Description Usage Arguments Value Examples
Takes a linear regression matrix and sets infinites to a finite value, and changes the sign to match the sign of the correlation for each value.
1 2 | postProcessLinRegMatrix(input_matrix, LM_mat, cor_type = "pearson",
inf_replacement_val = 300)
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input_matrix |
The input matrix, which consists of bins and samples (no LM or correlation has been done on the segmentation values) |
LM_mat |
The linear regression matrix, with rows and columns consisting of bins and the values being the negative log p-value between them. |
cor_type |
The correlation type ("pearson" (linear), "spearman" (rank), "kendall"(also rank-based)). Rank correlations capture nonlinear relationships as well as linear. Passed to stats::cor's method parameter. |
inf_replacement_val |
the value for which infinites are replaced, by default 300. |
The output matrix, or if using slurm, the slurm job object (which should be saved as an rds file and reloaded when creating the output matrix).
1 2 3 4 5 6 7 8 9 | inputmat<-matrix(runif(15),nrow=3)
colnames(inputmat)<-c("chr2_1_1000","chr2_1001_2000","chr2_2001_3000","chr2_3001_4000",
"chr2_4001_5000")
rownames(inputmat)<-c("PAFPJK","PAKKAT","PUFFUM")
outputmat<-matrix(runif(15),nrow=3)
outputmat<-cor(inputmat)*matrix(runif(25,-30,500),nrow=5)
diag(outputmat)<-Inf
postProcessLinRegMatrix(input_matrix=t(inputmat),LM_mat=outputmat,cor_type="pearson",
inf_replacement_val=300)
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