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The problem of sequence identification or matching - determining the subset of reference sequences from a given collection that are likely to contain a short, queried nucleotide sequence - is relevant for many important tasks in Computational Biology, such as metagenomics and pan-genome analysis. Due to the complex nature of such analyses and the large scale of the reference collections a resource-efficient solution to this problem is of utmost importance. This poses the threefold challenge of representing the reference collection with a data structure that is efficient to query, has light memory usage, and scales well to large collections. To solve this problem, we describe how recent advancements in associative, order-preserving, k-mer dictionaries can be combined with a compressed inverted index to implement a fast and compact colored de Bruijn graph data structure. This index takes full advantage of the fact that unitigs in the colored de Bruijn graph are monochromatic (all k-mers in a unitig have the same set of references of origin, or "color"), leveraging the order-preserving property of its dictionary. In fact, k-mers are kept in unitig order by the dictionary, thereby allowing for the encoding of the map from k-mers to their inverted lists in as little as 1+o(1) bits per unitig. Hence, one inverted list per unitig is stored in the index with almost no space/time overhead. By combining this property with simple but effective compression methods for inverted lists, the index achieves very small space. We implement these methods in a tool called Fulgor. Compared to Themisto, the prior state of the art, Fulgor indexes a heterogeneous collection of 30,691 bacterial genomes in 3.8× less space, a collection of 150,000 Salmonella enterica genomes in approximately 2× less space, is at least twice as fast for color queries, and is 2-6 × faster to construct. 

Abstract Detecting allelic imbalance at the isoform level requires accounting for inferential uncertainty, caused by multi-mapping of RNA-seq reads. Our proposed method, SEESAW, uses Salmon and Swish to offer analysis at various levels of resolution, including gene, isoform, and aggregating isoforms to groups by transcription start site. The aggregation strategies strengthen the signal for transcripts with high uncertainty. The SEESAW suite of methods is shown to have higher power than other allelic imbalance methods when there is isoform-level allelic imbalance. We also introduce a new test for detecting imbalance that varies across a covariate, such as time. 

Abstract We report the synthesis and characterization of sulfated pillar[5]arene hosts (P5S₂‐P5S₁₀) that differ in the number of sulfate substituents. All fiveP5S_nhosts display high solubility in water (73–131 mM) and do not undergo significant self‐association according to¹H NMR dilution experiments. The x‐ray crystal structures ofP5S₆,P5S₆ ⋅ Me₆HDA,P5S₈ ⋅ Me₆HDA, andP5S₁₀ ⋅ Me₆HDAreveal one intracavity molecule ofMe₆HDAand several external molecules ofMe₆HDAwhich form a network of close methonium ⋅ ⋅ ⋅ sulfate interactions. The thermodynamic parameters of complexation betweenP5S_nand the panel of guests was measured by direct or competitive isothermal titration calorimetry. We find that the binding free energy toward a guest becomes more negative as the number of sulfate substituents increase. Conversely, the binding free energy of a specific sulfated pillar[5]arene toward a homologous series of guests becomes more negative as the number of NMe groups increases. The ability to tune the host ⋅ guest affinity by changing the number of sulfate substituents will be valuable in supramolecular polymers, separation materials, and latching applications.