Inferring a trajectory inference using RaceID / StemID

Will generate a trajectory using RaceID / StemID.

This method was wrapped inside a container. The original code of this method is available here.

ti_raceid_stemid(knn = 10L, ccor = 0.4, metric = "pearson",
  sat = TRUE, samp = 1000L, cln = 30L, clustnr = 30L,
  bootnr = 50L, FUNcluster = "kmedoids", probthr = 0.001,
  outminc = 5L, outlg = 2L, outdistquant = 0.95,
  initial_cmd = TRUE, perplexity = 30L, cthr = 5L, nmode = TRUE,
  projcells_knn = 3L, fr = FALSE, pdishuf = 500L, fast = FALSE,
  pthr = 0.01, scthr = 0.2, run_environment = NULL)

Arguments

knn	integer; Number of nearest neighbors used to infer corresponding cell types in different batches. (default: 10L; range: from 5L to 50L)
ccor	numeric; Correlation coefficient used as a treshhold for determining genes correlated to eachother. (default: 0.4; range: from 0 to 1)
metric	discrete; Distances are computed from the filtered expression matrix after optional feature selection, dimensional reduction, and/or transformation (batch correction). (default: "pearson"; values: "pearson", "spearman", "logpearson", "euclidean")
sat	logical; If TRUE, then the number of clusters is determined based on finding the saturation point of the mean within-cluster dispersion as a function of the cluster number. If FALSE, then cluster number needs to be given as cln.
samp	integer; Number of booststrapping runs for clusterboot. Default is 50 (default: 1000L; range: from 50L to 10000L)
cln	integer; Number of clusters to be used. If sat is TRUE, this number is inferred by the saturation criterion. (default: 30L; range: from 10L to 100L)
clustnr	integer; Maximum number of clusters for the derivation of the cluster number by the saturation of mean within-cluster-dispersion. (default: 30L; range: from 10L to 100L)
bootnr	integer; Number of booststrapping runs for clusterboot. (default: 50L; range: from 20L to 100L)
FUNcluster	discrete; Clustering method used by RaceID3. (default: "kmedoids"; values: "kmedoids", "kmeans", "hclust")
probthr	numeric; Outlier probability threshold for a minimum of outlg genes to be an outlier cell. This probability is computed from a negative binomial background model of expression in a cluster. (default: 0.001; range: from 1e-05 to 1L)
outminc	integer; Minimal transcript count of a gene in a clusters to be tested for being an outlier gene. (default: 5L; range: from 0L to 100L)
outlg	integer; Minimum number of outlier genes required for being an outlier cell. (default: 2L; range: from 0L to 100L)
outdistquant	numeric; Real number between zero and one. Outlier cells are merged to outlier clusters if their distance smaller than the outdistquant-quantile of the distance distribution of pairs of cells in the orginal clusters after outlier removal. (default: 0.95; range: from 0 to 1)
initial_cmd	logical; If TRUE, then the t-SNE map computation is initialized with a configuration obtained by classical multidimensional scaling.
perplexity	integer; Perplexity of the t-SNE map. (default: 30L; range: from 5L to 100L)
cthr	integer; Clusters to be included into the StemID2 analysis must contain more than cthr cells. D (default: 5L; range: from 1L to 25L)
nmode	logical; If TRUE, then a cell of given cluster is assigned to the link to the cluster with the smallest average distance of the knn nearest neighbours within this cluster.
projcells_knn	integer; See nmode. (default: 3L; range: from 3L to 20L)
fr	logical; Use Fruchterman-Rheingold layout instead of t-SNE for dimensional-reduction representation of the lineage tree.
pdishuf	integer; Number of randomizations of cell positions for which to compute projections of cells on inter-cluster links. (default: 500L; range: from 10L to 10000L)
fast	logical; If TRUE and nmode is FALSE cells will still be assigned to links based on maximum projections but a fast approximate background model will be used to infer significance. The function will do nothing in this case.
pthr	numeric; P-value cutoff for link significance. This threshold is applied for the calculation of link scores reflecting how uniformly a link is occupied by cells. (default: 0.01; range: from 1e-05 to 1L)
scthr	numeric; Score threshold for links to be shown in the graph. (default: 0.2; range: from 0 to 1)
run_environment	In which environment to run the method, can be "docker" or "singularity".

Value

A TI method wrapper to be used together with infer_trajectory

References

Grün, D., Muraro, M.J., Boisset, J.-C., Wiebrands, K., Lyubimova, A., Dharmadhikari, G., van den Born, M., van Es, J., Jansen, E., Clevers, H., de Koning, E.J.P., van Oudenaarden, A., 2016. De Novo Prediction of Stem Cell Identity using Single-Cell Transcriptome Data. Cell Stem Cell 19, 266–277.