cellity: Quality Control for Single-Cell RNA-seq Data

A support vector machine approach to identifying and filtering low quality cells from single-cell RNA-seq datasets.

Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("cellity")
AuthorTomislav Illicic, Davis McCarthy
Bioconductor views DimensionReduction GeneExpression Normalization Preprocessing QualityControl RNASeq Sequencing Software SupportVectorMachine Transcriptomics Visualization
Date of publicationNone
MaintainerTomislav Ilicic <ti243@cam.ac.uk>
LicenseGPL (>= 2)
Version1.4.0

View on Bioconductor

Man pages

assess_cell_quality_PCA: ASSESS CELL QUALITY USING PCA AND OUTLIER DETECTION

assess_cell_quality_SVM: Assess quality of a cell - SVM version

cellity-package: Quality Control for Single-Cell RNA-seq Data

extract_features: Extracts biological and technical features for given dataset

extra_human_genes: Additional human genes that are used in feature extraction

extra_mouse_genes: Additional mouse genes that are used in feature extraction

feature_generation: Helper Function to create all features

feature_info: Information which genes and GO categories should be included...

mES1_features: Real test dataset containing all and common features from the...

mES1_labels: Real test dataset containing annotation of cells

multiplot: Internal multiplot function to combine plots onto a grid

normalise_by_factor: Internal function to normalize by library size

param_mES_all: Parameters used for SVM classification

param_mES_common: Parameters used for SVM classification

plot_pca: Plots PCA of all features. Colors high and low quality cells...

sample_counts: Sample gene expression data containing 40 cells

sample_stats: Sample read statistics data containing 40 cells

simple_cap: Converts all first letters to capital letters

sum_prop: Sums up normalised values of genes to groups.

training_mES_features: Original training dataset containing all and common features...

training_mES_labels: Original training dataset containing annotation of cells

uni.plot: Internal function to detect outliers from the mvoultier...

Functions

assess_cell_quality_PCA Man page
assess_cell_quality_SVM Man page
cellity-package Man page
extract_features Man page
extra_human_genes Man page
extra_mouse_genes Man page
feature_generation Man page
feature_info Man page
mES1_features Man page
mES1_labels Man page
multiplot Man page
normalise_by_factor Man page
param_mES_all Man page
param_mES_common Man page
plot_pca Man page
sample_counts Man page
sample_stats Man page
simple_cap Man page
sum_prop Man page
training_mES_features Man page
training_mES_labels Man page
uni.plot Man page

Files

DESCRIPTION
NAMESPACE
R
R/cellity-package.R R/data.R R/filter_low_qual_cells.R
README.md
build
build/vignette.rds
data
data/extra_human_genes.RData
data/extra_mouse_genes.RData
data/feature_info.RData
data/mES1_features.RData
data/mES1_labels.RData
data/param_mES_all.RData
data/param_mES_common.RData
data/sample_counts.RData
data/sample_stats.RData
data/training_mES_features.RData
data/training_mES_labels.RData
inst
inst/NEWS.Rd
inst/cellity_overview.png
inst/doc
inst/doc/cellity_vignette.R
inst/doc/cellity_vignette.Rmd
inst/doc/cellity_vignette.html
man
man/assess_cell_quality_PCA.Rd man/assess_cell_quality_SVM.Rd man/cellity-package.Rd man/extra_human_genes.Rd man/extra_mouse_genes.Rd man/extract_features.Rd man/feature_generation.Rd man/feature_info.Rd man/mES1_features.Rd man/mES1_labels.Rd man/multiplot.Rd man/normalise_by_factor.Rd man/param_mES_all.Rd man/param_mES_common.Rd man/plot_pca.Rd man/sample_counts.Rd man/sample_stats.Rd man/simple_cap.Rd man/sum_prop.Rd man/training_mES_features.Rd man/training_mES_labels.Rd man/uni.plot.Rd
tests
tests/testthat
tests/testthat.R tests/testthat/test-assess_cell_quality_SVM.R tests/testthat/test-extract_features.R
vignettes
vignettes/cellity_vignette.Rmd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.