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Improved lower bounds of DNA tags based on a modified genetic algorithm.

ABSTRACT: The well-known massively parallel sequencing method is efficient and it can obtain sequence data from multiple individual samples. In order to ensure that sequencing, replication, and oligonucleotide synthesis errors do not result in tags (or barcodes) that are unrecoverable or confused, the tag sequences should be abundant and sufficiently different. Recently, many design methods have been proposed for correcting errors in data using error-correcting codes. The existing tag sets contain small tag sequences, so we used a modified genetic algorithm to improve the lower bound of the tag sets in this study. Compared with previous research, our algorithm is effective for designing sets of DNA tags. Moreover, the GC content determined by existing methods includes an imprecise range. Thus, we improved the GC content determination method to obtain tag sets that control the GC content in a more precise range. Finally, previous studies have only considered perfect self-complementarity. Thus, we considered the crossover between different tags and introduced an improved constraint into the design of tag sets.

SUBMITTER: Wang B

PROVIDER: S-EPMC4332859 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Improved lower bounds of DNA tags based on a modified genetic algorithm.

Wang Bin B Wei Xiaopeng X Dong Jing J Zhang Qiang Q

PloS one 20150218 2

The well-known massively parallel sequencing method is efficient and it can obtain sequence data from multiple individual samples. In order to ensure that sequencing, replication, and oligonucleotide synthesis errors do not result in tags (or barcodes) that are unrecoverable or confused, the tag sequences should be abundant and sufficiently different. Recently, many design methods have been proposed for correcting errors in data using error-correcting codes. The existing tag sets contain small t ...[more]

PMID: 25693135

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Project description:BACKGROUND: Since 1998 the Joint United Nations Programme on HIV/AIDS and the World Health Organization has provided estimates on the magnitude of the HIV epidemic for individual countries. Starting with the 2003 estimates, plausibility bounds about the estimates were also reported. The bounds are intended to serve as a guide as to what reasonable or plausible ranges are for the uncertainty in HIV incidence, prevalence, and mortality. METHODS: Plausibility bounds were developed for three situations: for countries with generalised epidemics, for countries with low level or concentrated epidemics (LLC), and for regions. The techniques used build on those developed for the previous reporting round. However the current bounds are based on the available surveillance and survey data from each individual country rather than on data from a few prototypical countries. RESULTS: The uncertainty around the HIV estimates depends on the quality of the surveillance system in the country. Countries with population based HIV seroprevalence surveys have the tightest plausibility bounds (average relative range about the adult HIV prevalence (ARR) of -18% to +19%.) Generalised epidemic countries without a survey have the next tightest ranges (average ARR of -46% to +59%). Those LLC countries which have conducted multiple surveys over time for HIV among the populations most at risk have the bounds similar to those in generalised epidemic countries (ARR -40% to +67%). As the number and quality of the studies in LLC countries goes down, the plausibility bounds increase (ARR of -38% to +102% for countries with medium quality data and ARR of -53% to +183% for countries with poor quality data). The plausibility bounds for regions directly reflect the bounds for the countries in those regions. CONCLUSIONS: Although scientific, the plausibility bounds do not represent and should not be interpreted as formal statistical confidence intervals. However in order to make the bounds as meaningful as possible the authors have tried to apply reasonable statistical approaches and assumptions to their derivation. An understanding of the uncertainty in the HIV estimates may help policy makers take better informed decisions to address the epidemic in their respective countries.

Project description:BackgroundShort oligonucleotides can be used as markers to tag and track DNA sequences. For example, barcoding techniques (i.e. Multiplex Identifiers or Indexing) use short oligonucleotides to distinguish between reads from different DNA samples pooled for high-throughput sequencing. A similar technique called molecule tagging uses the same principles but is applied to individual DNA template molecules. Each template molecule is tagged with a unique oligonucleotide prior to polymerase chain reaction. The resulting amplicon sequences can be traced back to their original templates by their oligonucleotide tag. Consensus building from sequences sharing the same tag enables inference of original template molecules thereby reducing effects of sequencing error and polymerase chain reaction bias. Several independent groups have developed similar protocols for molecule tagging; however, user-friendly software for build consensus sequences from molecule tagged reads is not readily available or is highly specific for a particular protocol.ResultsMT-Toolbox recognizes oligonucleotide tags in amplicons and infers the correct template sequence. On a set of molecule tagged test reads, MT-Toolbox generates sequences having on average 0.00047 errors per base. MT-Toolbox includes a graphical user interface, command line interface, and options for speed and accuracy maximization. It can be run in serial on a standard personal computer or in parallel on a Load Sharing Facility based cluster system. An optional plugin provides features for common 16S metagenome profiling analysis such as chimera filtering, building operational taxonomic units, contaminant removal, and taxonomy assignments.ConclusionsMT-Toolbox provides an accessible, user-friendly environment for analysis of molecule tagged reads thereby reducing technical errors and polymerase chain reaction bias. These improvements reduce noise and allow for greater precision in single amplicon sequencing experiments.

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Improved lower bounds of DNA tags based on a modified genetic algorithm.

Publications

Improved lower bounds of DNA tags based on a modified genetic algorithm.

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