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infercnv 10x
Brian Haas edited this page Oct 31, 2018
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Below provides an example of how you might generate a counts matrix for use with inferCNV, starting with 10x data.
Here, we'll use Seurat for converting 10x count data to a CP100k matrix.
library(Seurat)
data = Read10X(data.dir = "10x_data_dir/")
seurat_obj = CreateSeuratObject(raw.data=data, min.cells=3, min.genes=200)
counts_matrix = as.matrix(seurat_obj@raw.data[,seurat_obj@cell.names])
# use more palatable column names (cell identifiers)
cell.names <- sapply(seq_along(colnames(counts_matrix)), function(i) paste0("cell_", i), USE.NAMES = F)
colnames(counts_matrix) = cell.names
# write the output table
write.table(round(counts_matrix, digits=3), file='sc.10x.counts.matrix', quote=F, sep="\t")
Now, the 'cp100k.log2.matrix' is ready for use with InferCNV.
- InferCNV Home
- Quick Start
- Installing inferCNV
- Running InferCNV
- Applying Noise Filters
- Predicting CNV via HMM
- Bayesian Mixture Model
- Tumor heterogeneity - define tumor subclusters
- Interpreting the Figure
- Inputs to InferCNV
- Outputs from InferCNV
- More inferCNV example data sets
- Using 10x data
- Interactively navigating data using the Next Generation Heatmap Viewer
- Extracting HMM features
- FAQ and common issues