[BioC] CummeRbund Error

[Valerie Obenchain]

cc'ing Loyal (package maintainer)


John,

Is is possible for you to provide the colon file so we can reproduce the 
error?

It looks like the colon data can be read in successfully but is failing 
when you try to produce the density plot. Is that correct?

this works

     cuff<-readCufflinks()

but this doesn't

     dens<-csDensity(genes(cuff))

If this is the case you can further investigate the cuff object by inspecting the 'genes' object

     samples(genes(cuff))
     features(genes(cuff))

The data that are plotted in cdDensity() are

     fpkmMatrix(genes(cuff))


Valerie





On 01/11/2012 07:33 AM, john herbert wrote:
> Thank you Steve, that is helpful. Based on what I get from traceback
> and the message being "Error: attempt to apply non-function", would I
> be right in thinking the lapply and seq_along being the problem?
>
> I also notice a big difference in size between the cuffData database
> files that cummeRbund makes.
> Colon that does not work = ~3Mb
> Blad that does work = ~115Mb
>
> All other cuffdiff result files are of a similar size between Colon
> and Blad samples.
>
> John.
>
>
>
>> densError: attempt to apply non-function>  traceback()9: FUN(1L[[1L]], ...)8: lapply(seq_along(data), function(i) {       layer<- layers[[i]]       layerd<- data[[i]]       grobs<- matrix(list(), nrow = nrow(layerd), ncol = ncol(layerd))       for (i in seq_len(nrow(layerd))) {           for (j in seq_len(ncol(layerd))) {               scales<- list(x = .$scales$x[[j]]$clone(), y = .$scales$y[[i]]$clone())               details<- coord$compute_ranges(scales)               grobs[[i, j]]<- layer$make_grob(layerd[[i, j]],                    details, coord)           }       }       grobs   })7: get(x, envir = this, inherits = inh)(this, ...)6: facet$make_grobs(data, layers, cs)5: ggplot_build(plot)4: ggplotGrob(x, ...)3: grid.draw(ggplotGrob(x, ...))2: print.ggplot(list(data = list(gene_id = character(0), sample_name = integer(0),        fpkm = numeric(0), conf_hi = numeric(0), conf_lo = numeric(0),        quant_status = character(0)), layers = list(<environment>),        scales =<environment>, mapping = list(), options = list(           title = "genes", labels = list(x = "log10(fpkm)", group = "sample_name",                colour = "sample_name", fill = "sample_name", y = "density")),        coordinates =<environment>, facet =<environment>, plot_env =<environment>))1: print(list(data = list(gene_id = character(0), sample_name = integer(0),        fpkm = numeric(0), conf_hi = numeric(0), conf_lo = numeric(0),        quant_status = character(0)), layers = list(<environment>),        scales =<environment>, mapping = list(), options = list(           title = "genes", labels = list(x = "log10(fpkm)", group = "sample_name",                colour = "sample_name", fill = "sample_name", y = "density")),        coordinates =<environment>, facet =<environment>, plot_env =<environment>))
> On Wed, Jan 11, 2012 at 2:56 PM, Steve Lianoglou
> <mailinglist.honeypot at gmail.com>  wrote:
>> Hi,
>>
>> On Wed, Jan 11, 2012 at 9:28 AM, john herbert<arraystruggles at gmail.com>  wrote:
>>> Hi,
>>> I have downloaded/installed cummeRbund vis biocLite and have run it on
>>> 2 sets of samples.
>>>
>>> I have 2 sets of cuffdiff 1.3.0 results and they both load fine into
>>> cummeRbund as follows.
>>>
>>> library(cummeRbund)
>>>
>>> setwd("C:/Users/mark/Documents/Cross/cufflinks_data/diff_blad_1_3_0/diff_blad_1_3_0")
>>>
>>> cuff<-readCufflinks()
>>>
>>> dens<-csDensity(genes(cuff))
>>> dens
>>>
>>> # This works fine and displays a density plot. But, if I run all this
>>> again on a different set of samples, I get this.
>>>
>>> library(cummeRbund)
>>> setwd("C:/Users/mark/Documents/Cross/cufflinks_data/diff_colon_1_3_0/diff_colon_1_3_0")
>>> cuff<-readCufflinks()
>>> dens<-csDensity(genes(cuff))
>>> dens
>>>
>>> Error: attempt to apply non-function
>>>
>>> Any ideas how I can fix this; looks like there is a difference in
>>> results somewhere but all files present in both sets of data.
>> I "like" to peruse the source code of the packages I'm using to see
>> what's cooking under the hood (you can download the source package
>> from the package site at bioconductor.org).
>>
>> To get a better idea of where to start digging in the source, call
>> "traceback()" in your R workspace after the error occurs. R will print
>> a stack trace that shows you the series of function calls that landed
>> you in the fix you're in now. The stack trace will act as a trail of
>> breadcrumbs you can use to follow the execution path of your code in
>> hopes of finding which expectations aren't met in your program that
>> causes the error.
>>
>> HTH,
>> -steve
>>
>> --
>> Steve Lianoglou
>> Graduate Student: Computational Systems Biology
>>   | Memorial Sloan-Kettering Cancer Center
>>   | Weill Medical College of Cornell University
>> Contact Info: http://cbio.mskcc.org/~lianos/contact
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at r-project.org
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor