# Quality Control and Semantic Enrichment of Datasets

## Documentation for package ‘eHDPrep’ version 1.4.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

apply_quality_ctrl | Apply quality control measures to a dataset
assess_completeness | Assess completeness of a dataset
assess_quality | Assess quality of a dataset
assume_var_classes | Assume variable classes in data
cellspec_lgl | Kable logical data highlighting
compare_completeness | Compare Completeness between Datasets
compare_info_content | Information Content Comparison Table
compare_info_content_plt | Information Content Comparison Plot
completeness_heatmap | Completeness Heatmap
count_compare | Compare unique values before and after data modification
discrete.mi | Calculate mutual information of a matrix of discrete values
distant_neg_val | Find highly distant value for data frame
edge_tbl_to_graph | Convert edge table to tidygraph graph
encode_as_num_mat | Convert data frame to numeric matrix
encode_binary_cats | Encode categorical variables as binary factors
encode_bin_cat_vec | Encode a categorical vector with binary categories
encode_cats | Encode categorical variables using one-hot encoding.
encode_genotypes | Encode genotype/SNP variables in data frame
encode_genotype_vec | Encode a genotype/SNP vector
encode_ordinals | Encode ordinal variables
entropy | Calculate Entropy of a Vector
exact.kde | Exact kernel density estimation
example_data | Example data for eHDPrep
example_edge_tbl | Example ontology as an edge table for semantic enrichment
example_mapping_file | Example mapping file for semantic enrichment
example_ontology | Example ontology as a network graph for semantic enrichment
export_dataset | Export data to delimited file
extract_freetext | Extract information from free text
identify_inconsistency | Identify inconsistencies in a dataset
import_dataset | Import data into 'R'
import_var_classes | Import corrected variable classes
information_content_contin | Calculate Information Content (Continuous Variable)
information_content_discrete | Calculate Information Content (Discrete Variable)
join_vars_to_ontol | Join Mapping Table to Ontology Network Graph
max_catchNAs | Find maximum of vector safely
mean_catchNAs | Find mean of vector safely
merge_cols | Merge columns in data frame
metavariable_agg | Aggregate Data by Metavariable
metavariable_info | Compute Metavariable Information
metavariable_variable_descendants | Extract metavariables' descendant variables
min_catchNAs | Find minimum of vector safely
mi_content_discrete | Calculate Mutual Information Content
mod_track | Data modification tracking
node_IC_zhou | Calculate Node Information Content (Zhou et al 2008 method)
normalize | Min max normalization
nums_to_NA | Replace numeric values in numeric columns with NA
onehot_vec | One hot encode a vector
ordinal_label_levels | Extract labels and levels of ordinal variables in a dataset
plot_completeness | Plot Completeness of a Dataset
prod_catchNAs | Find product of vector safely
report_var_mods | Track changes to dataset variables
review_quality_ctrl | Review Quality Control
row_completeness | Calculate Row Completeness in a Data Frame
semantic_enrichment | Semantic enrichment
skipgram_append | Append Skipgram Presence Variables to Dataset
skipgram_freq | Report Skipgram Frequency
skipgram_identify | Identify Neighbouring Words (Skipgrams) in a free-text vector
strings_to_NA | Replace values in non-numeric columns with NA
sum_catchNAs | Sum vector safely for semantic enrichment
validate_consistency_tbl | Validate internal consistency table
validate_mapping_tbl | Validate mapping table for semantic enrichment
validate_ontol_nw | Validate ontology network for semantic enrichment
variable.bw.kde | Variable bandwidth Kernel Density Estimation
variable_completeness | Calculate Variable Completeness in a Data Frame
variable_entropy | Calculate Entropy of Each Variable in Data Frame
warn_missing_dots | Missing dots warning
zero_entropy_variables | Identify variables with zero entropy