MAC_perm: Function to perform a permutation analysis to determine a...

In LEAP: Constructing Gene Co-Expression Networks for Single-Cell RNA-Sequencing Data Using Pseudotime Ordering

Description

See vignette for more details.

Usage

 MAC_perm(data, MACs_observ, num_perms = 100, max_lag_prop = 1/3, 
 FDR_cutoffs = 101, perm_file_name = F)

Arguments

data	A data matrix for which the rows are genes and the columns are experiments, sorted by their pseudotime.
MACs_observ	The resulting matrix of MACs from running MAC_counter on the dataset
num_perms	The number of permutations to be performed. Default is 100.
max_lag_prop	The largest proportion of your experiments that you want the size of the lag to be. Recommended not to go beyond 1/3. Default value is 1/3.
FDR_cutoffs	The number of cutoffs between 0 and 1 to use for FDR analysis. Default value is 101, resulting in 0,0.01,0.02,...,0.98,0.99,1.
perm_file_name	The name to be used for resulting .csv file. I.e., using perm_file_name="mine" would create the file "perm_mine.csv"

Details

See vignette for more details.

Value

Returns a dataset with four columns: cors are the correlation cutoffs, MACs_observed are the number of observed correlations at that cutoff, MACs_ave_perm are the average number observed in the permuted datasets at that cutoff, and fdr is the false discovery rate (FDR) observed at that cutoff.

Examples

x <- matrix(rnorm(6),2,3)
cor <- cor(x)
y <- MAC_perm(x, cor)

## Not run: MAC_perm(data=example_data, MACs_observ=MAC_example)

LEAP documentation built on May 1, 2019, 9:23 p.m.