Hi R users,

I generated a square correlation matrix for the dat dataframe below;
dat<-data.frame(g1=c(1,0,0,1,1,1,0,0,0),
                g2=c(0,1,0,1,0,1,1,0,0),
                g3=c(1,1,0,0,0,1,0,0,0),
                g4=c(0,1,0,1,1,1,1,1,0))
library("Hmisc")
dat.rcorr = rcorr(as.matrix(dat))
dat.r <-round(dat.rcorr$r,2)

however, I want to modify this correlation calculation;
my dat has more than 1000 rows and 22 columns;
in each column, less than 10% values are 1, most of them are 0;
so I want to remove a  row with value of zero in both columns when calculate 
correlation between two columns.
I just want to check whether those values of 1 are correlated between two 
columns.
Please look at my code in the following;

cor.4gene <-matrix(0,nrow=4*4, ncol=4)
for (i in 1:4){
  #i=1
  for (j in 1:4) {
    #j=1
    d <-dat[,c(i,j)]%>%
      filter(eval(as.symbol(colnames(dat)[i]))!=0 |
               eval(as.symbol(colnames(dat)[j]))!=0)
    c <-cor.test(d[,1],d[,2])
    cor.4gene[i*j,]<-c(colnames(dat)[i],colnames(dat)[j],
                        c$estimate,c$p.value)
  }
}
cor.4gene<-as.data.frame(cor.4gene)%>%filter(V1 !=0)
colnames(cor.4gene)<-c("gene1","gene2","cor","P")

Can you tell me what mistakes I made?
first, why cor is NA when calculation of correlation for g1 and g1, I though it 
should be 1.

cor.4gene$cor[is.na(cor.4gene$cor)]<-1
cor.4gene$cor[is.na(cor.4gene$P)]<-0
cor.4gene.sq <-pivot_wider(cor.4gene, names_from = gene1, values_from = cor)

Then this line of code above did not generate a square matrix as what the HMisc 
library did.
How to fix my code?

Thank you,

Ding


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