Also, just got an error Error in which(c1$csize) : argument to 'which' is not logical Calls: <Anonymous> ... withCallingHandlers -> withVisible -> eval -> eval -> which Execution halted
On Wed, Feb 4, 2015 at 5:45 PM, Benika H <[email protected]> wrote: > Oh ok. I'm new to this. I will send data. > > hgnc_mapped2.txt is the 1st edgelist (y in my code) > newdata.txt is the 2nd edgelist (z in my code) > > I got an error saying *Warning in layout[, 1] + label.dist * > cos(-label.degree) * (vertex.size +## : longer object length is not a > multiple of shorter object length* > I'm not getting any errors now, but I'm still getting all communities > except thrones I requested. > > > > > > > > > On Wed, Feb 4, 2015 at 5:33 PM, Chris Watson <[email protected]> wrote: > >> We can't reproduce your code because we don't have your data. You also >> don't show any error messages you receive, or how the output/result is >> different than what you expect to see. >> >> On Wed, Feb 4, 2015 at 5:30 PM, Benika H <[email protected]> >> wrote: >> >>> Hi Tamas, Could you help me with my question. >>> >>> I have an edgelist (1st file) which I created the graph object. I want >>> to use walktrap community detection on that network. After getting the >>> communities, I need to plot only the communities with at most 8 vertices >>> and at least 2 vertices (no isolates). Using those communities, I want to >>> join the edgelist from the 2nd file to the matching vertices in a column. >>> Here, I think I can use graph.union. However, I can't seem to get the >>> communities with a sizes 2-8.. >>> >>> >>> >>> My data are in files: >>> hgnc_mapped looks like >>> >>> ABCB7 MARS 0.054839 >>> ABCB7 MAX 0.0638109 >>> ABCB7 MRPS34 0.112394 >>> ABCB7 NDUFA8 0.123633 >>> ABCB7 NUP133 0.0810968 >>> >>> combined looks like >>> >>> hsa-mir-1180 MAPK7 >>> hsa-mir-1228 NACA >>> hsa-mir-1248 IRF9 >>> hsa-mir-1248 PSME2 >>> hsa-mir-1254 KIAA1279 >>> hsa-mir-125b-1PCDHGB3 >>> >>> My code so far is: >>> >>> edgeList <- read.table("hgnc_mapped.txt", header=TRUE, sep="\t") >>> eQTLList <- read.table("combined.txt", header=TRUE, sep="\t") >>> t <- as.data.frame(edgeList) >>> u <- as.data.frame(eQTLList) >>> >>> y <- graph.data.frame(t, directed=FALSE, vertices=NULL) >>> V(y) >>> z <- graph.data.frame(u, directed=TRUE) >>> # new_g <- delete.vertices(y,which(degree(y) < 1) - 1) >>> # V(new_g) >>> ``` >>> >>> ```{r cache=TRUE, dependson='network-data'} >>> #Run the community detection algorithm >>> wc <- walktrap.community(y, weights = edgeList$Weight, steps=6, merges >>> =TRUE, modularity = TRUE, membership = TRUE) >>> ``` >>> >>> c1 <- clusters(y) >>> c1$membership >>> # small.clusters <- which(c1$size > 7) >>> # vertices.to.delete <- which((c1$membership)==small.clusters)-1 >>> # g <- delete.vertices(y, vertices.to.delete) >>> layout <- layout.fruchterman.reingold(y) >>> x <- (which(c1$csize) < 8 & (c1$csize) > 1) >>> vertices <- which(c1$membership==x) >>> g1 <- induced.subgraph(y, vertices) >>> plot(g1,layout=layout[vertices,]) >>> >>> Thanks in advance..... >>> >>> >>>> >>> _______________________________________________ >>> igraph-help mailing list >>> [email protected] >>> https://lists.nongnu.org/mailman/listinfo/igraph-help >>> >>> >> >> _______________________________________________ >> igraph-help mailing list >> [email protected] >> https://lists.nongnu.org/mailman/listinfo/igraph-help >> >> >
_______________________________________________ igraph-help mailing list [email protected] https://lists.nongnu.org/mailman/listinfo/igraph-help
