Hi Jianhong,

Perfect. With this I still keep the biological information I needed, and 
I will probably just need to match this "uc007aeu.1" and similar to the 
values in the kgXref table, which I can import separately (using the field

#*kgID*	mRNA	spID	spDisplayID	geneSymbol	refseq	protAcc	description

to join the tables), but feel free to correct me if I am wrong. I will 
furthermore try all these commands and see if there could be any more 
ways to make the data look complete and beautiful!

Thanks, again and again, for the prompt support.

Best regards,

Federico

On 29/03/12 21:45, Ou, Jianhong wrote:
> Hi Federico,
>
> The feature column is the rownames of annotationData. so you could try:
> rownames(RDucscmm9)<-RDucscmm9$tx_name
> before annotatePeakInBatch.
>
> Yours sincerely,
>
> Jianhong Ou
>
> jianhong.ou@umassmed.edu <mailto:jianhong.ou@umassmed.edu>
>
>
> On Mar 29, 2012, at 3:12 PM, Federico Marini wrote:
>
>> Hi Jianhong,
>>
>> I tried the intermediate step you suggested and it actually returned 
>> no error, just the warning message:
>>
>>     Warning message:
>>     In annotatePeakInBatch(peaksRDt[1:10, ], AnnotationData =
>>     RDucscmm9,  :
>>       Please use select instead of multiple!
>>
>> but this is minor. So, first of all thank you one more time for 
>> solving this issue. Just one more thing, and then I think I really am 
>> good to go: the table I downloaded should ideally report the NM_ and 
>> NR_ identifiers for the transcripts, but in the final output what I 
>> see is this (in bold the column of interest)
>>
>>     RangedData with 14 rows and 9 value columns across 1 space
>>                           space             ranges |        
>>     peak      strand
>>     <factor> <IRanges> | <character> <character>
>>     MACS_peak_1 01511      chr1 [3024414, 3024497] | 
>>     MACS_peak_1           -
>>     MACS_peak_10 01515     chr1 [4346000, 4346141] |
>>     MACS_peak_10           -
>>     MACS_peak_2 01511      chr1 [3115427, 3115503] | 
>>     MACS_peak_2           -
>>     MACS_peak_3 01511      chr1 [3145725, 3145836] | 
>>     MACS_peak_3           -
>>     MACS_peak_4 01511      chr1 [3332349, 3332698] | 
>>     MACS_peak_4           -
>>     MACS_peak_5 01513      chr1 [3566535, 3566719] | 
>>     MACS_peak_5           -
>>     MACS_peak_6 01512      chr1 [3726359, 3726485] | 
>>     MACS_peak_6           -
>>     MACS_peak_7 01512      chr1 [3795201, 3795271] | 
>>     MACS_peak_7           -
>>     MACS_peak_8 01515      chr1 [4204115, 4204357] | 
>>     MACS_peak_8           -
>>     MACS_peak_9 01515      chr1 [4283090, 4283190] | 
>>     MACS_peak_9           -
>>     MACS_peak_10 01514     chr1 [4346000, 4346141] |
>>     MACS_peak_10           -
>>     MACS_peak_4 01512      chr1 [3332349, 3332698] | 
>>     MACS_peak_4           -
>>     MACS_peak_5 01512      chr1 [3566535, 3566719] | 
>>     MACS_peak_5           -
>>     MACS_peak_9 01514      chr1 [4283090, 4283190] | 
>>     MACS_peak_9           -
>>                            feature start_position end_position
>>     insideFeature
>>     <character> <numeric> <numeric> <character>
>>     MACS_peak_1 01511 *01511*        3195985      3205713    downstream
>>     MACS_peak_10 01515 *01515*        4333588      4350395        inside
>>     MACS_peak_2 01511 *01511*        3195985      3205713    downstream
>>     MACS_peak_3 01511 *01511*        3195985      3205713    downstream
>>     MACS_peak_4 01511 *01511*        3195985      3205713      upstream
>>     MACS_peak_5 01513 *01513*        3638392      3648985    downstream
>>     MACS_peak_6 01512 *01512*        3204563      3661579      upstream
>>     MACS_peak_7 01512 *01512*        3204563      3661579      upstream
>>     MACS_peak_8 01515 *01515*        4333588      4350395    downstream
>>     MACS_peak_9 01515 *01515*        4333588      4350395    downstream
>>     MACS_peak_10 01514 *01514*        4280927      4399322        inside
>>     MACS_peak_4 01512 *01512*        3204563      3661579        inside
>>     MACS_peak_5 01512 *01512*        3204563      3661579        inside
>>     MACS_peak_9 01514 *01514*        4280927      4399322        inside
>>                        distancetoFeature shortestDistance
>>     fromOverlappingOrNearest
>>     <numeric> <numeric> <character>
>>     MACS_peak_1 01511             181299           171488            
>>     NearestStart
>>     MACS_peak_10 01515              4395             4254            
>>     NearestStart
>>     MACS_peak_2 01511              90286            80482            
>>     NearestStart
>>     MACS_peak_3 01511              59988            50149            
>>     NearestStart
>>     MACS_peak_4 01511            -126636           126636            
>>     NearestStart
>>     MACS_peak_5 01513              82450            71673            
>>     NearestStart
>>     MACS_peak_6 01512             -64780            64780            
>>     NearestStart
>>     MACS_peak_7 01512            -133622           133622            
>>     NearestStart
>>     MACS_peak_8 01515             146280           129231            
>>     NearestStart
>>     MACS_peak_9 01515              67305            50398            
>>     NearestStart
>>     MACS_peak_10 01514             53322           
>>     53181              Overlapping
>>     MACS_peak_4 01512             329230          
>>     127786              Overlapping
>>     MACS_peak_5 01512              95044           
>>     94860              Overlapping
>>     MACS_peak_9 01514             116232            
>>     2163              Overlapping
>>
>> So, no(t yet) the TranscriptID as I was planning (while it appears 
>> regularly ENSMUSG00000064842 or others when I use the TSS you 
>> provided). Is some step still missing? I also tried playing around 
>> with the vals and columns parameters in the transcripts step, but it 
>> didn't work.
>>
>> Best regards,
>>
>> Federico
>>
>>
>> On 29/03/12 18:52, Ou, Jianhong wrote:
>>> Hi Federico,
>>>
>>> Could you please have a try
>>> RDucscmm9$strand<-as(RDucscmm9$strand,"factor")
>>> before using annotatePeakInBatch, and tell me how about the results.
>>>
>>> Yours sincerely,
>>>
>>> Jianhong Ou
>>>
>>> jianhong.ou@umassmed.edu <mailto:jianhong.ou@umassmed.edu>
>>>
>>>
>>> On Mar 29, 2012, at 12:42 PM, Zhu, Lihua (Julie) wrote:
>>>
>>>> Dear Federico,
>>>>
>>>> The following code works. So RDucscmm9<- as(ucscmm9, "RangedData") 
>>>> should work as well. It complains about ranges being NA.
>>>>
>>>> Jianhong will help you to debug and get back to you. Thanks!
>>>>
>>>> gr <-
>>>>     GRanges(seqnames =
>>>>             Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)),
>>>>             ranges =
>>>>             IRanges(1:10, width = 10:1, names = head(letters,10)),
>>>>             strand =
>>>>             Rle(strand(c("-", "+", "*", "+", "-")),
>>>>                 c(1, 2, 2, 3, 2)),
>>>>             score = 1:10,
>>>>             GC = seq(1, 0, length=10))
>>>>
>>>> as(gr, “RangedData”)
>>>>
>>>> Best regards,
>>>>
>>>> Julie
>>>>
>>>> On 3/29/12 11:27 AM, "Federico Marini" <f.marini@imb-mainz.de 
>>>> <x-msg://458/f.marini@imb-mainz.de>> wrote:
>>>>
>>>>>  Dear Julie,
>>>>>
>>>>>  Thanks first of all for the positive and prompt answer.
>>>>>
>>>>>  I just have one additional question: when retrieving the 
>>>>> TranscriptDb object, these are the steps I took.
>>>>>
>>>>>
>>>>>> source("http://bioconductor.org/biocLite.R" 
>>>>>> <http://bioconductor.org/biocLite.R> )
>>>>>>  biocLite("GenomicFeatures")
>>>>>>
>>>>>>  library(GenomicFeatures)
>>>>>>  supportedUCSCtables()
>>>>>>  mm9KG <-makeTranscriptDbFromUCSC(genome = "mm9",tablename = 
>>>>>> "knownGene")
>>>>>>
>>>>>>  ucscmm9<- transcripts(mm9KG)
>>>>>> annotPeaksUCSC<-annotatePeakInBatch(peaksRDt[1:10,],AnnotationData=ucscmm9,output="both",multiple=FALSE,maxgap=0)
>>>>>>
>>>>>
>>>>>  This returns an error since annotatePeakInBatch requires a 
>>>>> RangedData object for the annotation, but my "ucscmm9" is a 
>>>>> GRanges object; still, 
>>>>> http://wiki.fhcrc.org/bioc/Transcript_Annotation_API_Spec 
>>>>> specified that I would have a RangedData object as the output for 
>>>>> the transcripts function - but apparently it didn't work like that.
>>>>>
>>>>>  I thought one way to make it work is to us
>>>>>
>>>>>> RDucscmm9<- as (ucscmm9, "RangedData")
>>>>>>
>>>>> but I get this as an output
>>>>>
>>>>>> Error in .Call2("solve_user_SEW0", start, end, width, PACKAGE = 
>>>>>> "IRanges") :
>>>>>>    solving row 1: range cannot be determined from the supplied 
>>>>>> arguments (too many NAs)
>>>>>>
>>>>> I tried googling around for this, but sadly no solution was found 
>>>>> (yet). Is there a tested and smart way to do this - and get 
>>>>> something which is under all aspects comparable to the 
>>>>> TSS.mouse.NCBIM37 annotation?
>>>>>
>>>>>  Thanks again for the attention.
>>>>>
>>>>>  Best regards,
>>>>>
>>>>>  Federico
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>  On 29/03/12 16:43, Zhu, Lihua (Julie) wrote:
>>>>>>  Re: ChIPpeakAnno - Request of information Dear Federico,
>>>>>>
>>>>>>  Yes. You can ChIPpeakAnno to annotate your peaks with refseq 
>>>>>> genes/transcripts. You could also use any custom annotation file 
>>>>>> you have.
>>>>>>
>>>>>>  One option for obtaining the refseq genes/transcripts would be 
>>>>>> using GenomicFeatures package. I am ccing Bioconductor listserv 
>>>>>> for others to chime in.
>>>>>>
>>>>>> library(GenomicFeatures)
>>>>>> supportedUCSCtables()
>>>>>>
>>>>>> Best regards,
>>>>>>
>>>>>>  Julie
>>>>>>
>>>>>>
>>>>>>  On 3/29/12 3:58 AM, "Federico Marini" <f.marini@imb-mainz.de 
>>>>>> <x-msg://458/f.marini@imb-mainz.de>> wrote:
>>>>>>
>>>>>>
>>>>>>> Dear Prof. Zhu,
>>>>>>>
>>>>>>>   My name is Federico Marini, and I started recently my activity 
>>>>>>> as PhD student at the Institute of Molecular Biology in Mainz, 
>>>>>>> Germany.
>>>>>>>
>>>>>>>   I contact you to request additional information regarding one 
>>>>>>> of your published works, namely "ChIPpeakAnno: a Bioconductor 
>>>>>>> package to annotate ChIP-seq and ChIP-chip data", which I had 
>>>>>>> the pleasure to read in detail. I would like to get perform the 
>>>>>>> annotation referring to the refseq genes/transcripts, instead of 
>>>>>>> the ensembl ones. Could it be possible to obtain a similar 
>>>>>>> object for this, and if so, what could be the best/smartest way 
>>>>>>> to do it?
>>>>>>>
>>>>>>>   Since it could be a very precious resource for the needs of 
>>>>>>> our lab, this is why I chose to contact you directly.
>>>>>>>
>>>>>>>   Thanks in advance for your time and attention.
>>>>>>>
>>>>>>>   Best regards,
>>>>>>>
>>>>>>>   Federico Marini
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>>
>>>
>>
>> -- 
>> *Federico Marini*
>> Signaling to Chromatin Laboratory
>> Institute of Molecular Biology gGmbH (IMB)
>> http://www.imb-mainz.de <http://www.imb-mainz.de/>
>> Tel: +49 (0) 6131 39 21462
>

-- 
*Federico Marini*
Signaling to Chromatin Laboratory
Institute of Molecular Biology gGmbH (IMB)
http://www.imb-mainz.de
Tel: +49 (0) 6131 39 21462

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