impute_missing_abundance | R Documentation |
impute_missing_abundance() takes as input A 'tbl' (with at least three columns for sample, feature and transcript abundance) or 'SummarizedExperiment' (more convenient if abstracted to tibble with library(tidySummarizedExperiment)) and returns a consistent object (to the input) with additional sample-transcript pairs with imputed transcript abundance.
impute_missing_abundance(
.data,
.formula,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
suffix = "",
force_scaling = FALSE
)
## S4 method for signature 'spec_tbl_df'
impute_missing_abundance(
.data,
.formula,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
suffix = "",
force_scaling = FALSE
)
## S4 method for signature 'tbl_df'
impute_missing_abundance(
.data,
.formula,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
suffix = "",
force_scaling = FALSE
)
## S4 method for signature 'tidybulk'
impute_missing_abundance(
.data,
.formula,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
suffix = "",
force_scaling = FALSE
)
## S4 method for signature 'SummarizedExperiment'
impute_missing_abundance(
.data,
.formula,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
suffix = "",
force_scaling = FALSE
)
## S4 method for signature 'RangedSummarizedExperiment'
impute_missing_abundance(
.data,
.formula,
.sample = NULL,
.transcript = NULL,
.abundance = NULL,
suffix = "",
force_scaling = FALSE
)
.data |
A 'tbl' (with at least three columns for sample, feature and transcript abundance) or 'SummarizedExperiment' (more convenient if abstracted to tibble with library(tidySummarizedExperiment)) |
.formula |
A formula with no response variable, representing the desired linear model where the first covariate is the factor of interest and the second covariate is the unwanted variation (of the kind ~ factor_of_interest + batch) |
.sample |
The name of the sample column |
.transcript |
The name of the transcript/gene column |
.abundance |
The name of the transcript/gene abundance column |
suffix |
A character string. This is added to the imputed count column names. If empty the count column are overwritten |
force_scaling |
A boolean. In case a abundance-containing column is not scaled (columns with _scale suffix), setting force_scaling = TRUE will result in a scaling by library size, to compensating for a possible difference in sequencing depth. |
'r lifecycle::badge("maturing")'
This function imputes the abundance of missing sample-transcript pair using the median of the sample group defined by the formula
A consistent object (to the input) non-sparse abundance
A consistent object (to the input) with imputed abundance
A consistent object (to the input) with imputed abundance
A consistent object (to the input) with imputed abundance
A 'SummarizedExperiment' object
A 'SummarizedExperiment' object
res =
impute_missing_abundance(
tidybulk::se_mini,
~ condition
)
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