Estimate isoform-specific fraction news (or more generally "fractions").
EstimateIsoformFractions.Rd
Combines the output of EstimateFractions
with transcript isoform
quantification performed by an outside tool (e.g., RSEM, kallisto, salmon, etc.)
to infer transcript isoform-specific fraction news (or more generally fraction
of reads coming from a particular mutation population).
Usage
EstimateIsoformFractions(
obj,
features = NULL,
populations = NULL,
fraction_design = NULL,
repeatID = NULL,
exactMatch = TRUE,
fraction_name = NULL,
quant_name = NULL,
gene_to_transcript = NULL,
overwrite = TRUE,
TPM_min = 1,
count_min = 10
)
Arguments
- obj
An
EZbakRData
object- features
Character vector of the set of features you want to stratify reads by and estimate proportions of each RNA population. The default of "all" will use all feature columns in the
obj
's cB.- populations
Mutational populations that were analyzed to generate the fractions table to use. For example, this would be "TC" for a standard s4U-based nucleotide recoding experiment.
- fraction_design
"Design matrix" specifying which RNA populations exist in your samples. By default, this will be created automatically and will assume that all combinations of the
mutrate_populations
you have requested to analyze are present in your data. If this is not the case for your data, then you will have to create one manually. See docs forEstimateFractions
(run ?EstimateFractions()) for more details.- repeatID
If multiple
fractions
tables exist with the same metadata, then this is the numerical index by which they are distinguished.- exactMatch
If TRUE, then
features
andpopulations
have to exactly match those for a given fractions table for that table to be used. Means that you can't specify a subset of features or populations by default, since this is TRUE by default.- fraction_name
Name of fraction estimate table to use. Should be stored in the
obj$fractions
list under this name. Can also rely on specifyingfeatures
and/orpopulations
and havingEZget()
find it.- quant_name
Name of transcript isoform quantification table to use. Should be stored in the obj$readcounts list under this name. Use
ImportIsoformQuant()
to create this table. Ifquant_name
isNULL
, it will search for tables containing the string "isoform_quant" in their name, as that is the naming convention used byImportIsoformQuant()
. If more than one such table exists, an error will be thrown and you will have to specify the exact name inquant_name
.- gene_to_transcript
Table with columns
transcript_id
and all feature related columns that appear in the relevant fractions table. This is only relevant as a hack to to deal with the case where STAR includes in its transcriptome alignment transcripts on the opposite strand from where the RNA actually originated. This table will be used to filter out such transcript-feature combinations that should not exist.- overwrite
If TRUE and a fractions estimate output already exists that would possess the same metadata (features analyzed, populations analyzed, and fraction_design), then it will get overwritten with the new output. Else, it will be saved as a separate output with the same name + "_#" where "#" is a numerical ID to distinguish the similar outputs.
- TPM_min
Minimum TPM for a transcript to be kept in analysis.
- count_min
Minimum expected_count for a transcript to be kept in analysis.