RCSL is an R toolkit for single-cell clustering and trajectory analysis using single-cell RNA-seq data.

This package can be installed through devtools in R:

```
$ R
> library("devtools")
> devtools::install_github("QinglinMei/RCSL")
```

Now RCSL can be loaded in R:

`> library(RCSL)`

The input of RCSL is a normalized data matrix with columns being cells and rows being genes in log(CPM+1), log(RPKM+1), log(TPM+1) or log(FPKM+1) format; or a data file in RDS format.

We provide an example script to run RCSL in *demo_RCSL.R*.

The nine functions of RCSL can also be run independently.

Function | Description |
---|---|

`GenesFilter` |
Perform genes filtering. |

`SimS` |
Calculate the initial similarity matrix S. |

`NeigRepresent` |
Calculate the neighbor representation of cells. |

`EstClusters` |
Estimate the optimal number of clusters C. |

`BDSM` |
Learn the block-diagonal matrix B. |

`PlotMST` |
Construct MST based on clustering results from RCSL. |

`PlotPseudoTime` |
Infer the pseudo-temporal ordering of cells. |

`getLineage` |
Infer the lineage based on the clustering results and the starting cell. |

`PlotTrajectory` |
Plot the developmental trajectory based on the clustering results and the starting cell. |

Load packages:

```
> library(RCSL)
> library(SingleCellExperiment)
> library(ggplot2)
> library(igraph)
```

Load Yan dataset:

```
> origData <- yan
> data <- logcounts(origData+1)
> label <- origData$cell_type1
> DataName <- "Yan"
```

Generating clustering result:

`> res_RCSL <- RCSL(data)`

Calculating Adjusted Rand Index:

`> ARI_RCSL <- igraph::compare(res_RCSL$y, label, method = "adjusted.rand")`

Trajectory analysis:

```
> label <- origData$cell_type1
> res_TrajecAnalysis <- TrajectoryAnalysis(res_RCSL$gfData, res_RCSL$drData, res_RCSL$S,
clustRes = res_RCSL$y, TrueLabel = label, startPoint = 1,
dataName = DataName)
```

Display the plot of constructed MST:

`> res_TrajecAnalysis$MSTPlot`

Display the plot of the pseudo-temporal ordering

`> res_TrajecAnalysis$PseudoTimePlot`

Display the plot of the inferred developmental trajectory

`> res_TrajecAnalysis$TrajectoryPlot`

A vignette in R Notebook format is available here

- The RCSL package requires three extra packages: namely the
*SingleCellExperiment*package (see https://bioconductor.org/packages/release/bioc/html/SingleCellExperiment.html) to read the*SingleCellExperiment*object, the*igraph*package (see https://igraph.org/) to find the strongest connected components and the*ggplot2*package (see https://cran.r-project.org/web/packages/ggplot2/index.html) to plot the developmental trajectory and MST. - The data for the demonstration purpose in the directory
*Data*was from https://hemberg-lab.github.io/scRNA.seq.datasets/. This data is stored in both RDS and text formats.

Please feel free to contact us if you have problems running our tool at meiqinglinkf@163.com.