RaceID3_StemID2_package

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RaceID3_StemID2_package

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Algorithm for the inference of cell types and lineage trees from single-cell RNA-seq data. This is a novel R package of the RaceID3 and StemID2 method including novel functionalities and performance improvements compared to the previous RaceID3/StemID2 version in the RaceID3_StemID2 repository. The RaceID3_StemID2 repository will not be updated anymore in the future.

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# RaceID/StemID/VarID algorithm

RaceID is a clustering algorithm for the identification of cell types
from single-cell RNA-sequencing data. It was specifically designed for
the detection of rare cells which correspond to outliers in
conventional clustering methods. The package contains RaceID3, the
most recently published version of this algorithm, and StemID2, an
algorithm for the identification of lineage trees based on RaceID3
analysis. RaceID3 utilizes single cell expression data, and was
designed to work well with quantitative single-cell RNA-seq data
incorporating unique molecular identifiers. It requires a gene-by-cell
expression matrix as input and produces a clustering partition
representing cell types. StemID2 assembles these cell types into a
lineage tree.
The RaceID package (>= v0.1.4) also contains functions for a VarID
analysis. VarID comprises a sensitive clustering method utilizing pruned
k-nearest neighbor networks, connecting only cells with links
supported by a background model of gene expression. These pruned
k-nearest neighbor networks further enable the definition of homogenous
neighborhoods for the quantification of local gene expression
variability in cell state space.

## Installing

After downloading and unzipping
```
unzip RaceID3_StemID2_package-master.zip 
```

it can be installed from the command line by
```
R CMD INSTALL RaceID3_StemID2_package-master
```

or directly in R from source by
```
install.packages("RaceID3_StemID2_package-master",repos = NULL, type="source")
```
(if R is started from the directory where `RaceID3_StemID2_package-master.zip` has been downloaded to; otherwise specify the full path)

Alternatively, install in R directly from github using devtools:
```
install.packages("devtools")
library(devtools)
install_github("dgrun/RaceID3_StemID2_package")
```

## Running a RaceID/StemID/VarID analysis

Load package:
```
library(RaceID)
```

See vignette for details and examples:
```
vignette("RaceID")
```

## Reference:

Rosales-Alvarez RE,  Rettkowski J, Herman JS, Dumbovic G, Cabezas-Wallscheid N, Grün D (2022) VarID2 quantifies gene expression noise dynamics and unveils functional heterogeneity of ageing hematopoietic stem cells. Genome Biology 24(1):148. doi: 10.1186/s13059-023-02974-1.

Grün D (2020) Revealing Dynamics of Gene Expression Variability in Cell State Space. Nature Methods 17(1):45-49.  doi: 10.1038/s41592-019-0632-3

Herman JS, Sagar, Grün D. (2018) FateID infers cell fate bias in multipotent progenitors from single-cell RNA-seq data. Nature Methods. 2018 May;15(5):379-386. doi: 10.1038/nmeth.4662.

RaceID3_StemID2_package

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