• Arsenault Figueroa posted an update 6 months, 3 weeks ago

    The resolution of the Tree of Life has accelerated with advances in DNA sequencing technology. To achieve dense taxon sampling, it is often necessary to obtain DNA from historical museum specimens to supplement modern genetic samples. However, DNA from historical material is generally degraded, which presents various challenges. In this study, we evaluated how the coverage at variant sites and missing data among historical and modern samples impacts phylogenomic inference. We explored these patterns in the brush-tongued parrots (lories and lorikeets) of Australasia by sampling ultraconserved elements in 105 taxa. Trees estimated with low coverage characters had several clades where relationships appeared to be influenced by whether the sample came from historical or modern specimens, which were not observed when more stringent filtering was applied. To assess if the topologies were affected by missing data, we performed an outlier analysis of sites and loci, and a data reduction approach where we excluded sites based on data completeness. Depending on the outlier test, 0.15% of total sites or 38% of loci were driving the topological differences among trees, and at these sites, historical samples had 10.9x more missing data than modern ones. In contrast, 70% data completeness was necessary to avoid spurious relationships. selleck inhibitor Predictive modeling found that outlier analysis scores were correlated with parsimony informative sites in the clades whose topologies changed the most by filtering. After accounting for biased loci and understanding the stability of relationships, we inferred a more robust phylogenetic hypothesis for lories and lorikeets.Motivation The amount of genomic data generated globally is seeing explosive growth, leading to increasing needs for processing, storage, and transmission resources, which motivates the development of efficient compression tools for these data. Work so far has focused mainly on the compression of data generated by short-read technologies. However, nanopore sequencing technologies are rapidly gaining popularity due to the advantages offered by the large increase in the average size of the produced reads, the reduction in their cost, and the portability of the sequencing technology. We present ENANO, a novel lossless compression algorithm especially designed for nanopore sequencing FASTQ files. Results The main focus of ENANO is on the compression of the quality scores, as they dominate the size of the compressed file. ENANO offers two modes, Maximum Compression and Fast (default), which trade-off compression efficiency and speed. We tested ENANO, the current state of the art compressor SPRING, and the general compressor pigz, on several publicly available nanopore datasets. The results show that the proposed algorithm consistently achieves the best compression performance (in both modes) on every considered nanopore dataset, with an average improvement over pigz and SPRING of more than 24.7% and 6.3%, respectively. In addition, in terms of encoding and decoding speeds, ENANO is 2.9x and 1.7x times faster than SPRING, respectively, with memory consumption up to 0.2 GB. Availability ENANO is freely available for download at https//github.com/guilledufort/EnanoFASTQ. Supplementary information Supplementary data are available at Bioinformatics online.Purpose Prophylactic warfarin with an International Normalized Ratio (INR) goal of 1.5 to 2.0 is one antithrombotic therapy utilized in children after cardiothoracic surgery (CTS); published sources suggest a dose of 0.1 mg/kg per day to achieve this goal. However, few studies have evaluated dosing in this population. The purpose of this study was to evaluate dosing and safety outcomes in children receiving warfarin after CTS. Methods A descriptive, retrospective review was conducted to evaluate warfarin dosing and INR outcomes in patients 18 years of age or younger who underwent CTS and received prophylactic warfarin with an INR goal of 1.5 to 2.0 from January 2014 through December 2018. The primary objective was to determine the median initial warfarin dose. Secondary objectives included identifying the percentage of documented INR values that were outside the therapeutic range, the percentage of patients with therapeutic INRs at discharge, and the 30-day readmission rate. Results Twenty-six patients were included in the review. The median initial warfarin dosage was 0.07 mg/kg/d (interquartile range , 0.05-0.10 mg/kg/d). Of the total of 177 INR values collected during the entire study period, 67 (37.9%) were therapeutic, 64 (36.2%) were subtherapeutic, and 46 (26.0%) were supratherapeutic. Eighteen patients (69.2%) had at least 1 supratherapeutic INR at any point during the study period, most frequently on days 2 through 4 of therapy. At discharge, 11 patients (42.3%) had therapeutic INRs. Four patients (15.4%) were readmitted within 30 days, with bleeding documented in 2 patients during their readmission. Conclusion The majority of patients received an initial warfarin dose less than that specified in published recommendations but still had a supratherapeutic INR at least once during the study period. When initiating warfarin after CTS, a dosage of less then 0.1 mg/kg per day and frequent monitoring may be needed to achieve an INR goal of 1.5 to 2.0.Motivation Many protein function databases are built on automated or semi-automated curations and can contain various annotation errors. The correction of such misannotations is critical to improving the accuracy and reliability of the databases. Results We proposed a new approach to detect potentially incorrect Gene Ontology (GO) annotations by comparing the ratio of annotation rates (RAR) for the same GO term across different taxonomic groups, where those with a relatively low RAR usually correspond to incorrect annotations. As an illustration, we applied the approach to 20 commonly-studied species in two recent UniProt-GOA releases and identified 250 potential misannotations in the 2018-11-6 release, where only 25% of them were corrected in the 2019-6-3 release. Importantly, 56% of the misannotations are “Inferred from Biological aspect of Ancestor (IBA)” which is in contradiction with previous observations that attributed misannotations mainly to “Inferred from Sequence or structural Similarity (ISS)”, probably reflecting an error source shift due to the new developments of function annotation databases.

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