Description Usage Arguments Value Examples
Utility function to generate a pagoda2 app from a conos object
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | p2app4conos(
conos,
cdl = NULL,
metadata = NULL,
filename = "conos_app.bin",
save = TRUE,
n.cores = 1,
n.odgenes = 3000,
nPcs = 100,
k = 30,
perplexity = 50,
log.scale = TRUE,
trim = 10,
keep.genes = NULL,
min.cells.per.gene = 0,
min.transcripts.per.cell = 100,
get.largevis = TRUE,
get.tsne = TRUE,
make.geneknn = TRUE,
go.env = NULL,
cell.subset = NULL,
max.cells = Inf,
additional.embeddings = NULL,
test.pathway.overdispersion = FALSE,
organism = NULL,
return.details = FALSE
)
|
conos |
Conos object |
cdl |
list Optional list of raw matrices (so that gene merging doesn't have to be redone) (default=NULL) |
metadata |
list Optional list of (named) metadata factors (default=NULL) |
filename |
string Name of the *.bin file to seralize for the pagoda2 application if save=TRUE (default='conos_app.bin') |
save |
boolean Save serialized *bin file specified in filename (default=TRUE) |
n.cores |
integer Number of cores (default=1) |
n.odgenes |
numeric Number of top overdispersed genes to use (dfault=3e3). From pagoda2::basicP2proc(). |
nPcs |
numeric Number of PCs to use (default=100). From pagoda2::basicP2proc(). |
k |
numeric Default number of neighbors to use in kNN graph (default=30). From pagoda2::basicP2proc(). |
perplexity |
numeric Perplexity to use in generating tSNE and largeVis embeddings (default=50). From pagoda2::basicP2proc(). |
log.scale |
boolean Whether to use log scale normalization (default=TRUE). From pagoda2::basicP2proc(). |
trim |
numeric Number of cells to trim in winsorization (default=10). From pagoda2::basicP2proc(). |
keep.genes |
optional set of genes to keep from being filtered out (even at low counts) (default=NULL). From pagoda2::basicP2proc(). |
min.cells.per.gene |
numeric Minimal number of cells required for gene to be kept (unless listed in keep.genes) (default=0). From pagoda2::basicP2proc(). |
min.transcripts.per.cell |
numeric Minimumal number of molecules/reads for a cell to be admitted (default=100). From pagoda2::basicP2proc(). |
get.largevis |
boolean Whether to caluclate largeVis embedding (default=TRUE). From pagoda2::basicP2proc(). |
get.tsne |
boolean Whether to calculate tSNE embedding (default=TRUE). From pagoda2::basicP2proc(). |
make.geneknn |
boolean Whether pre-calculate gene kNN (for gene search) (default=TRUE). From pagoda2::basicP2proc(). |
go.env |
GO environment for the organism of interest (default=NULL) |
cell.subset |
string Cells to subset with the conos embedding conos$embedding. If NULL, uses all cells via rownames(conos$embedding) (default=NULL) |
max.cells |
numeric Limit to the cells that are included in the conos. If Inf, there is no limit (default=Inf) |
additional.embeddings |
list Additional embeddings to add to conos for the pagoda2 app (default=NULL) |
test.pathway.overdispersion |
boolean Find all IDs using GO category against either org.Hs.eg.db ('hs') or org.Mm.eg.db ('mm') (default=FALSE |
organism |
string Organism of interest, either 'hs' (Homo sapiens) or 'mm' (Mus musculus, i.e. mouse) (default=NULL). Only used if test.pathway.overdispersion is TRUE. If NULL and test.pathway.overdispersion=TRUE, then 'hs' is used. |
return.details |
boolean If TRUE, return list of p2 application, pagoda2 object, list of raw matrices, and cell names. If FALSE, simply return pagoda2 app object. (default=FALSE) |
pagoda2 app object
1 2 3 4 5 6 7 8 9 10 |
library(pagoda2)
panel.preprocessed <- lapply(conosPanel::panel, basicP2proc, n.cores=1, min.cells.per.gene=0,
n.odgenes=2e3, get.largevis=FALSE, make.geneknn=FALSE)
con <- Conos$new(panel.preprocessed, n.cores=1)
con$buildGraph(k=30, k.self=5, space='PCA', ncomps=30, n.odgenes=2000, matching.method='mNN',
metric='angular', score.component.variance=TRUE, verbose=TRUE)
con$findCommunities(method=leiden.community, resolution=1)
con$embedGraph(alpha=0.001, sgd_batched=1e8)
p2app4conos(con)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.