spearman correlation and p-value as a matrix

2 messages · Ozgul Inceoglu, arun

Original

Thu, Feb 14, 2013 7:22 AM #

you are right! I was so happy to find out the p-value criteria, I totally forgot about the spearman correlation, no I dont think there is an option of spearman correlation. Thank you for pointing that out!

Cheers,

?

Dear Ozgul,

I made a comment in the previous email, which I didn't check it.
Thank you for the ?cor2m().
I checked the results of the example dataset with cor2m().? Does it have an option for spearman correlation?? 

The values below seem to be pearson
#cor2m
?cor2m(bg,ag,trim=TRUE,alpha=0.05) ######I
????? Otu00022 Otu00029?? Otu00039 Otu00042? Otu00101 Otu00105 Otu00125
ag1? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
ag2? 0.0000000????? NaN? 0.0000000????? NaN 0.7743597????? NaN????? NaN
ag3 -0.8901029????? NaN -0.8901029????? NaN 0.0000000????? NaN????? NaN
ag4? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
ag5? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
??? Otu00131?? Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185?? Otu00190
ag1????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
ag2????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
ag3????? NaN -0.8901029????? NaN????? NaN????? NaN????? NaN????? NaN -0.8901029
ag4????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
ag5????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
??? Otu00209?? Otu00218
ag1????? NaN? 0.0000000
ag2????? NaN? 0.0000000
ag3????? NaN -0.8901029
ag4????? NaN? 0.0000000
ag5????? NaN? 0.0000000

#Pearson correlation from my solution:
resr<-do.call(rbind,lapply(split(bg_ag,1:nrow(bg_ag)),function(x)
{res<-rcorr(cbind(bg[,x[,1]],ag[,x[,2]]))$r; row.names(res)<- 
rep(paste(x[1],x[2],sep="_"),2);res})) 
?indx<-row(resr)%%2!=1
resrnew<-as.matrix(resr[indx[,1],1]) 
resrnew1<-data.frame(read.table(text=row.names(resrnew),sep="_",stringsAsFactors=FALSE),value=resrnew)
?row.names(resrnew1)<-1:nrow(resrnew1)
library(reshape2)
?dcast(resrnew1,V2~V1,value.var="value")?? V2??? Otu00022 Otu00029??? Otu00039 Otu00042?? Otu00101 Otu00105 Otu00125
#1 ag1 -0.12705141????? NaN -0.12705141????? NaN -0.6394308????? NaN????? NaN
#2 ag2 -0.61522514????? NaN -0.61522514????? NaN? 0.7743597????? NaN????? NaN
#3 ag3 -0.89010286????? NaN -0.89010286????? NaN -0.2655363????? NaN????? NaN
#4 ag4? 0.03036290????? NaN? 0.03036290????? NaN -0.5638320????? NaN????? NaN
#5 ag5? 0.08266317????? NaN? 0.08266317????? NaN -0.2582930????? NaN????? NaN
?# Otu00131??? Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185??? Otu00190
#1????? NaN -0.12705141????? NaN????? NaN????? NaN????? NaN????? NaN -0.12705141
#2????? NaN -0.61522514????? NaN????? NaN????? NaN????? NaN????? NaN -0.61522514
#3????? NaN -0.89010286????? NaN????? NaN????? NaN????? NaN????? NaN -0.89010286
#4????? NaN? 0.03036290????? NaN????? NaN????? NaN????? NaN????? NaN? 0.03036290
#5????? NaN? 0.08266317????? NaN????? NaN????? NaN????? NaN????? NaN? 0.08266317
?# Otu00209??? Otu00218
#1????? NaN -0.12705141
#2????? NaN -0.61522514
#3????? NaN -0.89010286
#4????? NaN? 0.03036290
#5????? NaN? 0.08266317

A.K.



----- Original Message -----
From: Ozgul Inceoglu <Ozgul.Inceoglu at ulb.ac.be>
To: R help <r-help at r-project.org>
Cc: 
Sent: Thursday, February 14, 2013 1:10 AM
Subject: Re: [R] spearman correlation and p-value as a matrix

Thank you all for the answers. I really need to learn a lot. 
Bu I also discover cor2m(x, y, trim = TRUE, alpha = 0.05)
in ecodist package, which gives an output file with significant correlations.

?zg?l

Yj>HI,

#ag data was created
bg<- as.matrix(read.table(text=" 
???? Otu00022 Otu00029 Otu00039 Otu00042 Otu00101 Otu00105 Otu00125 Otu00131 Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185 Otu00190 Otu00209 Otu00218 
Gi20Jun11? 0.001217??????? 0 0.001217??????? 0 0.000000??????? 0??????? 0??????? 0 0.001217??????? 0??????? 0??????? 0??????? 0??????? 0 0.001217??????? 0 0.001217 
Gi40Jun11? 0.000000??????? 0 0.000000??????? 0 0.000000??????? 0??????? 0??????? 0 0.000000??????? 0??????? 0??????? 0??????? 0??????? 0 0.000000??????? 0 0.000000 
Gi425Jun11 0.000000??????? 0 0.000000??????? 0 0.000000??????? 0??????? 0??????? 0 0.000000??????? 0??????? 0??????? 0??????? 0??????? 0 0.000000??????? 0 0.000000 
Gi45Jun11? 0.000000??????? 0 0.000000??????? 0 0.001513??????? 0??????? 0??????? 0 0.000000??????? 0??????? 0??????? 0??????? 0??????? 0 0.000000??????? 0 0.000000 
Gi475Jun11 0.000000??????? 0 0.000000??????? 0 0.000000??????? 0??????? 0??????? 0 0.000000??????? 0??????? 0??????? 0??????? 0??????? 0 0.000000??????? 0 0.000000 
Gi50Jun11? 0.000000??????? 0 0.000000??????? 0 0.000000??????? 0??????? 0??????? 0 0.000000??????? 0??????? 0??????? 0??????? 0??????? 0 0.000000??????? 0 0.000000 
",sep="",header=TRUE,stringsAsFactors=F))
set.seed(128)
ag<- matrix(rnorm(30),nrow=6)
colnames(ag)<- paste("ag",1:5,sep="")
bg_ag<-expand.grid(colnames(bg),colnames(ag),stringsAsFactors=FALSE)
?attr(bg_ag,"out.attrs")<- NULL
?library(Hmisc)
#correlation
resr<-do.call(rbind,lapply(split(bg_ag,1:nrow(bg_ag)),function(x) {res<-rcorr(cbind(bg[,x[,1]],ag[,x[,2]]),type="spearman")$r; row.names(res)<- rep(paste(x[1],x[2],sep="_"),2);res}))
?head(resr)
#???????????????? [,1]????? [,2]
#Otu00022_ag1 1.0000000 0.1309307
#Otu00022_ag1 0.1309307 1.0000000
#Otu00029_ag1 1.0000000?????? NaN
#Otu00029_ag1?????? NaN 1.0000000
#Otu00039_ag1 1.0000000 0.1309307
#Otu00039_ag1 0.1309307 1.0000000

#p-values
resP<-do.call(rbind,lapply(split(bg_ag,1:nrow(bg_ag)),function(x) {res<-rcorr(cbind(bg[,x[,1]],ag[,x[,2]]),type="spearman")$P; row.names(res)<- rep(paste(x[1],x[2],sep="_"),2);res}))
? head(resP)
#????????????????? [,1]????? [,2]
#Otu00022_ag1??????? NA 0.8047262
#Otu00022_ag1 0.8047262??????? NA
#Otu00029_ag1??????? NA?????? NaN
#Otu00029_ag1?????? NaN??????? NA
#Otu00039_ag1??????? NA 0.8047262
#Otu00039_ag1 0.8047262??????? NA

#If you need only the values
indx<-row(resr)%%2!=1
?resPnew<-as.matrix(resP[indx[,1],1])
?resrnew<-as.matrix(resr[indx[,1],1])

head(resPnew)
#????????????????? [,1]
#Otu00022_ag1 0.8047262
#Otu00029_ag1?????? NaN
#Otu00039_ag1 0.8047262
#Otu00042_ag1?????? NaN
#Otu00101_ag1 0.1583024
#Otu00105_ag1?????? NaN

head(resrnew)
#?????????????????? [,1]
#Otu00022_ag1? 0.1309307
#Otu00029_ag1??????? NaN
#Otu00039_ag1? 0.1309307
#Otu00042_ag1??????? NaN
#Otu00101_ag1 -0.6546537
#Otu00105_ag1??????? NaN

A.K.




----- Original Message -----
From: Ozgul Inceoglu <Ozgul.Inceoglu at ulb.ac.be>
To: r-help at r-project.org
Cc: 
Sent: Wednesday, February 13, 2013 4:48 AM
Subject: [R] spearman correlation and p-value as a matrix

I have two data matrices that I want to make the correlation between each column from data1 and each column from data 2 and also calculate the p-value Matrices dont have the same size and I tried such a script.

bg <- read.table (file.choose(), header=T, row.names) 
bg 
Otu00022 Otu00029 Otu00039 Otu00042 Otu00101 Otu00105 Otu00125 Otu00131 Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185 Otu00190 Otu00209 Otu00218 
Gi20Jun11 0.001217 0 0.001217 0 0.000000 0 0 0 0.001217 0 0 0 0 0 0.001217 0 0.001217 
Gi40Jun11 0.000000 0 0.000000 0 0.000000 0 0 0 0.000000 0 0 0 0 0 0.000000 0 0.000000 
Gi425Jun11 0.000000 0 0.000000 0 0.000000 0 0 0 0.000000 0 0 0 0 0 0.000000 0 0.000000 
Gi45Jun11 0.000000 0 0.000000 0 0.001513 0 0 0 0.000000 0 0 0 0 0 0.000000 0 0.000000 
Gi475Jun11 0.000000 0 0.000000 0 0.000000 0 0 0 0.000000 0 0 0 0 0 0.000000 0 0.000000 
Gi50Jun11 0.000000 0 0.000000 0 0.000000 0 0 0 0.000000 0 0 0 0 0 0.000000 0 0.000000

ag <- read.table (file.choose(), header=T, row.names) 

for (i in 1:(ncol(bg))) 
for (j in 1:(ncol(ag))) 
print(c(i,j))
final_matrix <- matrix(rep("0",ncol(bg)*ncol(ag)),ncol=ncol(bg),nrow=ncol(ag))

cor <- cor.test(as.vector(as.matrix(bg[,i])),as.vector(as.matrix(ag[,j])), method="spearman")

#but the output is not matrice with all the values but a single correlation value

data:? bg[, i] and ag[, j] 
t = 2.2992, df = 26, p-value = 0.02978
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
0.04485289 0.67986803 
sample estimates:
? ? ? cor 
0.4110515 

# How I can creat an outfile with all the correlations and p-values?

Thank you very much!
?zg?l

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

?zg?l Inceoglu, PhD.

Universit? Libre de Bruxelles
Ecology of Aquatic Systems 
Campus de la plaine CP221  
Boulevard du triomphe  
1050 Bruxelles Belgium

arun

Thu, Feb 14, 2013 7:50 AM #

Hi Ozgul,

Try this:
#Here I used the "pearson correlation" as `spearman` was not significant

resr<-do.call(rbind,lapply(split(bg_ag,1:nrow(bg_ag)),function(x) {res<-rcorr(cbind(bg[,x[,1]],ag[,x[,2]]),type="pearson")$r; row.names(res)<- rep(paste(x[1],x[2],sep="_"),2);res})) 
#p-values 
resP<-do.call(rbind,lapply(split(bg_ag,1:nrow(bg_ag)),function(x) {res<-rcorr(cbind(bg[,x[,1]],ag[,x[,2]]),type="pearson")$P; row.names(res)<- rep(paste(x[1],x[2],sep="_"),2);res}))
indx<-row(resr)%%2!=1 
?resPnew<-as.matrix(resP[indx[,1],1]) 
?resrnew<-as.matrix(resr[indx[,1],1])
resrnew1<-data.frame(read.table(text=row.names(resrnew),sep="_",stringsAsFactors=FALSE),value=resrnew)
?row.names(resrnew1)<-1:nrow(resrnew1)
library(reshape2)
resrnew2<- dcast(resrnew1,V2~V1,value.var="value") 

resPnew1<-data.frame(read.table(text=row.names(resPnew),sep="_",stringsAsFactors=FALSE),value=resPnew)
row.names(resPnew1)<-1:nrow(resPnew1)
resPnew2<-dcast(resPnew1,V2~V1,value.var="value") 

resrnew2[,-1][resPnew2[,-1]>0.10|is.na(resPnew2[,-1])]<- 0? #also I used the cut-off limit as 0.10 because:
#correlation value for a p-value of 0.07 was also included in the ?cor2m() result

resPnew2
?#? V2?? Otu00022 Otu00029?? Otu00039 Otu00042?? Otu00101 Otu00105 Otu00125
#1 ag1 0.81044832????? NaN 0.81044832????? NaN 0.17157638????? NaN????? NaN
#2 ag2 0.19359426????? NaN 0.19359426????? NaN 0.07062624 ??? NaN????? NaN
#3 ag3 0.01745244????? NaN 0.01745244????? NaN 0.61105696????? NaN????? NaN
#4 ag4 0.95446965????? NaN 0.95446965????? NaN 0.24387489????? NaN????? NaN
#5 ag5 0.87628767????? NaN 0.87628767????? NaN 0.62117658????? NaN????? NaN
?# Otu00131?? Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185?? Otu00190
#1????? NaN 0.81044832????? NaN????? NaN????? NaN????? NaN????? NaN 0.81044832
#2????? NaN 0.19359426????? NaN????? NaN????? NaN????? NaN????? NaN 0.19359426
#3????? NaN 0.01745244????? NaN????? NaN????? NaN????? NaN????? NaN 0.01745244
#4????? NaN 0.95446965????? NaN????? NaN????? NaN????? NaN????? NaN 0.95446965
#5????? NaN 0.87628767????? NaN????? NaN????? NaN????? NaN????? NaN 0.87628767
?# Otu00209?? Otu00218
#1????? NaN 0.81044832
#2????? NaN 0.19359426
#3????? NaN 0.01745244
#4????? NaN 0.95446965
#5????? NaN 0.87628767


cor2m(bg,ag,trim=TRUE,alpha=0.05)
#????? Otu00022 Otu00029?? Otu00039 Otu00042? Otu00101 Otu00105 Otu00125
#ag1? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
#ag2? 0.0000000????? NaN? 0.0000000????? NaN 0.7743597????? NaN????? NaN
#ag3 -0.8901029????? NaN -0.8901029????? NaN 0.0000000????? NaN????? NaN
#ag4? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
#ag5? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
?# ? Otu00131?? Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185?? Otu00190
#ag1????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
#ag2????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
#ag3????? NaN -0.8901029????? NaN????? NaN????? NaN????? NaN????? NaN -0.8901029
#ag4????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
#ag5????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
?# ? Otu00209?? Otu00218
#ag1????? NaN? 0.0000000
#ag2????? NaN? 0.0000000
#ag3????? NaN -0.8901029
#ag4????? NaN? 0.0000000
#ag5????? NaN? 0.0000000


resrnew2
#?? V2?? Otu00022 Otu00029?? Otu00039 Otu00042? Otu00101 Otu00105 Otu00125
#1 ag1? 0.0000000??????? 0? 0.0000000??????? 0 0.0000000??????? 0??????? 0
#2 ag2? 0.0000000??????? 0? 0.0000000??????? 0 0.7743597??????? 0??????? 0
#3 ag3 -0.8901029??????? 0 -0.8901029??????? 0 0.0000000??????? 0??????? 0
#4 ag4? 0.0000000??????? 0? 0.0000000??????? 0 0.0000000??????? 0??????? 0
#5 ag5? 0.0000000??????? 0? 0.0000000??????? 0 0.0000000??????? 0??????? 0
?# Otu00131?? Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185?? Otu00190
#1??????? 0? 0.0000000??????? 0??????? 0??????? 0??????? 0??????? 0? 0.0000000
#2??????? 0? 0.0000000??????? 0??????? 0??????? 0??????? 0??????? 0? 0.0000000
#3??????? 0 -0.8901029??????? 0??????? 0??????? 0??????? 0??????? 0 -0.8901029
#4??????? 0? 0.0000000??????? 0??????? 0??????? 0??????? 0??????? 0? 0.0000000
#5??????? 0? 0.0000000??????? 0??????? 0??????? 0??????? 0??????? 0? 0.0000000
#? Otu00209?? Otu00218
#1??????? 0? 0.0000000
#2??????? 0? 0.0000000
#3??????? 0 -0.8901029
#4??????? 0? 0.0000000
#5??????? 0? 0.0000000
#If you want the Na values to remain as such use:
resrnew2[,-1][resPnew2[,-1]>0.10]<- 0 

?resrnew2
#?? V2?? Otu00022 Otu00029?? Otu00039 Otu00042? Otu00101 Otu00105 Otu00125
#1 ag1? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
#2 ag2? 0.0000000????? NaN? 0.0000000????? NaN 0.7743597????? NaN????? NaN
#3 ag3 -0.8901029????? NaN -0.8901029????? NaN 0.0000000????? NaN????? NaN
#4 ag4? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
#5 ag5? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
?# Otu00131?? Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185?? Otu00190
#1????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
#2????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
#3????? NaN -0.8901029????? NaN????? NaN????? NaN????? NaN????? NaN -0.8901029
#4????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
#5????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
?# Otu00209?? Otu00218
#1????? NaN? 0.0000000
#2????? NaN? 0.0000000
#3????? NaN -0.8901029
#4????? NaN? 0.0000000
#5????? NaN? 0.0000000


Hope it helps.
A.K.

----- Original Message -----
From: Ozgul Inceoglu <Ozgul.Inceoglu at ulb.ac.be>
To: arun <smartpink111 at yahoo.com>
Cc: R help <r-help at r-project.org>
Sent: Thursday, February 14, 2013 10:22 AM
Subject: re:Re: [R] spearman correlation and p-value as a matrix

you are right! I was so happy to find out the p-value criteria, I totally forgot about the spearman correlation, no I dont think there is an option of spearman correlation. Thank you for pointing that out!

Cheers,

?

Dear Ozgul,

I made a comment in the previous email, which I didn't check it.
Thank you for the ?cor2m().
I checked the results of the example dataset with cor2m().? Does it have an option for spearman correlation?? 

The values below seem to be pearson
#cor2m
?cor2m(bg,ag,trim=TRUE,alpha=0.05) ######I
????? Otu00022 Otu00029?? Otu00039 Otu00042? Otu00101 Otu00105 Otu00125
ag1? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
ag2? 0.0000000????? NaN? 0.0000000????? NaN 0.7743597????? NaN????? NaN
ag3 -0.8901029????? NaN -0.8901029????? NaN 0.0000000????? NaN????? NaN
ag4? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
ag5? 0.0000000????? NaN? 0.0000000????? NaN 0.0000000????? NaN????? NaN
??? Otu00131?? Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185?? Otu00190
ag1????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
ag2????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
ag3????? NaN -0.8901029????? NaN????? NaN????? NaN????? NaN????? NaN -0.8901029
ag4????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
ag5????? NaN? 0.0000000????? NaN????? NaN????? NaN????? NaN????? NaN? 0.0000000
??? Otu00209?? Otu00218
ag1????? NaN? 0.0000000
ag2????? NaN? 0.0000000
ag3????? NaN -0.8901029
ag4????? NaN? 0.0000000
ag5????? NaN? 0.0000000

#Pearson correlation from my solution:
resr<-do.call(rbind,lapply(split(bg_ag,1:nrow(bg_ag)),function(x)
{res<-rcorr(cbind(bg[,x[,1]],ag[,x[,2]]))$r; row.names(res)<- 
rep(paste(x[1],x[2],sep="_"),2);res})) 
?indx<-row(resr)%%2!=1
resrnew<-as.matrix(resr[indx[,1],1]) 
resrnew1<-data.frame(read.table(text=row.names(resrnew),sep="_",stringsAsFactors=FALSE),value=resrnew)
?row.names(resrnew1)<-1:nrow(resrnew1)
library(reshape2)
?dcast(resrnew1,V2~V1,value.var="value")?? V2??? Otu00022 Otu00029??? Otu00039 Otu00042?? Otu00101 Otu00105 Otu00125
#1 ag1 -0.12705141????? NaN -0.12705141????? NaN -0.6394308????? NaN????? NaN
#2 ag2 -0.61522514????? NaN -0.61522514????? NaN? 0.7743597????? NaN????? NaN
#3 ag3 -0.89010286????? NaN -0.89010286????? NaN -0.2655363????? NaN????? NaN
#4 ag4? 0.03036290????? NaN? 0.03036290????? NaN -0.5638320????? NaN????? NaN
#5 ag5? 0.08266317????? NaN? 0.08266317????? NaN -0.2582930????? NaN????? NaN
?# Otu00131??? Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185??? Otu00190
#1????? NaN -0.12705141????? NaN????? NaN????? NaN????? NaN????? NaN -0.12705141
#2????? NaN -0.61522514????? NaN????? NaN????? NaN????? NaN????? NaN -0.61522514
#3????? NaN -0.89010286????? NaN????? NaN????? NaN????? NaN????? NaN -0.89010286
#4????? NaN? 0.03036290????? NaN????? NaN????? NaN????? NaN????? NaN? 0.03036290
#5????? NaN? 0.08266317????? NaN????? NaN????? NaN????? NaN????? NaN? 0.08266317
?# Otu00209??? Otu00218
#1????? NaN -0.12705141
#2????? NaN -0.61522514
#3????? NaN -0.89010286
#4????? NaN? 0.03036290
#5????? NaN? 0.08266317

A.K.



----- Original Message -----
From: Ozgul Inceoglu <Ozgul.Inceoglu at ulb.ac.be>
To: R help <r-help at r-project.org>
Cc: 
Sent: Thursday, February 14, 2013 1:10 AM
Subject: Re: [R] spearman correlation and p-value as a matrix

Thank you all for the answers. I really need to learn a lot. 
Bu I also discover cor2m(x, y, trim = TRUE, alpha = 0.05)
in ecodist package, which gives an output file with significant correlations.

?zg?l

Yj>HI,

#ag data was created
bg<- as.matrix(read.table(text=" 
???? Otu00022 Otu00029 Otu00039 Otu00042 Otu00101 Otu00105 Otu00125 Otu00131 Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185 Otu00190 Otu00209 Otu00218 
Gi20Jun11? 0.001217??????? 0 0.001217??????? 0 0.000000??????? 0??????? 0??????? 0 0.001217??????? 0??????? 0??????? 0??????? 0??????? 0 0.001217??????? 0 0.001217 
Gi40Jun11? 0.000000??????? 0 0.000000??????? 0 0.000000??????? 0??????? 0??????? 0 0.000000??????? 0??????? 0??????? 0??????? 0??????? 0 0.000000??????? 0 0.000000 
Gi425Jun11 0.000000??????? 0 0.000000??????? 0 0.000000??????? 0??????? 0??????? 0 0.000000??????? 0??????? 0??????? 0??????? 0??????? 0 0.000000??????? 0 0.000000 
Gi45Jun11? 0.000000??????? 0 0.000000??????? 0 0.001513??????? 0??????? 0??????? 0 0.000000??????? 0??????? 0??????? 0??????? 0??????? 0 0.000000??????? 0 0.000000 
Gi475Jun11 0.000000??????? 0 0.000000??????? 0 0.000000??????? 0??????? 0??????? 0 0.000000??????? 0??????? 0??????? 0??????? 0??????? 0 0.000000??????? 0 0.000000 
Gi50Jun11? 0.000000??????? 0 0.000000??????? 0 0.000000??????? 0??????? 0??????? 0 0.000000??????? 0??????? 0??????? 0??????? 0??????? 0 0.000000??????? 0 0.000000 
",sep="",header=TRUE,stringsAsFactors=F))
set.seed(128)
ag<- matrix(rnorm(30),nrow=6)
colnames(ag)<- paste("ag",1:5,sep="")
bg_ag<-expand.grid(colnames(bg),colnames(ag),stringsAsFactors=FALSE)
?attr(bg_ag,"out.attrs")<- NULL
?library(Hmisc)
#correlation
resr<-do.call(rbind,lapply(split(bg_ag,1:nrow(bg_ag)),function(x) {res<-rcorr(cbind(bg[,x[,1]],ag[,x[,2]]),type="spearman")$r; row.names(res)<- rep(paste(x[1],x[2],sep="_"),2);res}))
?head(resr)
#???????????????? [,1]????? [,2]
#Otu00022_ag1 1.0000000 0.1309307
#Otu00022_ag1 0.1309307 1.0000000
#Otu00029_ag1 1.0000000?????? NaN
#Otu00029_ag1?????? NaN 1.0000000
#Otu00039_ag1 1.0000000 0.1309307
#Otu00039_ag1 0.1309307 1.0000000

#p-values
resP<-do.call(rbind,lapply(split(bg_ag,1:nrow(bg_ag)),function(x) {res<-rcorr(cbind(bg[,x[,1]],ag[,x[,2]]),type="spearman")$P; row.names(res)<- rep(paste(x[1],x[2],sep="_"),2);res}))
? head(resP)
#????????????????? [,1]????? [,2]
#Otu00022_ag1??????? NA 0.8047262
#Otu00022_ag1 0.8047262??????? NA
#Otu00029_ag1??????? NA?????? NaN
#Otu00029_ag1?????? NaN??????? NA
#Otu00039_ag1??????? NA 0.8047262
#Otu00039_ag1 0.8047262??????? NA

#If you need only the values
indx<-row(resr)%%2!=1
?resPnew<-as.matrix(resP[indx[,1],1])
?resrnew<-as.matrix(resr[indx[,1],1])

head(resPnew)
#????????????????? [,1]
#Otu00022_ag1 0.8047262
#Otu00029_ag1?????? NaN
#Otu00039_ag1 0.8047262
#Otu00042_ag1?????? NaN
#Otu00101_ag1 0.1583024
#Otu00105_ag1?????? NaN

head(resrnew)
#?????????????????? [,1]
#Otu00022_ag1? 0.1309307
#Otu00029_ag1??????? NaN
#Otu00039_ag1? 0.1309307
#Otu00042_ag1??????? NaN
#Otu00101_ag1 -0.6546537
#Otu00105_ag1??????? NaN

A.K.




----- Original Message -----
From: Ozgul Inceoglu <Ozgul.Inceoglu at ulb.ac.be>
To: r-help at r-project.org
Cc: 
Sent: Wednesday, February 13, 2013 4:48 AM
Subject: [R] spearman correlation and p-value as a matrix

I have two data matrices that I want to make the correlation between each column from data1 and each column from data 2 and also calculate the p-value Matrices dont have the same size and I tried such a script.

bg <- read.table (file.choose(), header=T, row.names) 
bg 
Otu00022 Otu00029 Otu00039 Otu00042 Otu00101 Otu00105 Otu00125 Otu00131 Otu00137 Otu00155 Otu00158 Otu00172 Otu00181 Otu00185 Otu00190 Otu00209 Otu00218 
Gi20Jun11 0.001217 0 0.001217 0 0.000000 0 0 0 0.001217 0 0 0 0 0 0.001217 0 0.001217 
Gi40Jun11 0.000000 0 0.000000 0 0.000000 0 0 0 0.000000 0 0 0 0 0 0.000000 0 0.000000 
Gi425Jun11 0.000000 0 0.000000 0 0.000000 0 0 0 0.000000 0 0 0 0 0 0.000000 0 0.000000 
Gi45Jun11 0.000000 0 0.000000 0 0.001513 0 0 0 0.000000 0 0 0 0 0 0.000000 0 0.000000 
Gi475Jun11 0.000000 0 0.000000 0 0.000000 0 0 0 0.000000 0 0 0 0 0 0.000000 0 0.000000 
Gi50Jun11 0.000000 0 0.000000 0 0.000000 0 0 0 0.000000 0 0 0 0 0 0.000000 0 0.000000

ag <- read.table (file.choose(), header=T, row.names) 

for (i in 1:(ncol(bg))) 
for (j in 1:(ncol(ag))) 
print(c(i,j))
final_matrix <- matrix(rep("0",ncol(bg)*ncol(ag)),ncol=ncol(bg),nrow=ncol(ag))

cor <- cor.test(as.vector(as.matrix(bg[,i])),as.vector(as.matrix(ag[,j])), method="spearman")

#but the output is not matrice with all the values but a single correlation value

data:? bg[, i] and ag[, j] 
t = 2.2992, df = 26, p-value = 0.02978
alternative hypothesis: true correlation is not equal to 0 
95 percent confidence interval:
0.04485289 0.67986803 
sample estimates:
? ? ? cor 
0.4110515 

# How I can creat an outfile with all the correlations and p-values?

Thank you very much!
?zg?l

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

______________________________________________
R-help at r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.

?zg?l Inceoglu, PhD.

Universit? Libre de Bruxelles
Ecology of Aquatic Systems 
Campus de la plaine CP221? 
Boulevard du triomphe? 
1050 Bruxelles Belgium?