Function reference • pbwrangler

All functions

adv_clones: adv_clones

assign_benches(): assign clones to tissue culture benches

capture_location(): use purrr::imap to capture location of a trial from trial file ipurrr::map applies a function to each element of a vector and its index

check_gene_chars(): check length of accession family name - should be 9

check_geno(): get accession names that do not conform to required protocol

clean_clone_name(): Clean accession names

clean_dir_name(): clean file name using gsub

clean_dir_name_c(): clean file name using gsub

clean_file_names(): clean file names using gsub

clean_var_names(): clean variable names

combine_meta_files(): read meta-files from separate trials in a season into 1 file

compare_df(): Compare field experiment data to see if they share designs, variables, etc.

compute_cols(): Compute nmtp, mtwp (no/marketable tuber weight per plot)

convert_to_character(): Coerce columns to character

convert_to_factor(): Coerce columns to factors

convert_to_numeric(): onvert column values that numeric but read as character to numeric

create_family_vars(): create new family code per new naming convention

create_meta_file(): create a meta-data file with design factors, planting dates etc

create_pedigree(): create pedigree (ancestry)

create_td(): A wrapper for statgenSTA::createTD for a row-col design model fitting

drop_all_data(): drop dataframe objects from a list of dataframes

drop_empty_dfs(): drop from a list dataframes with no dimension or columns having all NA

drop_nas(): delete columns with all values missing(NA)

drop_null_dfs(): drop null dataframes from a list of dataframes

drop_sheets(): drop workbook sheets not of interest

drop_zeros(): delete columns with all values 0

duplicate_row(): duplicate a row

extract_blups(): extract BLUPs from a REML model

family_code: country_level_data

filter_geno(): Filter clone ids to rid of non-compliant formats

find_var(): find variables in df

fit_td(): A wrapper for statgenSTA::fitTD for REML analysis

format_accessions(): organize accessions to export

geno_by_tubers(): Distribute clones to match the available seeds during replication

gen_familycode(): a regular expr deleting everything after last fullstop(.) or last underscore(_)

gen_location(): generate possible location from file paths

gen_uniqueid(): generate unique ids

get_design_factors(): Get experimental design factors from a trial dataframe/fieldbook

get_fieldbooks(): get field trial fieldbooks in a particular folder

get_ontology_labels(): get ontology labels from {st4gi}

get_valid_columns(): get column names defined in ontology

`%nin%`: %nin% returns a logical vector if there is a match or not for left operand

ilri: ilri

join_by_keys(): Join predictor and heritability (h2) data objects to one dataframe

keep_geno(): drop dfs w/o geno column

keep_ttyna(): drop dfs without ttyna as a column

list_design_files(): List design files after designing trial experiments in R

list_files(): List file in a directory

merge_note_obs(): Merge notes & obs to one column

meta: adv_clones

my_left(): Extract first n elements of a string

my_right(): Extract last n elements of a string

names_df(): sort names in ascending order

pre_process_trials(): run a number of checks & transformations to pre-process a list of trial data

pre_process_trials_(): run a number of checks & transformations to pre-process a list of trial data

process_trials(): run a number of checks & transformations to pre-process a list of trial data

randomize_noRep(): randomize trials for multiplication without replication

randomize_res_row_col(): resolvable row column design: plots = row by col; test clones replicated once, checks more than once

randomize_row_col(): row column design: plots = row by col; equal rep for each treatment

rand_Prep(): Partially replicated field design

read_accessions(): read accession files that have been fixed and confirmed correct

read_workbooks(): A wrapper for readr's read_csv & readxl's read_excel for reading trial data

recode_var(): Coarce variable to numeric or character

rename_cols(): rename data columns to conform to ontology labels

run_checks(): run data quality checks using {st4gi} functions

run_data_processes(): compute derived phenotypic variables

select_cols(): A wrapper for dplyr::select function

split_by_chunk(): split a dataframe into a list by row numbe

subset_invalid_cols(): get invalid names (labels not in ontology) & add geno

sum_rowwise(): dplyr::rowwise sum target columns

trial_design_meta(): generate trial design inputs i.e., geno replications and blocking list

update_geno(): Update accession names to conform to naming convention

write_data(): write processed trial data to a directory

write_season_data(): Write out data for pre-processed experimental data by calling write_trials()

write_trials(): write out trial data