test_var_main: Differential variability test
In WeiqiangZhou/SCDV: Single cell differential variance analysis

Description Usage Arguments Value Examples

This function is used for testing differential variability.

1
2
3

test_var_main(treatment_data, treatment_data_weight, control_data,
  control_data_weight, num_permute = 1000, ncore = 1,
  log_transform = TRUE)

`treatment_data`	Normalized count data for the treatment group
`treatment_data_weight`	1 - dropout probability for the treatment group
`control_data`	Normalized count data for the control group
`control_data_weight`	1 - dropout probability for the control group
`num_permute`	Number of permutation performed in the test
`ncore`	Number of CPU cores used in the test
`log_transform`	If TRUE, take log2 transformation after adding a pseudo count of 1 to the input data. Default TRUE.

`statistics`	The weighted F-statistics
`pval_greater`	P-values for testing whether the variability of each gene in the treatment group is larger than that in the control group
`fdr_greater`	Adjusted p-values (FDR) of pval_greater
`pval_less`	P-values for testing whether the variability of each gene in the treatment group is smaller than that in the control group
`fdr_less`	Adjusted p-values (FDR) of pval_less
`pval_ts`	P-values for testing whether the variability of each gene in the treatment group is not equal to that in the control group
`fdr_ts`	Adjusted p-values (FDR) of pval_ts

## Not run: 
diff_var <- test_var_main(treatment_data_adjust,treatment_data_weight,control_data_adjust,control_data_weight,num_permute=10000,ncore=6,log_transform=TRUE)
write.csv(data.frame(match_gene_name,diff_var),file="diff_var.csv",row.names=FALSE)

## End(Not run)