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Fuzzysplit: demultiplexing and trimming sequenced DNA with a declarative language.

ABSTRACT: Next-generation sequencing technologies create large, multiplexed DNA sequences that require preprocessing before any further analysis. Part of this preprocessing includes demultiplexing and trimming sequences. Although there are many existing tools that can handle these preprocessing steps, they cannot be easily extended to new sequence schematics when new pipelines are developed. We present Fuzzysplit, a tool that relies on a simple declarative language to describe the schematics of sequences, which makes it incredibly adaptable to different use cases. In this paper, we explain the matching algorithms behind Fuzzysplit and we provide a preliminary comparison of its performance with other well-established tools. Overall, we find that its matching accuracy is comparable to previous tools.

SUBMITTER: Liu D

PROVIDER: S-EPMC6589082 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Fuzzysplit: demultiplexing and trimming sequenced DNA with a declarative language.

Liu Daniel D

PeerJ 20190619

Next-generation sequencing technologies create large, multiplexed DNA sequences that require preprocessing before any further analysis. Part of this preprocessing includes demultiplexing and trimming sequences. Although there are many existing tools that can handle these preprocessing steps, they cannot be easily extended to new sequence schematics when new pipelines are developed. We present Fuzzysplit, a tool that relies on a simple declarative language to describe the schematics of sequences, ...[more]

PMID: 31249738

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Project description:BackgroundIt has been proposed that children with Specific Language Impairment (SLI) have a selective deficit in procedural learning, with relatively spared declarative learning. In previous studies we and others confirmed deficits in procedural learning of sequences, using both verbal and nonverbal materials. Here we studied the same children using a task that implicates the declarative system, auditory-visual paired associate learning. There were parallel tasks for verbal materials (vocabulary learning) and nonverbal materials (meaningless patterns and sounds).MethodsParticipants were 28 children with SLI aged 7-11 years, 28 younger typically-developing children matched for raw scores on a test of receptive grammar, and 20 typically-developing children matched on chronological age. Children were given four sessions of paired-associate training using a computer game adopting an errorless learning procedure, during which they had to select a picture from an array of four to match a heard stimulus. In each session they did both vocabulary training, where the items were eight names and pictures of rare animals, and nonverbal training, where stimuli were eight visual patterns paired with complex nonverbal sounds. A total of 96 trials of each type was presented over four days.ResultsIn all groups, accuracy improved across the four sessions for both types of material. For the vocabulary task, the age-matched control group outperformed the other two groups in the starting level of performance, whereas for the nonverbal paired-associate task, there were no reliable differences between groups. In both tasks, rate of learning was comparable for all three groups.ConclusionsThese results are consistent with the Procedural Deficit Hypothesis of SLI, in finding spared declarative learning on a nonverbal auditory-visual paired associate task. On the verbal version of the task, the SLI group had a deficit in learning relative to age-matched controls, which was evident on the first block in the first session. However, the subsequent rate of learning was consistent across all three groups. Problems in vocabulary learning in SLI could reflect the procedural demands of remembering novel phonological strings; declarative learning of crossmodal links between auditory and visual information appears to be intact.

Project description:BackgroundDNA tracts composed of only two bases are possible in six combinations: A+G (purines, R), C+T (pyrimidines, Y), G+T (Keto, K), A+C (Imino, M), A+T (Weak, W) and G+C (Strong, S). It is long known that all-pyrimidine tracts, complemented by all-purines tracts ("R.Y tracts"), are excessively present in analyzed DNA. We have previously shown that R.Y tracts are in vast excess in yeast promoters, and brought evidence for their role in gene regulation. Here we report the systematic mapping of all six binary combinations on the level of complete sequenced chromosomes, as well as in their different subregions.ResultsDNA tracts composed of the above binary base combinations have been mapped in seven sequenced chromosomes: Human chromosomes 21 and 22 (the major contigs); Drosophila melanogaster chr. 2R; Caenorhabditis elegans chr. I; Arabidopsis thaliana chr. II; Saccharomyces cerevisiae chr. IV and M. jannaschii. A huge over-representation, reaching million-folds, has been found for very long tracts of all binary motifs except S, in each of the seven organisms. Long R.Y tracts are the most excessive, except in D. melanogaster, where the K.M motif predominates. S (G, C rich) tracts are in excess mainly in CpG islands; the W motif predominates in bacteria. Many excessively long W tracts are nevertheless found also in the archeon and in the eukaryotes. The survey of complete chromosomes enables us, for the first time, to map systematically the intergenic regions. In human and other chromosomes we find the highest over-representation of the binary DNA tracts in the intergenic regions. These over-representations are only partly explainable by the presence of interspersed elements.ConclusionsThe over-representation of long DNA tracts composed of five of the above motifs is the largest deviation from randomness so far established for DNA, and this in a wide range of eukaryotic and archeal chromosomes. A propensity for ready DNA unwinding is proposed as the functional role, explaining the evolutionary conservation of the huge excesses observed.

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Fuzzysplit: demultiplexing and trimming sequenced DNA with a declarative language.

Publications

Fuzzysplit: demultiplexing and trimming sequenced DNA with a declarative language.

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