News:A Tale Of Next Generation Sequencing Platforms: Ion Torrent, Pacific Biosciences And Illumina Miseq
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11.6 years ago

A recent paper that is probably of interest to many of our readers

BMC Genomics 2012, 13:341 doi:10.1186/1471-2164-13-341, Published: 24 July 2012

A tale of three next generation sequencing platforms: comparison of Ion torrent, pacific biosciences and illumina MiSeq sequencers by Michael Quail, Miriam E Smith, Paul Coupland, Thomas D Otto, Simon R Harris, Thomas R Connor, Anna Bertoni, Harold P Swerdlow and Yong Gu

Next generation sequencing (NGS) technology has revolutionized genomic and genetic research. The pace of change in this area is rapid with three major new sequencing platforms having been released in 2011: Ion Torrent's PGM, Pacific Biosciences' RS and the Illumina MiSeq. Here we compare the results obtained with those platforms to the performance of the Illumina HiSeq, the current market leader. In order to compare these platforms and get sufficient coverage depth to allow meaningful analysis, we have sequenced a set of 4 microbial genomes with mean GC content ranging from 19.3 to 67.7%. Together, these represent a comprehensive range of genome content. Here we report our analysis of that sequence data in terms of coverage distribution, bias, GC distribution, variant detection and accuracy.

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What could be the use-case for PacBio, as it has 13% error rate and has high costs per base?

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I think long reads have the potential to bring about a substantially improved and easier interpretation of the data. It is probably a lot easier to improve on sequencing errors as the technology matures than increase read lengths.

This technology produces substantially longer reads 1500bp although the paper has disclaimer that I don't quite understand:

** Mean mapped read length includes adapter and reverse strand sequences. Subread lengths, >i.e. the individual stretches of sequence originating from the sequenced fragment, are significantly shorter

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As long as you are able to map cheap Illumina sequences to them, you can get multi-K reads with close to 100% quality. I don't have any PacBio data myself, but it should be pretty straightforward to implement, and do wonders for de novo assembly.

Or, if that doesn't work, generate short contigs with Illumina, and map those to PacBio to scaffold them. Then you can even use something like BLAST for alignment, which is much more forgiving of read errors than your average read aligner.

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