I think you're better off using the NEL (Nodes Edge List) graph
representation. See the documentation in the graph package.

Michael

On Thu, Apr 26, 2012 at 2:52 PM, Abhishek Pratap <apratap@lbl.gov> wrote:

> Forgot to copy everyone on my last email and also just for completeness I
> do think that the previous error is likely due to the memory. So reading
> some more about the memory limits in  ?"Memory-limits" I am wondering if
> any tweaks can be made for me to create a big adjacency matrix.
>
> -A
>
>
> On Thu, Apr 26, 2012 at 2:24 PM, Abhishek Pratap <apratap@lbl.gov> wrote:
>
>> Hi Michael
>>
>> I finally got thru this and got expected results on the test data set.
>>
>> On full data till the intersect step it runs well but when I am trying to
>> create an adjacency matrix in order to create a graph I am getting an error
>> by the matrix creation object.
>>
>> Error in matrix(0, queryLength(good_hits), subjectLength(good_hits)) :
>>   too many elements specified
>>
>> queryLength(good_hits) = 900,000
>>
>> I am wondering if there is an efficient way to construct a graph to find
>> the connected components for a large set of points.
>>
>>
>>
>> Thanks!
>> -Abhi
>>
>>
>>
>> On Wed, Apr 25, 2012 at 4:14 PM, Michael Lawrence <
>> lawrence.michael@gene.com> wrote:
>>
>>> Making an adjacency matrix from a Hits object would be something like:
>>>
>>> am <- matrix(0, queryLength(hits), subjectLength(hits))
>>> am[as.matrix(hits)] <- 1
>>>
>>> Michael
>>>
>>>
>>> On Wed, Apr 25, 2012 at 3:40 PM, Abhishek Pratap <apratap@lbl.gov>wrote:
>>>
>>>> Thanks Steve. Legit solution and it works for me too. Based on my
>>>> partial understanding of methods I have no idea how this will scale for a
>>>> million points,I have in the actual data(may be it will) but I will let you
>>>> know.
>>>>
>>>> @Michael : I updated my installation and I am able to run the intersect
>>>> step on the findOverlaps() output from start and end.
>>>> I guess now I need to convert the common hits to a graph object and
>>>> call connComp on it. Any way I could convert hits matrix to a adjacency
>>>> matrix to create a graph or maybe there is another slick way to find the
>>>> connected points.
>>>>
>>>> ir <- IRanges(c(10,10,11,9,10,11), width=c(190,190,190,190,180,180))
>>>> start  <- flank(ir,1,both=TRUE)
>>>> end <- flank(ir,1,start=FALSE,both=TRUE)
>>>> start_overlaps <- findOverlaps(start)
>>>> end_overlaps <- findOverlaps(end)
>>>> good_hits <- intersect(start_overlaps,end_overlaps)
>>>>
>>>>
>>>> Thanks!
>>>> -Abhi
>>>>
>>>>
>>>> On Wed, Apr 25, 2012 at 3:08 PM, Steve Lianoglou <
>>>> mailinglist.honeypot@gmail.com> wrote:
>>>>
>>>>> Hi,
>>>>>
>>>>> On Wed, Apr 25, 2012 at 5:21 PM, Abhishek Pratap <apratap@lbl.gov>
>>>>> wrote:
>>>>> > Hi Michael
>>>>> >
>>>>> > SessionInfo copied below. My versions could be one older to current
>>>>> one.  I
>>>>> > am still wondering how I can get this information in a format that
>>>>> can be
>>>>> > digested by connectedComp or something similar. I think we are close
>>>>> to a
>>>>> > solution.
>>>>>
>>>>> Step 1: Upgrade R ;-)
>>>>>
>>>>> It's not necessary for the approach I'm going to suggest, but it'll
>>>>> probably make it easier for Michael to help you w/ his solution, which
>>>>> is probably going to be more robust than the
>>>>> duct-tape-and-elmer's-glue snippet I'm going to try:
>>>>>
>>>>> R> library(GenomicRanges)
>>>>> R> ir <- IRanges(c(10,10,11,9,10,11), width=c(190,190,190,190,180,180))
>>>>> R> starts <- reduce(resize(ir, width=1, fix='start'), min.gapwidth=2)
>>>>> R> ends <- reduce(resize(ir, width=1, fix='end'), min.gapwidth=2)
>>>>> R> sc <- countOverlaps(ir, starts)
>>>>> R> ec <- countOverlaps(ir, ends)
>>>>>
>>>>> ... and ... good morning:
>>>>>
>>>>> R> split(ir, (paste(sc,ec,sep=":")))
>>>>> CompressedIRangesList of length 2
>>>>> $`1:1`
>>>>> IRanges of length 2
>>>>>    start end width
>>>>> [1]    10 189   180
>>>>> [2]    11 190   180
>>>>>
>>>>> $`1:2`
>>>>> IRanges of length 4
>>>>>    start end width
>>>>> [1]    10 199   190
>>>>> [2]    10 199   190
>>>>> [3]    11 200   190
>>>>> [4]     9 198   190
>>>>>
>>>>> 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
>>>>>
>>>>
>>>>
>>>
>>
>

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