[R] fast way to compare two matrices of combinations

[Charles C. Berry]

On Thu, 13 Mar 2008, Mark W Kimpel wrote:

> I have a list (length 750), each element containing a vector of unique
> strings (unique gene ids), with length up to ~40 (median 15). I want to
> compile a matrix of all possible triplets and their frequency within
> gene elements. Using combn and a lot of looping, I am accomplishing this
> but it is VERY slow.
>
> I've tried to figure out a way to vectorize this, using "match" and
> "%in%", but can't get my mind around it.
>
> Below is my code. sig.tf.pairs is the list. Suggestions?

First, be sure that your code does what you really intend for it to do.

Does this really do what you wanted?

       if (length(intersect(triplets[,m], all.triplets[,k] == M))){

If so, then why does the first line below never produce an error?

 	 count.vec <- count.vec[,-redundant.vec]

 	is.null(dim(count.vec)) ## TRUE

You are basically tabulating. Use the functions that are built for that.

It looks like what you want is along these lines:

 	tab.combns <- function(x) apply( combn( sort(x), M ),2,
         	                        function(x) paste(x,collapse=''))

 	tab.all <- table( unlist( lapply(sig.tf.pairs,tab.combns) ) )

Chuck
>
> Mark
>
>
> ############################################################
> M <- 3 # 3 for triplets, etc.
> ##########################################################
> # count all triplets
> all.triplets <- NULL
> all.count.vec <- NULL
> for (i in 1:length(sig.tf.pairs)){
>   if (length(sig.tf.pairs[[i]] >= M)){
>     triplets <- combn(sig.tf.pairs[[i]], M, simplify = TRUE)
>     for (j in 1:ncol(triplets)){
>       o <- order(triplets[,j])
>       triplets[,j] <- triplets[o,j]
>       count.vec <- rep(1, ncol(triplets))
>     }
>     if (is.null(all.count.vec)){
>       all.count.vec <- count.vec
>       all.triplets <- triplets
>     } else {
>       redundant.vec <- NULL
>       for (k in 1:ncol(all.triplets)){
>         for (m in 1:ncol(triplets)){
>           if (length(intersect(triplets[,m], all.triplets[,k] == M))){
>             all.count.vec[k] <- all.count.vec[k] + 1
>             redundant.vec <- c(redundant.vec, m)
>           }
>         }
>       }
>       if(!is.null(redundant.vec)){
>         triplets <- triplets[,-redundant.vec]
>         count.vec <- count.vec[,-redundant.vec]
>       }
>       all.triplets <- cbind(all.triplets, triplets)
>       all.count.vec <- c(all.count.vec, count.vec)
>     }
>   }
> }
> ###################################
>
> -- 
>
> Mark W. Kimpel MD  ** Neuroinformatics ** Dept. of Psychiatry
> Indiana University School of Medicine
>
> 15032 Hunter Court, Westfield, IN  46074
>
> (317) 490-5129 Work, & Mobile & VoiceMail
> (317) 204-4202 Home (no voice mail please)
>
> mwkimpel<at>gmail<dot>com
>
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> and provide commented, minimal, self-contained, reproducible code.
>

Charles C. Berry                            (858) 534-2098
                                             Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	            UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901