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Seurat (version 1.2.1)

Seurat : R toolkit for single cell genomics

Description

Seurat : R toolkit for single cell genomics

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Version

Install

install.packages('Seurat')

Monthly Downloads

46,322

Version

1.2.1

License

GPL 3.0

Maintainer

Satija Lab

Last Published

October 5th, 2015

Functions in Seurat (1.2.1)

diff.t.test

Differential expression testing using Student's t-test

average.expression

Averaged gene expression by identity class

average.pca

Average PCA scores by identity class

DBclust_dimension

Perform spectral density clustering on single cells

cluster.alpha

Probability of detection by identity class

cellPlot

Cell-cell scatter plot

buildClusterTree

Phylogenetic Analysis of Identity Classes

addImputedScore

Calculate imputed expression values

addMetaData

Add Metadata

batch.gene

Identify potential genes associated with batch effects

diffExp.test

Likelihood ratio test for zero-inflated data

doHeatMap

Gene expression heatmap

dim.plot

Dimensional reduction plot

dot.plot

Dot plot visualization

find_all_markers

Gene expression markers for all identity classes

find.markers

Gene expression markers of identity classes

feature.heatmap

Vizualization of multiple features

fetch.data

Access cellular data

feature.plot

Visualize 'features' on a dimensional reduction plot

doKMeans

K-Means Clustering

find.markers.node

Gene expression markers of identity classes defined by a phylogenetic clade

ica.plot

Plot ICA map

initial.mapping

Infer spatial origins for single cells

get.centroids

Get cell centroids

icHeatmap

Independent component heatmap

jackStraw

Determine statistical significance of PCA scores.

fit.gene.k

Build mixture models of gene expression

genePlot

Scatter plot of single cell data

ica

Run Independent Component Analysis on gene expression

icTopGenes

Find genes with highest ICA scores

plotClusterTree

Plot phylogenetic tree

pcTopGenes

Find genes with highest PCA scores

marker.test

ROC-based marker discovery

mean.var.plot

Identify variable genes

pca

Run Principal Component Analysis on gene expression

pca.sig.genes

Significant genes from a PCA

pcHeatmap

Principal component heatmap

pca.plot

Plot PCA map

Kclust_dimension

Perform spectral k-means clustering on single cells

jackStrawPlot

JackStraw Plot

set.all.ident

Switch identity class definition to another variable

set.ident

Set identity class information

project.pca

Project Principal Components Analysis onto full dataset

refined.mapping

Quantitative refinement of spatial inferences

run_tsne

Run t-distributed Stochastic Neighbor Embedding

rename.ident

Rename one identity class to another

plotNoiseModel

Visualize expression/dropout curve

Return a subset of the Seurat object

print.pca

Print the results of a PCA analysis

tobit.test

Differential expression testing using Tobit models

which.cells

Identify matching cells

Single cell violin plot