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cytominer
View on CRAN: Click
here
Download and install cytominer package within the R console
Install from CRAN:
install.packages("cytominer")
Install from Github:
library("remotes")
install_github("cran/cytominer") Install by package version:
library("remotes")
install_version("cytominer", "0.2.2") Attach the package and use:
library("cytominer")
Maintained by
Shantanu Singh
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-09-17
Latest Update: 2020-05-09
Description:
Typical morphological profiling datasets have millions of cells
and hundreds of features per cell. When working with this data, you must
clean the data, normalize the features to make them comparable across
experiments, transform the features, select features based on their
quality, and aggregate the single-cell data, if needed. 'cytominer' makes
these steps fast and easy. Methods used in practice in the field are
discussed in Caicedo (2017) . An overview of the
field is presented in Caicedo (2016) .
How to cite:
Shantanu Singh (2017). cytominer: Methods for Image-Based Cell Profiling. R package version 0.2.2, https://cran.r-project.org/web/packages/cytominer. Accessed 22 Sep. 2026.
Previous versions and publish date:
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Other R packages that cytominer depends,
imports, suggests or enhances
Complete documentation for cytominer
Functions, R codes and Examples using
the cytominer R package
Some associated functions: aggregate . correlation_threshold . count_na_rows . covariance . drop_na_columns . drop_na_rows . extract_subpopulations . generalized_log . generate_component_matrix . normalize . replicate_correlation . sparse_random_projection . svd_entropy . transform . variable_importance . variable_select . variance_threshold . whiten .
Some associated R codes: aggregate.R . correlation_threshold.R . count_na_rows.R . covariance.R . drop_na_columns.R . drop_na_rows.R . extract_subpopulations.R . generalized_log.R . normalize.R . replicate_correlation.R . sparse_random_projection.R . svd_entropy.R . transform.R . variable_importance.R . variable_select.R . variance_threshold.R . whiten.R . Full cytominer package functions and examples
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