Package index • sampleDB

All functions

ArchiveAndDeleteControls(): Archive and Delete Wetlab EPPIcenter Samples

ArchiveAndDeleteSamples(): Archive and Delete Samples

Backup_SampleDB(): Backup Sample Database

ColumnData(): Create a ColumnData S3 object

DeleteEmptyContainer(): Delete Empty Wetlab Containers in the EPPIcenter SampleDB database

DeleteWholeBloodSamples(): Delete Whole Blood Controls

ErrorData: ErrorData class

MoveContainers(): Move Wetlab Containers in the EPPIcenter SampleDB database

MoveSamples(): Move Wetlab Samples

RenameContainers(): Rename Wetlab Containers in the EPPIcenter SampleDB database

Run_SampleDB(): Run sampleDB as a R Shiny App

SampleDB_Setup(): Set up and deploy the SampleDB environment, database, and Shiny server.

SearchByType(): Search for Wetlab Samples in the EPPIcenter SampleDB database

SearchControls(): Get all malaria blood controls

UpdateReferences(): Update References in the EPPIcenter SampleDB database

UploadSpecimens(): Upload Wetlab Samples

ValidationErrorCollection: ValidationErrorCollection class

add_bags_if_not_exist(): Add new bags to the database if they don't exist

add_malaria_blood_controls_if_not_exist(): Add malaria blood controls to the database if they don't exist

add_new_blood_spot_collections(): Add New Blood Spot Collections

add_new_dbs_control_sheets(): Add new DBS control sheets to the database

add_position_column(): Add a position column based on column attributes

add_row_numbers(): Add row numbers to a dataframe

add_to_errors(): Add an Error to the Error List

append_strains_to_db(): Append Strains to the Database Table

append_study_to_db(): Append Studies to the Database Table

append_whole_blood_tubes(): Add whole blood tubes to the database if they don't exist

bind_new_data(): Add Data to User Data

check_control_exists(): Check for Control Existence

check_cryovial_barcodes_exist(): Check Cryovial Barcodes in Database

check_cryovial_box_exists(): Check If Cryovial Box Exists in the Database

check_duplicated_rows(): Check for duplicated rows in a data frame

check_longitudinal_study_dates(): Check if collection dates are missing for samples in a longitudinal study

check_micronix_barcodes_exist(): Check Micronix Barcodes in Database

check_micronix_plate_exists(): Check If Micronix Plate Exists in the Database

check_missing_data(): Check for missing data in required fields

check_strain_percentage_match(): Validate that the strain and percentage columns have matching semicolon counts

check_unique_positions(): Check Unique Positions

collapse_and_nest_columns(): Collapse and Nest Strain and Percentage Columns

concat_position(): Concatenate Position from Column and Row Information

convert_density_representations(): Convert Density Representations to Real Numbers

convert_density_to_numeric(): Convert string values with 'k' or 'K' to numeric values

copy_database(): Copy SQLite Database

copy_if_not_exists(): Copy a file to a destination if it does not exist there.

create_control_label(): Create Control Label with Density and Composition Values

create_controls_for_batch(): Create Controls for the batch

create_flat_view_by_sample_type(): Flatten all database tables by sample type

create_flat_view_of_extractions(): View all extractions in the database

create_unique_id(): Create a unique identifier for compositions

create_unique_id_from_sorted(): Create a unique identifier from sorted strains and percentages

cryovial_na: Cryovial NA

denormalize_composition_ids(): Denormalize Composition IDs from User Data

display_app_url(): Display the URL of the deployed Shiny application.

.Backup(): Internal function to backup a SQLite database

.Compress(): Internal function to compress a file

.Uncompress(): Internal function to uncompress a file

execute_sql(): Execute SQL Queries on a Database

extract_search_criteria(): Extract Search Criteria from User CSV File

find_column_name(): Find First Matching Column Name

find_header(): Identify the row in a CSV file that matches the header based on required column names.

format_composition_types(): Format composition types

format_error(): Create Formatting Error Data Frame

format_labels(): Format labels for compositions in a dplyr pipeline

fuzzy_merge_unique_compositions(): Fuzzy Merge Unique Compositions

generate_upgrade_script_path(): Generate Path to Database Upgrade Script

get_all_control_types(): Get all control types

get_all_sample_types(): Get all sample types

get_batches(): Get all batches from the database

get_composition_types(): Get all composition type from the database

get_container_by_sample(): Get containers by specified sample type

get_container_table_name(): Get the Relevant Table Name Based on Container Class

get_control_action_types(): Get action types for a specific control

get_control_file_columns(): Retrieve ColumnData for a given control type and action

get_control_types(): Get control types from a JSON file

get_db_version(): Retrieve Current Database Version

get_densities(): Get all densities from the database

get_dereferenced_values(): Get dereferenced values using sample_values and shared_values

get_destination_container_by_control(): Get destination container by specified control type

get_destination_location_by_control(): Get destination location by specified control type

get_duplicated_rows(): Find duplicate rows in a data frame

get_environ_file_path(): Get environ file path

get_expected_versions(): Retrieve Expected Versions from JSON File

get_file_types_for_control(): Get file types for a specific control

get_file_types_for_sample(): Get file types for a specific sample

get_location_by_sample(): Get locations by specified sample type

get_normalized_path(): Get normalized path

get_percentages(): Get all batches from the database

get_position_column_by_sample(): Get the expected position column for a sample type

get_reference_file_columns(): Retrieve ColumnData for a given reference type.

get_sample_action_types(): Get action types for a specific sample

get_sample_file_columns(): Retrieve ColumnData for a given sample type and action.

get_sample_types(): Get sample types from a JSON file

get_sample_types_by_action(): Get sample types from a JSON file by action

get_storage_container_by_control(): Get source container by specified control type

get_storage_location_by_control(): Get source location by specified control type

get_strains(): Get all strains from the database

get_studies(): Get all studies from the database

get_unique_compositions_from_database(): Extract unique compositions from the database

get_unique_compositions_from_user_data(): Normalize Percentages by Group

get_values(): Get values with priority to sample_values over shared_values.

handle_unknown_date_tokens(): Handle Unknown Date Tokens

handle_upgrade_error(): Handle any errors during the database upgrade

init_and_copy_to_db(): Initialize Database Connection and Copy User Data

init_db_conn(): Initialize a Database Connection

initialize_database_with_base_version(): Initialize Database with Base Version

is_linux_platform(): Check if the system platform is Linux.

is_shiny_server_installed(): Check if Shiny server is installed.

join_blood_spot_collections(): Join Blood Spot Collections

join_composition_ids(): Process user data to handle malaria blood control details

join_dbs_control_sheets(): Join DBS control sheets based on bag ID and label

join_locations_and_bags(): Join locations and bags from user data to the database

join_locations_and_boxes(): Process Whole Blood Box Data

join_malaria_controls(): Join malaria controls based on density and study subject ID

merge_configs(): Merge Configuration Lists

message_not_site_install(): Display a message indicating the need for a site install.

message_not_supported_platform(): Display a message indicating Shiny server isn't supported.

message_shiny_not_installed(): Display a message indicating Shiny server isn't installed.

micronix_na: Micronix NA

normalize_composition_ids(): Normalize Composition IDs from User Data

perform_batch_db_validations(): Perform Database-Related Validations for Batches

perform_composition_db_validations(): Perform Database-Related Validations for Compositions

perform_cryovial_db_validations(): Perform Database-Related Validations for Cryovials

perform_dbs_sample_db_validations(): Perform Database-Related Validations for DBS Samples

perform_dbs_sheet_db_validations(): Perform Database-Related Validations for DBS Sheets

perform_micronix_db_validations(): Perform Database-Related Validations for Micronix

perform_strain_db_validations(): Perform Database-Related Validations for Strains

perform_whole_blood_db_validations(): Perform Database-Related Validations for Whole Blood Controls

prepare_control_data_for_validation(): Prepare DataFrame for Control Validation

prepare_control_for_upload(): Prepare Control for Upload

prepare_new_compositions(): Prepare new compositions for database upload

prepare_reference_data_for_validation(): Prepare DataFrame for Reference Validation

prepare_specimen_data_for_validation(): Prepare DataFrame for Specimen Validation

print(<ColumnData>): Print method for ColumnData objects

process_and_append_compositions(): Process and append new compositions to the database

process_bag_data(): Process user data to handle bag details

process_blood_spot_collection_data(): Process Blood Spot Collection Data

process_control_csv(): Process and Validate Control CSV File

process_dbs_control_sheet_data(): Process user data to handle DBS control sheet details

process_malaria_blood_control_data(): Process user data to handle malaria blood control details

process_reference_csv(): Process and Validate Reference CSV File

process_specimen_csv(): Process and Validate Specimen User CSV File

process_whole_blood_location_container(): Process Whole Blood Box Data

read_and_preprocess_csv(): Read and Preprocess User CSV File

rejoin_dbs_control_sheet_ids(): Rejoin to Get New DBS Control Sheet IDs

rejoin_malaria_controls(): Rejoin malaria controls based on density and study subject ID

rejoin_to_get_bag_ids(): Rejoin the payload with the database to retrieve bag IDs

remove_na_columns_in_row(): Remove columns that have NA in a row

reshape_identifier_to_long_form(): Reshape Identifier Data to Long Form

retrieve_compositions_by_identifier(): Retrieve compositions from the database by identifier

retrieve_compositions_by_label(): Retrieve compositions from the database by label

search_by_study_subject_file_upload(): Search by Study Subject (and other longitudinal study criteria)

search_compositions(): Search for Compositions in Database

search_micronix_tube(): Search Micronix Tube Samples

select_relevant_columns(): Select relevant columns from the user CSV file

set_header_row(): Set a Specific Row as the Header

set_user_file_header(): Set the header row for the user CSV file

setup_database(): Setup or upgrade the database

setup_directory(): Setup a directory if it does not exist.

split_and_sort(): Split and sort strains and percentages

split_and_unnest_columns(): Split and Unnest Strain and Percentage Columns

stop_app_error(): Stop with an application error

stop_formatting_error(): Stop with a formatting error

stop_validation_error(): Stop with a validation error

update_configuration_file(): Update Configuration File

update_env_variable(): Update environment variable

upgrade_database(): Upgrade Database

upload_compositions(): Upload compositions to the database

upload_controls(): Upload Controls to the Database

upload_extracted_dna(): Upload Extracted DNA Data to SampleDB

validate_and_format_control_file(): Check if the user CSV file for control meets the requirements

validate_and_format_reference_file(): Check if the user CSV file for control meets the requirements

validate_and_format_specimen_file(): Check if the user CSV file meets the requirements

validate_batch(): Validate Batch Data

validate_box_uniqueness(): Check if boxes have enough unique cryovial barcodes to be easily identifiable.

validate_composition(): Validate Compositions Data

validate_composition_sum(): Validate if control compositions sum correctly

validate_controls(): Validate Control Specimens

validate_cryovial(): Validate Cryovial Specimen Data

validate_cryovial_collection_dates(): Confirm that Cryovials with no barcodes have collection dates if there's already a sample from that study subject.

validate_cryovial_moves(): Validate Cryovial Moves

validate_cryovial_position(): Validate Cryovial-specific position rules

validate_cryovial_uploads(): Validate Cryovial Uploads

validate_date_format(): Validate Date Format

validate_dates_with_tokens(): Validate Dates with Tokens

validate_dbs_bag_label_is_unique(): Validate DBS Bag Label is unique at a location

validate_dbs_sample(): Validate DBS Specimen Data

validate_dbs_sample_label_uniqueness(): DBS Specimen paper identifier uniqueness check

validate_dbs_sample_moves(): Validate DBS Specimen Moves

validate_dbs_sample_uploads(): Validate Micronix Uploads

validate_dbs_sheet(): Validate DBS Sheet Control Data

validate_dbs_sheet_create(): Validate DBS Sheet Create

validate_dbs_sheet_extraction(): Validate DBS Sheet Extraction

validate_empty_cryovial_well_upload(): Cryovial Empty Well Validation

validate_empty_micronix_well_upload(): Micronix Empty Well Validation

validate_existing_barcodes_by_study(): Validate if barcodes already exist for a given study

validate_extraction_counts_with_totals(): Validate Extraction Counts Against Blood Spot Collection Totals

validate_location_reference_db(): Validate location references (Database Version)

validate_longitudinal_study(): Ensure uniqueness of study subjects and collection dates within longitudinal studies.

validate_matrix_container(): Validate Matrix Container position

validate_micronix(): Validate Micronix Specimen Data

validate_micronix_barcode_length(): Validate Micronix-specific barcode length rules

validate_micronix_moves(): Validate Micronix Moves

validate_micronix_position(): Validate Micronix-specific position rules

validate_micronix_uploads(): Validate Micronix Uploads

validate_non_longitudinal_study_subjects(): Check uniqueness of StudySubject within non-longitudinal studies.

validate_references(): Validate References

validate_specimen_type_db(): Validate specimen type references (Database Version)

validate_specimens(): Validate Specimens Main Function

validate_strain(): Validate Strains Data

validate_strains_in_database(): Validate strains recorded in the database

validate_study_reference_db(): Validate study references (Database Version)

validate_study_short_code(): Validate that study does not have a date for it's short code

validate_whole_blood(): Validate Whole Blood Control Data

validate_whole_blood_create(): Validate Whole Blood Create

validate_whole_blood_extraction(): Validate Whole Blood Extraction

validate_whole_blood_tube_exists(): Validate Cryovial Tube Exists