Description Usage Arguments Value See Also Examples
Generate metadata (HVGs, PC-related genes, pathways) for one single cell RNAseq represented by gene-cell count table
1 2 3 4 5 6 7 | Bio_OnescRNAseq(
scdata,
nHVGs = 1000,
nPCs = 10,
PCind = 1,
organism = "mmusculus"
)
|
scdata |
a SingleCellExperiment object; (results from |
nHVGs |
integer; the number of highly variable genes (default: 1000) |
nPCs |
integer: the number of principal components (default: 10) |
PCind |
integer; which principal component for exploring biological featues (default: 1; the first principal component will be used to find genes highly correlated with PCA 1); PCind should be less than nPC |
organism |
string; the organism of single cell RNAseq datasets; if supported by WebGestaltR, functional enrichment analysis will be performed (defeault: mmusculus) |
a new SingleCellExperiment object by adding features into the the elementMetadata and metadata slots of the input object:
rowRanges@elementMetadata;
hvg: a dataframe containing mean, variance and z-score for dispersion
genevar_by_tounts: variance explained by the log-transformed counts
genevar_by_features: variance explained by the log-transformed features
genevar_by_Mt: variance explained by the log-transformed mitochondrial counts
genevar_by_rRNA: variance explained by the log-transformed rRNA counts
metadata: A list containing other metadata, including
pc1genes: a dataframe containing the genes highly correlated with the 1st (default) or the PCind principal component
pc1Pathway: a dataframe containing the pathways enriched in pc1 (default) or the PCind genes
hvgPathway: a dataframe containing the pathways enriched in top n (default:1000) highly variable genes
Process_OnescRNAseq
, Tech_OnescRNAseq
1 2 3 4 5 | library(scRNABatchQC)
sce<-Tech_OnescRNAseq(input="https://github.com/liuqivandy/scRNABatchQC/raw/master/bioplar1.csv.gz")
sce<-Bio_OnescRNAseq(sce)
head(sce@rowRanges@elementMetadata)
sce@metadata$hvgPathway
|
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