Open huangwb8 opened 5 years ago
Moreover,for the result from gdcCEAnalysis function,could you give a suggestion about proper cut-off of parameters for a real ceRNA network?
Hi,
I am trying to use gdcCEAnalysis function and it gives two main errors:
1.) Error in colnames<-
(*tmp*
, value = c("lncRNAs", "Genes", "Counts", :
attempt to set 'colnames' on an object with less than two dimensions
2.)Error in cor.test.default(lncDa, mirDa, alternative = "less") : not enough finite observations.
I believe huangwb8 has suggested some changes regarding same. However, I am new to R and it would really help if you can help me resolve the issue.
When I use it to build ceRNA network,I notice the internal dataset "pcTarget" and "lncTarget" of this package.
QUESTION: According to your published article,you use 3 data sources including StarBase v2.0 (Li et al.,2014), miRcode (Jeggari et al., 2012), and spongeScan (Furio´ -Tarı´et al., 2016).So I was confused when I found only 137 lncRNAs in lncTarget dataset.Whether you use intersect or union of them? Because starBase had been updated to v3.0 with 531 lncRNAs with miRNA interaction.I wonder whether to use my new data.Counld you give some suggestion?
ADVICE: I found an error would appear if some miRNAs in the matrix of users didn't exist in the "pcTarget"/ "lncTarget" or self-defined datasets of users.And I think the next code for mirCorTestFun function would avoid this problems.Your suggestion?
`mirCorTestFun <- function(lncDa,pcDa, mir,mir.expr) { if(mir %in% rownames(mir.expr)){
miRNA in the matrix(your raw codes)
} else {
miRNA not exist,so correlation could not be calculated.
} return (c(reglm, regpm)) ## lnc then pc }`
Look forward to your return.Thank you!