Function doing the actual analysis before calling the plotting functions.
run(infercnv_obj, cutoff = 1, min_cells_per_gene = 3, out_dir = ".",
normalize_factor = NA, window_length = 101, num_ref_groups = NULL,
max_centered_threshold = NA, noise_filter = NA, sd_amplifier = 1.5,
cluster_by_groups = FALSE, k_obs_groups = 1,
outlier_method_bound = "average_bound", outlier_lower_bound = NA,
outlier_upper_bound = NA, hclust_method = "complete",
anscombe_normalize = TRUE, use_zscores = FALSE,
remove_genes_at_chr_ends = FALSE, mask_nonDE_genes = TRUE,
mask_nonDE_pval = 0.05, test.use = "wilcoxon", plot_steps = FALSE,
debug = FALSE, include.spike = FALSE, pseudocount = 0)An infercnv object populated with raw count data
Cut-off for the min average read counts per gene among reference cells. (default: 1)
minimum number of reference cells requiring expression measurements to include the corresponding gene. default: 3
path to directory to deposit outputs (default: '.')
scaling factor for total sum of counts (default: NA, in which case will be set = 10^round(log10(mean(colSums))), typically setting to 1e5
Length of the window for the moving average (smoothing). Should be an odd integer. (default: 101)#'
The number of reference groups or a list of indices for each group of reference indices in relation to reference_obs. (default: NULL)
The maximum value a value can have after centering. Also sets a lower bound of -1 * this value.
Values +- from the reference cell mean will be set to zero (whitening effect) default(NA, instead will use sd_amplifier below.
Noise is defined as mean(reference_cells) +- sdev(reference_cells) * sd_amplifier default: 1.0
If observations are defined according to groups (ie. patients), each group of cells will be clustered separately. (default=FALSE, instead will use k_obs_groups setting)
Number of groups in which to break the observations. (default: 1)
Method to use for bounding outlier values. (default: "average_bound") Will preferentially use outlier_lower_bounda and outlier_upper_bound if set.
Outliers below this lower bound will be set to this value.
Outliers above this upper bound will be set to this value.
Method used for hierarchical clustering of cells. Valid choices are: "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", "centroid".
Perform anscombe normalization on normalized counts before log transformation.
If true, converts log(expression) data to zscores based on reference cell expr distribution.
If true, removes the window_length/2 genes at both ends of the chromosome.
If true, sets genes not significantly differentially expressed between tumor/normal to the mean value for the complete data set
p-value threshold for defining statistically significant DE genes between tumor/normal
statistical test to use. (default: "wilcoxon") alternatives include 'perm' or 't'.'
If true, saves infercnv objects and plots data at the intermediate steps.
If true, output debug level logging.
If true, introduces an artificial spike-in of data at ~0x and 2x for scaling residuals between 0-2. (default: F)
Number of counts to add to each gene of each cell post-filtering of genes and cells and pre-total sum count normalization. (default: 0)
infercnv_obj containing filtered and transformed data