are the result of a matched RNA-ATAC sequencing assay such as 10x multiome assay. (i.e., there is a 1:1 correspondence between barcodes of the two modalities.) |
An object of class rcongasplus
data("example_input")
# For instance, RNA data
example_input$x_rna %>% print
# .. or ATAC data
example_input$x_atac %>% print
# .. and segmentation
example_input$x_segmentation %>% print
# .. and normalisation factors can be computed (default)
example_input$x_rna %>% auto_normalisation_factor()
x = init(
rna = example_input$x_rna,
atac = example_input$x_atac,
segmentation = example_input$x_segmentation,
rna_likelihood = "G",
atac_likelihood = 'NB',
description = 'My model')
print(x)
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