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https://github.com/jdekanter/CHETAH

scRNA-seq cell type identification
https://github.com/jdekanter/CHETAH

Last synced: 23 days ago
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scRNA-seq cell type identification

Host: GitHub
URL: https://github.com/jdekanter/CHETAH
Owner: jdekanter
License: agpl-3.0
Created: 2018-11-07T15:02:47.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2019-10-03T02:10:44.000Z (over 4 years ago)
Last Synced: 2024-05-14T15:45:08.092Z (about 2 months ago)
Language: R
Size: 3.5 MB
Stars: 39
Watchers: 3
Forks: 9
Open Issues: 3
Metadata Files:
- Readme: README.md
- License: LICENSE

Lists

awesome_single_cell - CHETAH - [R] - CHETAH: a selective, hierarchical cell type identification method for single-cell RNA sequencing. CHETAH (CHaracterization of cEll Types Aided by Hierarchical clustering) is an accurate cell type identification algorithm that is rapid and selective, including the possibility of intermediate or unassigned categories. Evidence for assignment is based on a classification tree of previously available scRNA-seq reference data and includes a confidence score based on the variance in gene expression per cell type. For cell types represented in the reference data, CHETAH's accuracy is as good as existing methods. Its specificity is superior when cells of an unknown type are encountered, such as malignant cells in tumor samples which it pinpoints as intermediate or unassigned. [bioRxiv](https://doi.org/10.1101/558908) (Software packages / Cell type identification and classification)
awesome-single-cell - CHETAH - [R] - CHETAH: a selective, hierarchical cell type identification method for single-cell RNA sequencing. CHETAH (CHaracterization of cEll Types Aided by Hierarchical clustering) is an accurate cell type identification algorithm that is rapid and selective, including the possibility of intermediate or unassigned categories. Evidence for assignment is based on a classification tree of previously available scRNA-seq reference data and includes a confidence score based on the variance in gene expression per cell type. For cell types represented in the reference data, CHETAH's accuracy is as good as existing methods. Its specificity is superior when cells of an unknown type are encountered, such as malignant cells in tumor samples which it pinpoints as intermediate or unassigned. [bioRxiv](https://doi.org/10.1101/558908) (Software packages / Cell type identification and classification)
awesome-single-cell - CHETAH - [R] - CHETAH: a selective, hierarchical cell type identification method for single-cell RNA sequencing. CHETAH (CHaracterization of cEll Types Aided by Hierarchical clustering) is an accurate cell type identification algorithm that is rapid and selective, including the possibility of intermediate or unassigned categories. Evidence for assignment is based on a classification tree of previously available scRNA-seq reference data and includes a confidence score based on the variance in gene expression per cell type. For cell types represented in the reference data, CHETAH's accuracy is as good as existing methods. Its specificity is superior when cells of an unknown type are encountered, such as malignant cells in tumor samples which it pinpoints as intermediate or unassigned. [bioRxiv](https://doi.org/10.1101/558908) (Software packages / Cell type identification and classification)

README

        # CHETAH: a selective, hierarchical cell type identification method for single-cell RNA sequencing

__CHETAH is an R package for cell type identification of single-cell RNA-sequencing (scRNA-seq) data.__

Cell types are assigned by correlating the input data to a reference in a hierarchical manner. CHETAH is built to work with scRNA-seq references, but will also work (with limited capabilities) with RNA-seq or micro-array reference datasets.

The article describing CHETAH can be found at: [Nucleic Acids Research](https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkz543/5521789?searchresult=1).  

> CHETAH is now part of [Bioconductor](https://www.bioconductor.org/packages/release/bioc/html/CHETAH.html).  

CHETAH can be installed by running:

```{r echo=TRUE, eval=FALSE}

if (!requireNamespace("BiocManager", quietly = TRUE))

    install.packages("BiocManager")

BiocManager::install("CHETAH")

```

To get to know the basics of the CHETAH pacakge, please look at the vignette;

```{r echo=TRUE, eval=FALSE}

vignette("CHETAH_introduction")

```

At a glance: to run chetah on an input count matrix `input_counts` with t-SNE coordinates in `input_tsne`, and a reference count matrix `ref_counts` with celltypes vector `ref_ct`, run:  

```{r glance, echo=TRUE, eval=FALSE}

## Make SingleCellExperiments

reference <- SingleCellExperiment(assays = list(counts = ref_counts),

                                     colData = DataFrame(celltypes = ref_ct))

input <- SingleCellExperiment(assays = list(counts = input_counts),

                              reducedDims = SimpleList(TSNE = input_tsne))

## Run CHETAH

input <- CHETAHclassifier(input = input, ref_cells = reference)

## Plot the classification

PlotCHETAH(input)

## Extract celltypes:

celltypes <- input$celltype_CHETAH

```