Are there any tools out there that would convert a SAM/BAM file to a gapped multiple sequence alignment of the reads and the reference? I am looking for a text formatted output (like fasta) of this rather than a vizualization tool.
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It is a non trivial task since the SAM/BAM format isn't a multiple sequence alignment but a collection of pairwise alignments to the reference. The problem comes with conflicting inserts.
e.g. Suppose the first insert is between columns 10 and 11. Most reads say there is no insert here, one read says there should a A, another says AT, a third ATG and a forth says TG. How do you align that? Maybe:
--- (most reads)
A--
AT-
ATG
-TG
That was a fairly easy example - but what if there was another group of reads with an insert of C at this point?
My point is the conversion would require doing this kind of realignment for every insert.
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I understand that this is non-trivial and choices have to be made. I was wondering if a trivial converter that mostly assumes single-base insertions and makes the most obvious choices for a multi-base insertions was available.
Are there any aligners present that provide the padding information?
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I had some code that performed a column wise "samtools pileup", so insertions would get their own rows in the output rather than shoehorning them into the same line via +seq. It needs some tidying up as it's no longer so standalone (it's part of my BAM reading code in Gap5), but could be made so again if it's useful.Originally posted by query View PostAre there any tools out there that would convert a SAM/BAM file to a gapped multiple sequence alignment of the reads and the reference? I am looking for a text formatted output (like fasta) of this rather than a vizualization tool.
As others have pointed out this is only half the problem though. It's not going to get your data aligned better and put P CIGAR operators in. I'm not aware of tools to automatically do this, but I'm sure some must exist.
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by GATTACATLove this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
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by SEQadmin2
I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...-
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