Package: MACSQuantifyR 1.26.0

Raphaël Bonnet

MACSQuantifyR: Fast treatment of MACSQuantify FACS data

Automatically process the metadata of MACSQuantify FACS sorter. It runs multiple modules: i) imports of raw file and graphical selection of duplicates in well plate, ii) computes statistics on data and iii) can compute combination index.

Authors:Raphaël Bonnet [aut, cre], Marielle Nebout [dtc],Giulia Biondani [dtc], Jean-François Peyron[aut,ths], Inserm [fnd]

MACSQuantifyR_1.26.0.tar.gz
MACSQuantifyR_1.26.0.zip(r-4.7-any)MACSQuantifyR_1.26.0.zip(r-4.6-any)MACSQuantifyR_1.26.0.zip(r-4.5-any)
MACSQuantifyR_1.26.0.tgz(r-4.6-any)MACSQuantifyR_1.26.0.tgz(r-4.5-any)
MACSQuantifyR_1.26.0.tar.gz(r-4.7-any)MACSQuantifyR_1.26.0.tar.gz(r-4.6-any)
MACSQuantifyR_1.26.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MACSQuantifyR/json (API)

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

On BioConductor:MACSQuantifyR-1.27.0(bioc 3.24)MACSQuantifyR-1.26.0(bioc 3.23)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

dataimportpreprocessingnormalizationflowcytometrydatarepresentationgui

4.48 score 3 scripts 323 downloads 10 exports 70 dependencies

Last updated from:9fc881774c (on RELEASE_3_23). Checks:1 ERROR, 7 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksERROR158
linux-develNOTE239
source / vignettesOK208
linux-releaseNOTE183
macos-releaseNOTE122
macos-oldrelNOTE104
windows-develNOTE97
windows-releaseNOTE71
windows-oldrelNOTE93
wasm-releaseOK119

Exports:barplot_datacombination_indexgenerate_reportload_MACSQuantnew_class_MQon_plate_selectionpipelinerDatasetPathsorted

Dependencies:askpassbase64encbslibcachemcellrangerclicpp11crayoncurldeldirdigestevaluatefarverfastmapfontawesomefsggplot2ggrepelgluegridExtragtablehighrhmshtmltoolshttrinterpisobandjpegjquerylibjsonliteknitrlabelinglatticelatticeExtralifecyclemagrittrMASSmemoisemimeopensslpillarpkgconfigpngprettydocprettyunitsprogressR6rappdirsRColorBrewerRcppRcppEigenreadxlrematchrlangrmarkdownrvestS7sassscalesselectrsystibbletinytexutf8vctrsviridisLitewithrxfunxml2yaml

MACSQuantifyR - Step-by-step analysis
Introduction | Pipeline | Create a new object MACSQuant: new_class_MQ() | Import your data: load_MACSQuant() | Sort your replicates: on_plate_selection() | 2D/3D data representation: barplot_data() | Combination index computation: combination_index() | Report generation: generate_report() | Links | Reference
Rendered fromMACSQuantifyR_combo.Rmdusingknitr::rmarkdown

Last update: 2019-10-22
Started: 2019-10-08

MACSQuantifyR - Introduction
Introduction | Pipelines | Automatic pipeline | Step-by-step pipeline
Rendered fromMACSQuantifyR.Rmdusingknitr::rmarkdown

Last update: 2019-10-08
Started: 2018-11-17

MACSQuantifyR - Automatic pipeline
Requirements | Running the pipeline() function | Load the packages to make the function available | Run the function | Access the results | Statistics | Graphical representations | Define output and experimental parameters (optional) | Links
Rendered fromMACSQuantifyR_pipeline.Rmdusingknitr::rmarkdown

Last update: 2019-10-08
Started: 2019-10-08