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I'm having the following issues using bwa mem on paired-end TruSeq Amplicon reads. I used the default settings with mem. The top sequence is from bwa mem. The bottom is from Illumina's BaseSpace analysis.
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I'm having the following issues using bwa mem on paired-end TruSeq Amplicon reads. I used the default settings with mem. The top sequence is from bwa mem. The bottom is from Illumina's BaseSpace analysis. -
Cross posted to Biostars: https://www.biostars.org/p/153442/ -
Any comments?Comment
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So based on a reply from biostars it looks like the BaseSpace reads have been trimmed. Now I just need to understand how they trimmed it. This is desirable since my alignment has led to the variant caller calling a lot of false indels.
It's possible that Illumina is trimming the reads based on the regions in their manifest file. If I could do the same then maybe I could get the reads I'm looking for.Comment
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You are likely doing an apples to oranges comparison (especially since you don't know the complete details of how BaseSpace analysis is being done). BaseSpace is also likely using isaac/isaac2 for the alignments (or do you know that they are using bwa).
What is it that you are trying to do? Replicate BaseSpace analysis locally (with same software/parameters)?Comment
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Is it even the same data? The reads appear to be different lengths.Comment
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The reads are from the same fastqs. I'm just trying to figure out why my alignment is looking so messy when the TruSeq Amplicon stuff is supposed to have strictly sized blocks of reads. It is possible they are using the isaac aligner so I'll have to do more tinkering to figure out what is going on.
I'm doing this to move my BaseSpace analyses in-house using bcbio-nextgen.Comment
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Is this what you are planning to use: https://github.com/chapmanb/bcbio-nextgen? Does not seem to include a trimming program at first glance (which you should plan to include).Originally posted by idedios View PostComment
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Yeah this is exactly what I am using. I could ask Brad Chapman about a trimming program.Originally posted by GenoMax View PostComment
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Love 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.07-01-2026, 11:43 AM
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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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