Name Mode Size
..
bin_scdata.Rd 100644 2 kb
calculate_cvs.Rd 100644 2 kb
correlate_windows.Rd 100644 2 kb
correlations_to_densities.Rd 100644 1 kb
define_top_genes.Rd 100644 2 kb
determine_bin_cutoff.Rd 100644 2 kb
filter_expression_table.Rd 100644 1 kb
get_mean_median.Rd 100644 1 kb
plot_correlations_distributions.Rd 100644 2 kb
plot_mean_variance.Rd 100644 2 kb
plot_metric.Rd 100644 2 kb
plot_top_window_autocor.Rd 100644 1 kb
scData_hESC.Rd 100644 1 kb
sc_feature_filter.Rd 100644 2 kb
README.md
# scFeatureFilter By Angeles Arzalluz-Luque, Guillaume Devailly, Anna Mantsoki & Anagha Joshi. ![scFeatureFilter outputs](inst/figure1_small.png) An R package to set thresholds for feature (gene, transcript, ...) filtering in single cell RNA sequencing analyses. # How to install? You can install the stable version of scFeatureFilter from Bioconductor (Require R version ≥ 3.5): ```R ## try http:// if https:// URLs are not supported if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install("scFeatureFilter") ``` You can install the development version of scFeatureFilter using `devtools` (Require R version ≥ 3.5): ```R devtools::install_github("gdevailly/scFeatureFilter") ``` # Getting started Load the package: ```R library(scFeatureFilter) ``` Then it is probably a good idea to read the package [vignette](https://gdevailly.github.io/scFeatureFilterVignette.html): ```R vignette("Introduction", package = "scFeatureFilter") ```