estimate_Schwabe_stage: Assign cell cycle stages using Schwabe method

In hansenlab/tricycle: tricycle: Transferable Representation and Inference of cell cycle

Assign cell cycle stages using Schwabe method

Description

The function is a re-implementation of cell cycle stage assignment method proposed in Schwabe et al.(2020), with a little modification. The core assignment method is not designed by the authors of this package!

Usage

estimate_Schwabe_stage(
  x,
  exprs_values = "logcounts",
  batch.v = NULL,
  altexp = NULL,
  cycleGene.l = NULL,
  gname = NULL,
  gname.type = c("ENSEMBL", "SYMBOL"),
  species = c("mouse", "human"),
  AnnotationDb = NULL,
  corThres = 0.2,
  tolerance = 0.3
)

Arguments

x	A numeric matrix of **log-expression** values where rows are features and columns are cells. Alternatively, a SummarizedExperiment or SingleCellExperiment containing such a matrix.
exprs_values	Integer scalar or string indicating which assay of x contains the **log-expression** values, which will be used for projection. If the projection already exists, you can ignore this value. Default: 'logcounts'
batch.v	A string specifies which column in colData of SummarizedExperiment or SingleCellExperiment to use as the batch variable. Or it can be a vector, of which the number of elements equals to the number of columns of x. The 5 stage cell cycle assignments are preformed for each batch separately. No NA is permitted. Default: NULL
altexp	String or integer scalar specifying an alternative experiment containing the **log-expression** data, which will be used for projection. If the projection is already calculated and stored in the SingleCellExperiment as a dimred, leave this value to default NULL.
cycleGene.l	A list contains the marker genes for each stage. The stage names should be included as names of the elements. If user feed custom list, they should make sure that the same gene id type for x and cycleGene.l. If not custom list is given, RevelioGeneList will be used. Default: NULL
gname	Alternative rownames of x. If provided, this will be used to map genes within x with genes in ref.m. If not provided, the rownames of x will be used instead. Default: NULL
gname.type	The type of gene names as in gname or rownames of x. It can be either 'ENSEMBL' or 'SYMBOL'. If the user uses custom ref.m, this value will have no effect. Default: 'ENSEMBL'
species	The type of species in x. It can be either 'mouse' or 'human'. If the user uses custom cycleGene.l, this value will have no effect. Default: 'mouse'
AnnotationDb	An AnnotationDb objects. It is used to map ENSEMBL IDs to gene SYMBOLs. If no AnnotationDb object being given, the function will use org.Hs.eg.db or org.Mm.eg.db for human and mouse respectively.
corThres	For each batch and each stage, correlations between expression of each gene and the mean of all genes belonging to that stage will be calculated to filter the final gene list used for inference. The genes with a correlation between corThres will not be used for calculating z-scores. Default: 0.2
tolerance	For each cell, the function will compare the largest two z-scores. If the difference between those two z-scores is less than tolerance, the cell will be treated un-assignable with NA value returned for that cell. Default: 0.3

Details

The function is a re-implementation of cell cycle stage assignment method proposed in Schwabe et al.(2020), with a little modification. We include this function only for the purpose of convenience. The core assignment method is not designed by the authors of this package! Breiefly, the function assigns cells to discretized cell cycle stages by comparing the z-scores calculated for each stage markers. Without cycleGene.l input, RevelioGeneList will be used. If you use this function, you should cite Schwabe et al.(2020).

Value

If the input is a numeric matrix, the discretized cell cycle stages - a factor vector corresponding to each cell will be returned.

If the input is SummarizedExperiment, the original SummarizedExperiment with the discretized cell cycle stages stored in colData with name 'CCStage' will be returned.

If the input is SingleCellExperiment, the original SingleCellExperiment with the discretized cell cycle stages stored in colData with name 'CCStage' will be returned.

Author(s)

Shijie C. Zheng

References

Schwabe D, et al. The transcriptome dynamics of single cells during the cell cycle. Molecular Systems Biology (2020) 16: e9946 doi:10.15252/msb.20209946.

Zheng SC, et al. Universal prediction of cell cycle position using transfer learning. Genome Biology (2022) 23: 41 doi:10.1186/s13059-021-02581-y.

Examples

data(neurosphere_example, package = "tricycle")
neurosphere_example <- estimate_Schwabe_stage(neurosphere_example,
 gname.type = "ENSEMBL", species = "mouse")
neurosphere_example2 <- estimate_Schwabe_stage(neurosphere_example, batch.v = "sample")
neurosphere_example3 <- estimate_Schwabe_stage(neurosphere_example,
 batch.v = neurosphere_example$sample)
neurosphere_example <- project_cycle_space(neurosphere_example)
plot(reducedDim(neurosphere_example, "tricycleEmbedding"),
 col = neurosphere_example$CCStage)

hansenlab/tricycle documentation built on March 19, 2022, 7:24 p.m.