Package: FastRet 1.4.1

Tobias Schmidt

FastRet: Retention Time Prediction in Liquid Chromatography

A framework for predicting retention times in liquid chromatography. Users can train custom models for specific chromatography columns, predict retention times using existing models, or adjust existing models to account for altered experimental conditions. The provided functionalities can be accessed either via the R console or via a graphical user interface. Related work: Bonini et al. (2020) <doi:10.1021/acs.analchem.9b05765>.

Authors:Tobias Schmidt [aut, cre, cph], Christian Amesoeder [aut, cph], Marian Schoen [aut, cph], Fadi Fadil [aut, cph], Katja Dettmer [aut, cph], Peter Oefner [ths, cph]

FastRet_1.4.1.tar.gz
FastRet_1.4.1.zip(r-4.7)FastRet_1.4.1.zip(r-4.6)FastRet_1.4.1.zip(r-4.5)
FastRet_1.4.1.tgz(r-4.6-any)FastRet_1.4.1.tgz(r-4.5-any)
FastRet_1.4.1.tar.gz(r-4.7-any)FastRet_1.4.1.tar.gz(r-4.6-any)
FastRet_1.4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
FastRet/json (API)

# Install 'FastRet' in R:

install.packages('FastRet', repos = c('https://spang-lab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/spang-lab/fastret/issues

Pkgdown/docs site:https://spang-lab.github.io

Uses libs:

openjdk– OpenJDK Java runtime, using Hotspot JIT

Datasets:

RP - Retention Times (RT) measured on a Reverse Phase (RP) Column

On CRAN:

retention time chromotography lc-ms data-science lcms openjdk

3.95 score 2 stars 4 scripts 239 downloads 27 exports 87 dependencies

Last updated from:b047cbb1e7. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	199
source / vignettes	OK	243
linux-release-x86_64	NOTE	197
macos-release-arm64	NOTE	136
macos-oldrel-arm64	NOTE	106
windows-devel	NOTE	111
windows-release	NOTE	135
windows-oldrel	NOTE	110
wasm-release	OK	201

Exports:adjust_frm analyzeCDNames as_canonical catf CDFeatures CDNames clip_predictions collect fastret_app get_predictors getCDs init_log_dir now pkg_file plot_frm preprocess_data read_retip_hilic_data read_rp_lasso_model_rds read_rp_xlsx read_rpadj_xlsx selective_measuring start_gui train_frm withLineEnd withSink withStopMessage withTimeout

Dependencies:base64enc bit bit64 blob bslib cachem cli cluster codetools commonmark cpp11 crosstalk data.table DBI digest DT evaluate farver fastmap fingerprint fontawesome foreach fs future ggplot2 glmnet globals glue gtable highr htmltools htmlwidgets httpuv isoband iterators itertools jquerylib jsonlite knitr labeling later lattice lazyeval lifecycle listenv litedown magrittr markdown Matrix memoise mime openxlsx otel parallelly pkgconfig png promises R6 rappdirs rcdk rcdklibs RColorBrewer Rcpp RcppEigen rJava rlang rmarkdown RSQLite S7 sass scales shape shiny shinyhelper shinyjs sourcetools stringi survival tinytex vctrs viridisLite withr xfun xgboost xtable yaml zip

Help page	Topics
Adjust an existing FastRet model for use with a new column	adjust_frm
Clip predictions to observed range	clip_predictions
The FastRet GUI	fastret_app
Get Chemical Descriptors for a list of molecules	getCDs
Plot predictions for a FastRet model	plot_frm
Predict retention times using a FastRet Model	predict.frm
Preprocess data	preprocess_data
Read the HILIC dataset from the Retip package	read_retip_hilic_data
LASSO Model trained on RP dataset	read_rp_lasso_model_rds
Read retention times (RT) measured on a reverse phase (RP) column	read_rp_xlsx
Hypothetical retention times	read_rpadj_xlsx
Retention Times (RT) measured on a Reverse Phase (RP) Column	RP
Selective Measuring	selective_measuring
Start the FastRet GUI	start_gui
Train a new FastRet model (FRM) for retention time prediction	train_frm

Package: FastRet 1.4.1

FastRet: Retention Time Prediction in Liquid Chromatography

Citation

Development and contributors

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)