Function reference • FacileData

All functions
`FacileData-package`	FacileData: A fluent API for accessing multi-assay high-throughput genomics data
`FacileDataSet()`	Instantiates a FacileDataSet object from disk.
`adata()`	Bioc-container specific assay data extraction functions
`addFacileAssaySet()`	Adds new set of assay data for all samples in a FacileDataSet
`append_facile_feature_info()`	Appends new features to `feature_info` table
`append_facile_table()`	Adds rows to a table in a FacileDataSet
`as.DGEList()` `as.ExpressionSet()` `as.SummarizedExperiment()`	Converts a "facile result" to a traditional Bioconductor assay container.
`as.EAVtable()`	Convert a `pData` data.frame to a melted EAV table
`as.FacileDataSet()`	Converts a (list of) bioconductor assay containers into a FacileDataSet.
`as_facile_frame()`	Converts a normal tibble/data.frame to a facile_frame
`assay_feature_info(<FacileDataSet>)`	Materializes a table with all feature information for a given assay.
`assay_feature_type()`	Returns the feature_type for a given assay
`assay_info()`	Fetches assay meta information for the assays stored in a FacileDataStore
`assay_info_over_samples()`	Identify the number of each assay run across specific samples.
`assay_sample_info()`	Utility functions to get row and column indices of rnaseq hdf5 files.
`assay_units()`	Units of measure in an assay
`assemble_example_dataset()`	Assembles an example facile dataset to play with
`assert_sample_subset()` `check_sample_subset()` `test_sample_subset()` `assert_facet_descriptor()` `is_facet_descriptor()` `assert_assay_feature_descriptor()` `is_assay_feature_descriptor()` `assert_expression_result()` `is_expression_result()` `assert_sample_statistics()` `is_sample_statistics()` `assert_sample_covariates()` `is_sample_covariates()` `assert_columns()` `has_columns()` `assert_covariate_definitions()` `is_covariate_definitions()`	Check to see that samples are referenced correctly
`biocbox()`	Materialize a Bioconductor assay container from some facile object.
`as_cSurv()` `as_Surv()`	cSurv is a character representation of survival::surv ###
`cast_covariate()`	Casts the character EAV values to their R-native defined types.
`check_categorical()` `assert_categorical()` `test_categorical()`	Check to see if a vector is categorical (character or string)
`check_facile_data_set()` `assert_facile_data_set()` `test_facile_data_set()`	Check if argument is a FacileDataSet
`check_facile_data_store()` `assert_facile_data_store()` `test_facile_data_store()`	Check if argument is a FacileDataStore
`conform_data_frame()`	Arranges the columns of one data.frame to another
`covariate_definitions()`	Get description of sample metadata columns
`covariate_meta_info()`	Retrieve the meta information about a covariate for EAV decoding
`create_assay_feature_descriptor()`	Creates a feature descriptor for interactive ease
`dbfn()`	Get location of the FacileDataSet database
`.level_biotypes()`	Utility function to "factorize" biotypes into an order we care about.
`ds_annot()`	Bioc-container specific data set annotation extraction functions
`eav_metadata_create()`	Create a facile covariate definition file from a sample `pData` data.frame
`eav_encode_right_censored()` `eav_decode_right_censored()`	Entity-attribute-value encodings for survival data.
`eav_encode()`	Encodes column(s) from `pData` into character values
`eav_encode_covariate()`	Encodes column(s) from `pData` into character values
`eav_metadata_merge()`	Merge inferred and explicit covariate column metadata.
`eavdef_for_column()`	Generate entity-attribute-value definition for a column in a data.frame
`exampleFacileDataSet()`	Retrieves an example FacileDataSet
`executeSQL()`	Execute multiple queries against a database
`extract_transcribed_info_from_ensembl_gtf()`	Extract gene- and transcript-level information from an ENSEMBL gtf.
`facet_frame()`	Retrieves grouping table for samples within a FacileDataSet.
`facilitate()`	Converts an arbitrary object into one that works in the facile ecosystem.
`fdata()`	BioC-container specific fData extraction functions
`fds()` `fds<-`() `set_fds()`	Get or set the FacileDataStore for an object
`assay_feature_name_map()` `feature_name_map()`	Returns table of names and aliases for features.
`feature_types()`	Enumerate the types of feature stored in a FacileDataSet
`features()`	Returns a table of information about the features (from an assay, or ...)
`fetch_assay_data()` `with_assay_data(<facile_frame>)`	Fetch assay data from single assay of choice
`fetch_assay_score(<FacileDataSet>)`	Helper function to get sample assay data from single or aggregate features
`fetch_assay_score()`	NOTE: is fetch_assay_score really necessary?
`fetch_custom_sample_covariates(<FacileDataSet>)`	Fetches custom (user) annotations for a given user prefix
`fetch_sample_statistics(<FacileDataSet>)`	Fetch the sample statistics for sets of samples in the warehouse
`fetch_sample_statistics()`	NOTE: fetch_sample_statistics -> `fetch_assay_covariates` Issue #2
`fetch_sample_statistics(<default>)`	Issue #2
`fetch_samples(<FacileDataSet>)`	Fetches a sample descriptor that matches the filter criterion
`filter_features(<FacileDataSet>)`	Filter against the sample_covariate_tbl as if it were wide.
`filter_samples(<FacileDataSet>)`	Filter against the sample_covariate_tbl EAV table as if it were wide.
`flog()`	Generates a logging message using glue and crayon, with some bells/whistles.
`flog_level()`	Retrieves the currently set logging level
`freplace_na()`	Replaces NA's with specified values.
`gene_info_tbl()`	Mimics the old `gene_info` table.
`has_feature_type()`	Test if a given feature type is stored in a FacileDataSet
`hdf5fn()`	Get location of the FacileDataSet HDF5 file
`infer_feature_type()`	Guesses the type of feature identifiers from a character vector.
`initializeFacileDataSet()`	Create an empty FacileDataSet
`is.FacileDataSet()`	Class and validity checker for FacileDataSet
`join_samples()`	Filters the samples down in a dataset to ones specified
`name()`	Labeled acts like interface to reactive modules.
`meta_file()` `meta_info()` `default_assay(<FacileDataSet>)` `dataset_definitions()`	Path to the meta information YAML file
`nameit()`	Ensures that a vector has names for all elements if it has names for any
`normalize_assay_data()`	Helper functions to normalize assay data into log2 space.
`organism(<FacileDataSet>)`	Retrieves the organism the data is defined over
`parse_sample_criterion()`	Creates a filter expression to select samples based on value of a covariate
`pdata()`	Bioc-container specific pData extraction functions
`pdata_metadata()`	Bioc-container specific pData extraction functions
`primary_key()`	Query a table to identify its primary key(s)
`remove_batch_effect()`	Regress out confounding variables from a data matrix.
`fetch_sample_covariates()` `with_sample_covariates()`	Appends covariate columns to a query result
`sample_stats_tbl()`	Mimics old sample_stats table
`samples(<FacileDataSet>)`	Retrieves the sample identifiers for all samples in a FacileDataSet.
`samples()`	Returns a facile_frame of samples from an object in the faciebio ecosystem.
`save_custom_sample_covariates()`	Saves custom sample covariates to a FacileDataSet
`set_class()`	Set the class of an object and return the object
`eav_decode_real()` `eav_encode_real()` `eav_encode_logical()` `eav_decode_logical()` `eav_encode_cSurv()` `eav_decode_cSurv()` `eav_decode_categorical()` `eav_encode_categorical()`	Entity-attribute-value decoding for real values.
`spread_assay_data()`	Takes a result from fetch_expression and spreads out genes across columns
`spread_covariates()`	Spreads the covariates returned from database into wide data.frame
`sqlFromFile()`	Utility function to send more than one sql command to the database
`summary(<eav_covariates>)`	Provides a summary table of sample covariates.
`example_sample_covariates()` `example_meta()` `example_sample_covariate_definitions()`	Fetches exemplar data for unit testing
`validate_covariate_def_list()`	Validates that a covariate defintion list reasonably describes a data.frame.
`with_feature_info()`	Append feature information columns to (feature-rows)

Reference

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