[BioC] Trimming of partial adaptor sequences
Harris A. Jaffee
hj at jhu.edu
Wed Jul 24 06:23:07 CEST 2013
Sorry to chime in late; I've been on the road. I'm still not clear on your specifications.
Herve's answer showed you how to do trimming of the same adaptor, so to speak, at both ends
of your reads, but I took your original question to be about trimming at the 3' end only (in
which case your adaptor goes as 'Rpattern', with nothing in 'Lpattern'). But I could be all
wrong. Please explain in more detail what you want, if you aren't happy yet.
You are right about a given "max.L/Rmismatch" value not being suitable for all your data.
There is no way to beat that except to subdivide your data. You may be able to gather some
intuition using neditStartingAt() or neditEndingAt().
To prevent (tiny) "false positive" trimming, construct a max.mismatch *vector* of the same
length as your adaptor string, with -1 in the low spots. By "low", I mean as many letters
as you want never to be trimmed. For example, to set a trimming lower limit to 3 letters,
do something along these lines:
rate <- .25 # pretty big rate
max.Lmismatch (or *R*, whichever you really want) <- rate * 1:nchar(adaptor)
max.Lmismatch[1:2] <- -1
Equivalently, send a shorter vector ("missing the low spots"):
max.Lmismatch <- (rate * 1:nchar(adaptor)) [-(1:2)]
There isn't an argument to do this for you. Maybe there should be.
There is also a trick to locate adaptors in "accidental places" in your data, such as 3'
adaptors in the middle of reads, like
[good_data][adaptor]AAAAAAAAAAAAAAAAAAAAA
For your Rpattern value, append many N's to your adaptor string, and set Rfixed="subject"
(or Rfixed=FALSE, just *not* Rfixed="pattern"). I suppose, if you knew that the only
garbage that might occur to the right of such an accident was always poly-*A*, then you
could just append A's instead of N's, and then you wouldn't need to relax Rfixed. This
line of attack, with the N's, is due to Patrick Aboyoun, the original author.
Let me know if I'm way off.
On Jul 23, 2013, at 6:26 PM, Taylor, Sean D wrote:
> Thanks all for your input. I will give some of these solutions a try and will probably go with whichever is faster and integrates well with the remainder of our analyses in R.
>
> Herve, thanks for the clarification. Looking back I see that I hadn't explored the function fully. I think it will work, but I have a few follow-up questions. Here is the sample data set that I'm playing around with:
>
> library(Rsamtools)
> bamfile <- system.file("extdata", "ex1.bam", package="Rsamtools")
> param <- ScanBamParam(what=c("seq", "qual"))
> gal <- readGappedAlignments(bamfile, use.names=TRUE, param=param)
>
> These sequences are all relatively short, about 35nts each. I set the first read as my "adaptor" and pulled out all the reads that have a start position overlapping the 'adaptor' sequence:
>
> gal<-gal[which(start(gal)<=width(gal[1]))]
> reads <- setNames(mcols(gal)$seq, names(gal))
> seqnames<-seqnames(gal)
> adaptor<-reads[[1]]
>
> The data are from two 'chromosomes', seq1 and seq2. My adaptor is from seq1, so I expect it to overlap on all seq1, but not on seq2. This lets me approximate best and worst case scenarios:
>
> seq1<-reads[seqnames=='seq1']
> seq2<-reads[seqnames=='seq2']
>
>> adaptor
> 36-letter "DNAString" instance
> seq: CACTAGTGGCTCATTGTAAATGTGTGGTTTAACTCG
>
>> seq1
> A DNAStringSet instance of length 16
> width seq names
> [1] 36 CACTAGTGGCTCATTGTAAATGTGTGGTTTAACTCG B7_591:4:96:693:509
> [2] 35 CTAGTGGCTCATTGTAAATGTGTGGTTTAACTCGT EAS54_65:7:152:36...
> [3] 35 AGTGGCTCATTGTAAATGTGTGGTTTAACTCGTCC EAS51_64:8:5:734:57
> [4] 36 GTGGCTCATTGTAATTTTTTGTTTTAACTCTTCTCT B7_591:1:289:587:906
> [5] 35 GCTCATTGTAAATGTGTGGTTTAACTCGTCCATGG EAS56_59:8:38:671...
> ... ... ...
> [12] 36 GTGGTTTAACTCGTCCATGGCCCAGCATTAGGGAGC B7_591:3:188:662:155
> [13] 35 TTTAACTCGTCCATGGCCCAGCATTAGGGATCTGT EAS56_59:2:225:60...
> [14] 35 TTAACTCGTCCATGGCCCAGCATTAGGGAGCTGTG EAS51_66:7:328:39...
> [15] 35 AACTCGTCCATGGCCCAGCATTAGGGAGCTGTGGA EAS51_64:5:257:96...
> [16] 35 GTACATGGCCCAGCATTAGGGAGCTGTGGACCCCG EAS54_61:4:143:69...
>
>> seq2
> A DNAStringSet instance of length 25
> width seq names
> [1] 36 TTCAAATGAACTTCTGTAATTGAAAAATTCATTTAA B7_591:8:4:841:340
> [2] 35 TTCAAATGAACTTCTGTAATTGAAAAATTCATTTA EAS54_67:4:142:94...
> [3] 35 TTCAAATGAACTTCTGTAATTGAAAAATTCATTTA EAS54_67:6:43:859...
> [4] 35 TCAAATGAACTTCTGTAATTGAAAAATTCATTTAA EAS1_93:2:286:923...
> [5] 35 AATGAACTTCTGTAATTGAAAAATTCATTTAAGAA EAS1_99:8:117:578...
> ... ... ...
> [21] 35 AAATTCATTTAAGAAATTACAAAATATAGTTGAAA EAS54_65:8:305:81...
> [22] 35 AATTCATTTAAGAAATTACAAAATATAGTTGAAAG EAS114_26:7:13:17...
> [23] 35 CATTTAAGAAATTACAAAATATAGTTGAAAGCTCT EAS56_63:7:34:334...
> [24] 35 TTAAGAAATTACAAAATATAGTTGAAAGCTCTAAC EAS114_45:3:32:13...
> [25] 40 TAAGAAATTACAAAATATAGTTGAAAGCTCTAACAATAGA EAS139_19:5:70:31...
>
> If I use the basic parameters for trimLRPatterns on seq1:
>
>> trimmed_reads1<-trimLRPatterns(Lpattern=adaptor, subject=seq1)
>
> My expected sequence widths after trimming are:
>> width(seq1)-(length(adaptor)-start(gal)[which(seqnames=='seq1')]+1)
> [1] 0 1 3 5 7 11 12 13 16 20 20 23 26 27 29 34
>
> Actually trimmed sequence widths:
>> width(trimmed_reads1)
> [1] 0 1 3 35 7 11 12 13 16 20 20 23 26 27 29 34
>
> Here, the 4th sequence isn't trimmed because of some mismatches in the sequence. I expect that my data will have some mismatches, so I need to be able to work with those. So I tried setting the max.Lmismatch=5 to allow for up to 5 mismatches, but got no trimming:
>
>> trimmed_reads2<-trimLRPatterns(Lpattern=adaptor, subject=seq1, max.Lmismatch=5)
>> width(trimmed_reads2)
> [1] 0 35 35 36 35 35 36 35 35 35 35 36 35 35 35 35
>
> In my experimenting, I had gone straight to this and saw that it didn't trim partial sequence with these settings, so I had concluded that it wouldn't do the job. After playing with it, I tried adjusting trimLRPatterns=0.5 to allow 50% mismatches (if I understand that correctly) and this time get too much trimming on the last sequence:
>
>> trimmed_reads3<-trimLRPatterns(Lpattern=adaptor, subject=seq1, max.Lmismatch=0.5)
>> width(trimmed_reads3)
> [1] 0 1 3 5 7 11 12 13 16 20 20 23 26 27 29 27
>
> I tried setting max.Lmismatch =0.1 but got too little trimming again:
>
>> trimmed_reads4<-trimLRPatterns(Lpattern=adaptor, subject=seq1, max.Lmismatch=0.1)
>> width(trimmed_reads4)
> [1] 0 1 3 35 7 11 12 13 16 20 20 23 26 27 29 34
>
> I could probably optimize until I got it just right, but with a large data set that might not be too practical.
> If I try these same settings against seq2, where there is not supposed to be overlap with the adaptor, I get erroneous trimming with mismatch =0.5. With mismatch = 0.1, it is better, but it decides to trim off the first nucleotide on a few of them:
>
>> trimmed_reads5<-trimLRPatterns(Lpattern=adaptor, subject=seq2, max.Lmismatch=0.5)
>> trimmed_reads6<-trimLRPatterns(Lpattern=adaptor, subject=seq2, max.Lmismatch=0.1)
>> width(seq2)
> [1] 36 35 35 35 35 35 35 35 36 35 35 35 35 35 35 35 35 35 35 35 35 35 35 35 40
>> width(trimmed_reads5)
> [1] 27 26 26 27 11 26 26 26 14 13 13 13 28 28 31 23 27 28 29 27 28 29 33 27 40
>> width(trimmed_reads6)
> [1] 36 35 35 35 35 35 35 35 36 35 35 35 34 34 35 35 34 35 35 35 35 35 35 35 40
>
> So what is the best way to optimize this? Obviously you are trying to balance recognizing the whole adaptor sequence without trimming off too many false positives. Also, can I set a limit that requires to have at least n bases overlap with the adaptor suffix?
>
> Thanks for your help (again)!
> Sean
>
>
>> -----Original Message-----
>> From: Hervé Pagès [mailto:hpages at fhcrc.org]
>> Sent: Monday, July 22, 2013 5:37 PM
>> To: Taylor, Sean D
>> Cc: bioconductor at r-project.org
>> Subject: Re: Trimming of partial adaptor sequences
>>
>> Hi Sean,
>>
>> On 07/22/2013 01:02 PM, Taylor, Sean D wrote:
>>> We have been experimenting with a NGS protocol in which we insert
>>> sheared genomic fragments into a custom plasmid for sequencing on an
>>> Illumina MiSeq instrument. The insertion site of this plasmid is
>>> flanked by our own custom barcodes (N7) and ~80 nt Illumina-based
>>> adaptor sequence. We then PCR out the insert with barcodes and
>>> adaptors for sequencing. Our adaptor sequence is similar to the
>>> Illumina adaptor, but we use custom primer binding sites. We are not
>>> sure if the Illumina software will be able to recognize and trim our
>>> custom adaptors. We are trying to figure out the best way to trim read
>> through into the 3'
>>> adaptor ourselves. We have roughly three scenarios:
>>>
>>> (1) The insert is long enough that we have no read through
>>>
>>> (2) The vector is empty, in which case the entire adaptor sequence is
>>> present
>>>
>>> (3) The insert is long enough to have useful data, but we get
>>> read-through into the 3' adaptor sequence that must be trimmed.
>>>
>>> The solution we are currently working on is to identify the minimal
>>> sequence that is recognizable as the adaptor sequence and trim that
>>> using trimLRPatterns() in the Biostrings package. Ideally we would
>>> like it if we could give trimLRPatterns() the entire adaptor sequence
>>> and have it recognize it on our reads even if it is only partially present.
>>
>> May be I misunderstand what you are trying to do exactly but yes, you can
>> give the entire adaptor sequence to trimLRPatterns() and it will recognize it
>> on our reads even if it's only partially present:
>>
>> library(Biostrings)
>>
>> adaptor <- DNAString("ACCAGGACAA") # entire adaptor
>> reads <- DNAStringSet(c(
>> "GACAATTTATTT", # adaptor partially present on the left
>> "CAATTTATTTGC", # adaptor partially present on the left
>> "TTTATTTACCAG", # adaptor partially present on the right
>> "CAATTTTTTACC" # adaptor partially present on both ends
>> ))
>>
>> Then:
>>
>>> trimLRPatterns(Lpattern=adaptor, Rpattern=adaptor, subject=reads)
>> A DNAStringSet instance of length 4
>> width seq
>> [1] 7 TTTATTT
>> [2] 9 TTTATTTGC
>> [3] 7 TTTATTT
>> [4] 6 TTTTTT
>>
>> Note that trimLRPatterns() expects that, when the adaptor is partially
>> present on the left (resp. right), what's present is a suffix (resp.
>> prefix) of the adaptor, and not an arbitrary substring of it. Is it what you
>> expect too?
>>
>> Thanks,
>> H.
>>
>>> However, in my experimenting it did not seem to be able to this. I
>>> thought I would ask the Bioconductor community if there are any better
>>> solutions to recognizing and trimming partial adaptor sequences.
>>>
>>> Thanks in advance for any input.
>>>
>>> Sean Taylor
>>>
>>> Post-doctoral Fellow
>>>
>>> Fred Hutchinson Cancer Research Center
>>>
>>> 206-667-5544
>>>
>>
>> --
>> Hervé Pagès
>>
>> Program in Computational Biology
>> Division of Public Health Sciences
>> Fred Hutchinson Cancer Research Center
>> 1100 Fairview Ave. N, M1-B514
>> P.O. Box 19024
>> Seattle, WA 98109-1024
>>
>> E-mail: hpages at fhcrc.org
>> Phone: (206) 667-5791
>> Fax: (206) 667-1319
>
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