Package: microdiluteR 1.0.1

Silvia Eckert

microdiluteR: Analysis of Broth Microdilution Assays

A framework for analyzing broth microdilution assays in various 96-well plate designs, visualizing results and providing descriptive and (simple) inferential statistics (i.e. summary statistics and sign test). The functions are designed to add metadata to 8 x 12 tables of absorption values, creating a tidy data frame. Users can choose between clean-up procedures via function parameters (which covers most cases) or user prompts (in cases with complex experimental designs). Users can also choose between two validation methods, i.e. exclusion of absorbance values above a certain threshold or manual exclusion of samples. A function for visual inspection of samples with their absorption values over time for certain group combinations helps with the decision. In addition, the package includes functions to subtract the background absorption (usually at time T0) and to calculate the growth performance compared to a baseline. Samples can be visually inspected with their absorption values displayed across time points for specific group combinations. Core functions of this package (i.e. background subtraction, sample validation and statistics) were inspired by the manual calculations that were applied in Tewes and Muller (2020) <doi:10.1038/s41598-020-67600-7>.

Authors:Silvia Eckert [aut, cre]

microdiluteR_1.0.1.tar.gz
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microdiluteR_1.0.1.tgz(r-4.4-any)microdiluteR_1.0.1.tgz(r-4.3-any)
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microdiluteR_1.0.1.tgz(r-4.4-emscripten)
microdiluteR.pdf |microdiluteR.html
microdiluteR/json (API)

# Install 'microdiluteR' in R:
install.packages('microdiluteR', repos = c('https://silvia-eckert.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/silvia-eckert/microdiluter/issues

Datasets:
  • bma - Absorption values from six broth microdilution assays conducted on 96-well plates

On CRAN:

3.30 score 6 scripts 423 downloads 29 exports 64 dependencies

Last updated 6 months agofrom:106a132b08. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 21 2024
R-4.5-winNOTENov 21 2024
R-4.5-linuxNOTENov 21 2024
R-4.4-winNOTENov 21 2024
R-4.4-macNOTENov 21 2024
R-4.3-winNOTENov 21 2024
R-4.3-macNOTENov 21 2024

Exports:add_concentrationadd_treatmentapply_sign_testapply_validation_methodask_concentration_listask_experiment_listask_group_listask_treatment_listcalculate_growth_performancecalculate_percentage_changecheck_monotonicitycheck_well_positionsgenerate_concentration_listgenerate_experiment_listgenerate_group_listgenerate_treatment_listmatch_concentrationmatch_treatmentplot_growth_performanceread_plateread_platessubtract_T0summarize_growth_performancetidy_platestidy_plates_via_paramstidy_plates_via_promptstidy_single_plateupdate_validityvalidate_cells

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggh4xggplot2ggthemesgluegtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6RColorBrewerRcppRcppEigenrlangrstatixscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Add concentration metadataadd_concentration ask_concentration_list generate_concentration_list match_concentration
Add treatment metadataadd_treatment ask_treatment_list generate_treatment_list match_treatment
Apply sign testapply_sign_test
Absorption values from six broth microdilution assays conducted on 96-well platesbma
Calculate and visualize growth performancecalculate_growth_performance calculate_percentage_change plot_growth_performance summarise_growth_performance summarize_growth_performance
Check monotonicity of well positions across groupscheck_monotonicity check_well_positions
Generate list of experiment names from user parametersask_experiment_list generate_experiment_list
Generate list of group IDs from user parametersask_group_list generate_group_list
Read multiple text files from photometer measurementread_plate read_plates
Subtract timepoint T0 and remove from datasubtract_T0
Add metadata to values from photometer measurementstidy_plates
Tidy multiple 96-well plates via parameterstidy_plates_via_params
Read raw photometry data and add meta data based on user inputtidy_plates_via_prompts
Tidy single 96-well plate via parameterstidy_single_plate
Check validity of each cell in data frame.apply_validation_method ask_invalid_samples ask_threshold ask_validity_method update_validity validate_cells