Package: mxnorm 1.0.3

mxnorm: Apply Normalization Methods to Multiplexed Images

Implements methods to normalize multiplexed imaging data, including statistical metrics and visualizations to quantify technical variation in this data type. Reference for methods listed here: Harris, C., Wrobel, J., & Vandekar, S. (2022). mxnorm: An R Package to Normalize Multiplexed Imaging Data. Journal of Open Source Software, 7(71), 4180, <doi:10.21105/joss.04180>.

Authors:Coleman Harris [aut, cre]

mxnorm_1.0.3.tar.gz
mxnorm_1.0.3.zip(r-4.5)mxnorm_1.0.3.zip(r-4.4)mxnorm_1.0.3.zip(r-4.3)
mxnorm_1.0.3.tgz(r-4.4-any)mxnorm_1.0.3.tgz(r-4.3-any)
mxnorm_1.0.3.tar.gz(r-4.5-noble)mxnorm_1.0.3.tar.gz(r-4.4-noble)
mxnorm_1.0.3.tgz(r-4.4-emscripten)mxnorm_1.0.3.tgz(r-4.3-emscripten)
mxnorm.pdf |mxnorm.html✨
mxnorm/json (API)

# Install 'mxnorm' in R:

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

Bug tracker:https://github.com/colemanrharris/mxnorm/issues

Datasets:

mx_sample - Sample multiplexed dataset for 'mxnorm'.

On CRAN:

4.48 score 6 stars 7 scripts 297 downloads 9 exports 123 dependencies

Last updated 2 years agofrom:ac6cd78772. Checks:OK: 1 NOTE: 5 ERROR: 1. Indexed: yes.

Target	Result	Date
Doc / Vignettes	OK	Nov 21 2024
R-4.5-win	NOTE	Nov 21 2024
R-4.5-linux	NOTE	Nov 21 2024
R-4.4-win	NOTE	Nov 21 2024
R-4.4-mac	NOTE	Nov 21 2024
R-4.3-win	NOTE	Nov 21 2024
R-4.3-mac	ERROR	Nov 21 2024

Exports:mx_dataset mx_normalize plot_mx_density plot_mx_discordance plot_mx_proportions plot_mx_umap run_otsu_discordance run_reduce_umap run_var_proportions

Dependencies:ash BH bitops boot caret class cli clock cluster codetools colorspace cpp11 data.table deSolve diagram digest dplyr dqrng e1071 fansi farver fda fds FNN foreach foreign fossil future future.apply generics ggplot2 globals glue gower GPArotation gtable hardhat hdrcde here ipred irlba isoband iterators jsonlite kernlab KernSmooth ks kSamples labeling lattice lava lifecycle listenv lme4 locfit lubridate magrittr maps MASS Matrix mclust mgcv minqa mnormt ModelMetrics multicool munsell mvtnorm nlme nloptr nnet numDeriv parallelly pcaPP pillar pkgconfig plyr png pracma pROC prodlim progressr proxy psych purrr R6 rainbow rappdirs RColorBrewer Rcpp RcppAnnoy RcppEigen RcppProgress RcppTOML RCurl recipes reshape2 reticulate rlang rpart rprojroot RSpectra scales shape shapefiles sitmo sp SQUAREM stringi stringr SuppDists survival tibble tidyr tidyselect timechange timeDate tzdb utf8 uwot vctrs viridisLite withr

The mxnorm package for removing slide-to-slide variation in multiplexed imaging data

| Coleman Harris | Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA

Rendered frommxnorm-vignette.Rmdusingknitr::rmarkdownon Nov 21 2024.

Last update: 2022-02-22
Started: 2022-02-04

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Generates mx_dataset	mx_dataset
Normalizes multiplexed data	mx_normalize
Sample multiplexed dataset for 'mxnorm'.	mx_sample
Visualize marker density before/after normalization by marker and slide	plot_mx_density
Visualize Otsu discordance scores by marker and slide	plot_mx_discordance
Visualize variance proportions by marker and table	plot_mx_proportions
Visualize UMAP dimension reduction algorithm	plot_mx_umap
Extension of 'print' S3 method to print 'summary.mx_dataset' objects	print.summary.mx_dataset
Calculate Otsu discordance scores using specified threshold for an 'mx_dataset' object.	run_otsu_discordance
Run UMAP dimension reduction algorithm on an 'mx_dataset' object.	run_reduce_umap
Run random effects modeling on 'mx_dataset' object to determine proportions of variance at the slide level	run_var_proportions
Extension of 'summary' S3 method to summarize 'mx_dataset' objects	summary.mx_dataset