EZget() returns a table of interest from your EZbakRData object. It is meant
to make it easier to find and access certain analyses, as a single EZbakRData
object may include analyses of different features, kinetic parameters, dynamical
systems models, comparisons, etc.
EZget(
obj,
type = c("fractions", "kinetics", "readcounts", "averages", "comparisons", "dynamics"),
features = NULL,
populations = NULL,
fraction_design = NULL,
isoforms = NULL,
kstrat = NULL,
parameter = NULL,
counttype = NULL,
design_factor = NULL,
dynamics_design_factors = NULL,
scale_factors = NULL,
cstrat = NULL,
feature_lengths = NULL,
experimental = NULL,
reference = NULL,
param_name = NULL,
param_function = NULL,
formula_mean = NULL,
sd_grouping_factors = NULL,
fit_params = NULL,
repeatID = NULL,
sub_features = NULL,
grouping_features = NULL,
sample_feature = NULL,
modeled_to_measured = NULL,
graph = NULL,
normalize_by_median = NULL,
deconvolved = NULL,
returnNameOnly = FALSE,
exactMatch = FALSE,
alwaysCheck = FALSE
)Table of interest from the relevant EZbakRdata list (set by the
type parameter).
EZbakRData object
The class of EZbakR outputs would you like to search through. Equivalent to the name of the list in the EZbakRData object that contains the tables of interest.
Features that must be present in the table of interest.
If exactMatch is TRUE, then these features must also be the only features
present in the table.
Only relevant if type == "fractions". Mutational
populations that must have been analyzed to generate the table of interest.
Only relevant if type == "fractions". Fraction design
table used to generate the table of interest.
If the relevant table is the result of isoform deconvolution
Only relevant if type == "kinetics". Short for "kinetics strategy";
the strategy used to infer kinetic parameters.
Only relevant if type == "averages" or "comparisons". Which
parameter was being averaged or compared?
String denoting what type of read count information you are looking for. Current options are "TMM_normalized", "transcript", and "matrix". TO-DO: Not sure this is being used in any way currently...
design_factor specified in relevant run of CompareParameters().
Therefore, only relevant if type == "comparisons".
design_factors included in final EZDynamics() output.
Therefore, only relevant if type == "dynamics".
Sample group scale factors used in EZDynamics().
Therefore, only relevant if type == "dynamics"
Strategy used for comparative analyses. Can be:
contrast: If two parameters were compared via specifying the reference
and experimental levels in CompareParameters() (for type == "averages").
single_param: If a single parameter was passed to CompareParameters()
via its param_name option.
dynamics: If output of EZDynamics() was passed to CompareParameters()
function: If function of multiple parameters was passed to CompareParameter()
via its param_function option.
Table of feature lengths used for length normalization.
Experimental condition specified in relevant run of CompareParameters().
Therefore, only relevant if type == "comparisons".
Reference condition specified in relevant run of CompareParameters().
Therefore, only relevant if type == "comparisons".
Parameter name specified in relevant run of CompareParameters().
Therefore, only relevant if type == "comparisons"
Function of parameters specified in relevant run of CompareParameters().
Therefore, only relevant if type == "comparisons".
An R formula object specifying how the parameter of interest
depends on the sample characteristics specified in obj's metadf. Therefore,
only relevant if type == "averages".
What metadf columns should data be grouped by when estimating standard deviations across replicates? Therefore, only relevant if type == "averages".
Character vector of names of parameters in linear model fit. Therefore, only relevant if type == "averages".
Numerical ID for duplicate objects with same metadata.
Only relevant if type == "dynamics". Feature columns
that distinguished between the different measured species when running
EZDynamics().
Only relevant if type == "dynamics. Features
that were the overarching feature assignments by which sub_features were grouped
when running EZDynamics().
Only relevant if type == "dynamics". Name of the metadf
column that distinguished the different classes of samples when running
EZDynamics().
Only relevant if type == "dynamics". Specifies
the relationship between sub_features, sample_feature (if specified),
and the species in graph.
Only relevant if type == "dynamics". NxN adjacency matrix,
where N represents the number of species modeled when running EZDynamics().
Whether median difference was subtracted from estimated kinetic parameter difference. Thus, only relevant if type == "comparisons".
Only relevant if type == "fractions". Boolean that is TRUE if
fractions table is result of performing multi-feature deconvolution with
DeconvolveFractions().
If TRUE, then only the names of tables that passed your
search criteria will be returned. Else, the single table passing your search
criteria will be returned. If there is more than one table that passes your
search criteria and returnNameOnly == FALSE, an error will be thrown.
If TRUE, then for features and populations, which can be vectors,
ensure that provided vectors of features and populations exactly match the relevant metadata
vectors.
If TRUE, then even if there is only a single table for the type
of interest, still run all checks against queries.
The input to EZget() is 1) the type of table you want to get ("fractions",
"kinetics", "averages", "comparisons", or "dynamics") and 2) the metadata necessary
to uniquely specify the table of interest. Above, every available piece of metadata
that can be specified for this purpose is documented. You only need to specify the
minimum information necessary. For example, if you would like to get a "fractions"
table from an analysis of exon bins (feature == "exon_bins", and potentially
other overarching features like "XF", "GF", or "rname"), and none of your other
"fractions" tables includes exon_bins as a feature, then you can get this table
with EZget(ezbdo, type = "fractions", features = "exon_bins"), where ezbdo
is your EZbakRData object.
As another example, imagine you want to get a "kinetics" table from an analysis
of gene-wise kinetic parameters (e.g., features == "XF"). You may have multiple
"kinetics" tables, all with "XF" as at least one of their features. If all of the
other tables have additional features though, then you can tell EZget() that
"XF" is the only feature present in your table of interest by setting exactMatch
to TRUE, which tells EZget() that the metadata you specify should exactly match
the relevant metadata for the table of interest. So the call in this case would
look like EZget(ezbdo, type = "fractions", features = "XF", exactMatch = TRUE).
EZget() is used internally in almost every single EZbakR function to specify
the input table for each analysis. Thus, the usage and metadata described here
also applies to all functions that require you to specify which table you want
to use (e.g., EstimateKinetics(), AverageAndRegularize(), CompareParameters(),
etc.).
# Simulate data to analyze
simdata <- EZSimulate(30)
# Create EZbakR input
ezbdo <- EZbakRData(simdata$cB, simdata$metadf)
# Estimate Fractions
ezbdo <- EstimateFractions(ezbdo)
# Estimate Kinetics
ezbdo <- EstimateKinetics(ezbdo)
# Average log(kdeg) estimates across replicate
ezbdo <- AverageAndRegularize(ezbdo)
#' # Average log(ksyn) estimates across replicate
ezbdo <- AverageAndRegularize(ezbdo, parameter = "log_ksyn")
# Compare log(kdeg) across conditions
ezbdo <- CompareParameters(
ezbdo,
design_factor = "treatment",
reference = "treatment1",
experimental = "treatment2"
)
# Get the one and only fractions object
fxns <- EZget(ezbdo, type = "fractions")
# Get the log(ksyn) averages table
ksyn_avg <- EZget(ezbdo, type = "averages", parameter = "log_ksyn")
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