Name Mode Size
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CLR_FN.Rd 100644 1 kb
DESEQ_FN.Rd 100644 1 kb
FQ_FN.Rd 100644 1 kb
SCRAN_FN.Rd 100644 0 kb
SUM_FN.Rd 100644 0 kb
SconeExperiment-class.Rd 100644 6 kb
TMM_FN.Rd 100644 1 kb
UQ_FN.Rd 100644 1 kb
biplot_color.Rd 100644 1 kb
biplot_interactive.Rd 100644 1 kb
control_genes.Rd 100644 3 kb
estimate_ziber.Rd 100644 2 kb
factor_sample_filter.Rd 100644 3 kb
fast_estimate_ziber.Rd 100644 2 kb
get_bio.Rd 100644 1 kb
get_design.Rd 100644 2 kb
get_negconruv.Rd 100644 2 kb
get_normalized.Rd 100644 3 kb
get_params.Rd 100644 1 kb
get_qc.Rd 100644 1 kb
get_scores.Rd 100644 1 kb
impute_expectation.Rd 100644 1 kb
impute_null.Rd 100644 1 kb
lm_adjust.Rd 100644 1 kb
make_design.Rd 100644 1 kb
metric_sample_filter.Rd 100644 4 kb
scone.Rd 100644 8 kb
sconeReport.Rd 100644 2 kb
scone_easybake.Rd 100644 6 kb
score_matrix.Rd 100644 5 kb
select_methods.Rd 100644 2 kb
simple_FNR_params.Rd 100644 1 kb
README.md
## SCONE ## [![Project Status: Active - The project has reached a stable, usable state and is being actively developed.](http://www.repostatus.org/badges/latest/active.svg)](http://www.repostatus.org/#active) [![Build Status](https://travis-ci.org/YosefLab/scone.svg?branch=master)](https://travis-ci.org/YosefLab/scone) [![Coverage](https://codecov.io/gh/YosefLab/scone/branch/master/graph/badge.svg)](https://codecov.io/gh/YosefLab/scone) ### Single-Cell Overview of Normalized Expression data ### SCONE (Single-Cell Overview of Normalized Expression), a package for single-cell RNA-seq data quality control (QC) and normalization. This data-driven framework uses summaries of expression data to assess the efficacy of normalization workflows. ### Install from Bioconductor ### We recommend installation of the package via bioconductor. ```{r} source("https://bioconductor.org/biocLite.R") biocLite("scone") ``` Note that SCONE is currently in Bioconductor devel and hence requires R-devel (>= 3.4). ### Install from Github ### Usually not recommended. SCONE is under active development. To download the development version of the package, use the `devtools` package. ```{r} library(devtools) install_github("YosefLab/scone") ``` ### Install for R 3.3 ### You can download the latest release of SCONE for R 3.3 [here](https://github.com/YosefLab/scone/releases/tag/v0.99.0).