Analysis of the relevance and interest of students in the federal project «Providing healthcare organizations with qualified personnel»

The article analyzes the data of anonymous questioning of students of the Ural State Medical University (USMU) for to determine the relevance of the Federal project «Providing healthcare organizations with qualified personnel» according to the program "Zemsky doctor». Results are presented where you can track the degree of willingness to participate in the program, identify the motivating sides of the projectВ статье проанализированы данные анонимного анкетирования студентов Уральского государственного медицинского университета (УГМУ) для определения их заинтересованности в участии реализации Федерального проекта «Обеспечение медицинских организаций системы здравоохранения квалифицированными кадрами» по программе «Земский доктор». Представлены результаты, по которым можно отследить степень готовности участия в программе, выявить мотивирующие стороны проект

The Effects of Alignment Quality, Distance Calculation Method, Sequence Filtering, and Region on the Analysis of 16S rRNA Gene-Based Studies

Pyrosequencing of PCR-amplified fragments that target variable regions within the 16S rRNA gene has quickly become a powerful method for analyzing the membership and structure of microbial communities. This approach has revealed and introduced questions that were not fully appreciated by those carrying out traditional Sanger sequencing-based methods. These include the effects of alignment quality, the best method of calculating pairwise genetic distances for 16S rRNA genes, whether it is appropriate to filter variable regions, and how the choice of variable region relates to the genetic diversity observed in full-length sequences. I used a diverse collection of 13,501 high-quality full-length sequences to assess each of these questions. First, alignment quality had a significant impact on distance values and downstream analyses. Specifically, the greengenes alignment, which does a poor job of aligning variable regions, predicted higher genetic diversity, richness, and phylogenetic diversity than the SILVA and RDP-based alignments. Second, the effect of different gap treatments in determining pairwise genetic distances was strongly affected by the variation in sequence length for a region; however, the effect of different calculation methods was subtle when determining the sample's richness or phylogenetic diversity for a region. Third, applying a sequence mask to remove variable positions had a profound impact on genetic distances by muting the observed richness and phylogenetic diversity. Finally, the genetic distances calculated for each of the variable regions did a poor job of correlating with the full-length gene. Thus, while it is tempting to apply traditional cutoff levels derived for full-length sequences to these shorter sequences, it is not advisable. Analysis of β-diversity metrics showed that each of these factors can have a significant impact on the comparison of community membership and structure. Taken together, these results urge caution in the design and interpretation of analyses using pyrosequencing data

Large-Scale Neighbor-Joining with NINJA

Abstract Neighbor-joining is a well-established hierarchical clustering algorithm for inferring phylogenies. It begins with observed distances between pairs of sequences, and clustering order depends on a metric related to those distances. The canonical algorithm requires O(n3) time and O(n2) space for n sequences, which precludes application to very large sequence families, e.g. those containing 100,000 sequences. Datasets of this size are available today, and such phylogenies will play an increasingly important role in comparative genomics studies. Recent algorithmic advances have greatly sped up neighbor-joining for inputs of thousands of sequences, but are limited to fewer than 13,000 sequences on a system with 4GB RAM. In this paper, I describe an algorithm that speeds up neighbor-joining by dramatically reducing the number of distance values that are viewed in each iteration of the clustering procedure, while still computing a correct neighbor-joining tree. This algorithm can scale to inputs larger than 100,000 sequences because of external-memory-efficient data structures. A free implementation may by obtained fro

XplorSeq: A software environment for integrated management and phylogenetic analysis of metagenomic sequence data

<p>Abstract</p> <p>Background</p> <p>Advances in automated DNA sequencing technology have accelerated the generation of metagenomic DNA sequences, especially environmental ribosomal RNA gene (rDNA) sequences. As the scale of rDNA-based studies of microbial ecology has expanded, need has arisen for software that is capable of managing, annotating, and analyzing the plethora of diverse data accumulated in these projects.</p> <p>Results</p> <p>XplorSeq is a software package that facilitates the compilation, management and phylogenetic analysis of DNA sequences. XplorSeq was developed for, but is not limited to, high-throughput analysis of environmental rRNA gene sequences. XplorSeq integrates and extends several commonly used UNIX-based analysis tools by use of a Macintosh OS-X-based graphical user interface (GUI). Through this GUI, users may perform basic sequence import and assembly steps (base-calling, vector/primer trimming, contig assembly), perform BLAST (Basic Local Alignment and Search Tool; <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr><abbr bid="B3">3</abbr></abbrgrp>) searches of NCBI and local databases, create multiple sequence alignments, build phylogenetic trees, assemble Operational Taxonomic Units, estimate biodiversity indices, and summarize data in a variety of formats. Furthermore, sequences may be annotated with user-specified meta-data, which then can be used to sort data and organize analyses and reports. A document-based architecture permits parallel analysis of sequence data from multiple clones or amplicons, with sequences and other data stored in a single file.</p> <p>Conclusion</p> <p>XplorSeq should benefit researchers who are engaged in analyses of environmental sequence data, especially those with little experience using bioinformatics software. Although XplorSeq was developed for management of rDNA sequence data, it can be applied to most any sequencing project. The application is available free of charge for non-commercial use at <url>http://vent.colorado.edu/phyloware</url>.</p

Third-party mutualists have contrasting effects on host invasion under the enemy-release and biotic-resistance hypotheses

Plants engage in complex multipartite interactions with mutualists and antagonists, but these interactions are rarely included in studies that explore plant invasiveness. When considered in isolation, we know that beneficial microbes can enhance an exotic plant’s invasive ability and that herbivorous insects often decrease an exotic plant’s likeliness of success. However, the effect of these partners on plant fitness has not been well characterized when all three species coevolve. We use computational evolutionary modeling of a trait-based system to test how microbes and herbivores simultaneously coevolving with an invading plant affect the invaders’ probability of becoming established. Specifically, we designed a model that explores how a beneficial microbe would influence the outcome of an interaction between a plant and herbivore. To model novel interactions, we included a phenotypic trait shared by each species. Making this trait continuous and selectable allows us to explore how trait similarities between coevolving plants, herbivores and microbes affect fitness. Using this model, we answer the following questions: (1) Can a beneficial plant-microbe interaction influence the evolutionary outcome of antagonistic interactions between plants and herbivores? (2) How does the initial trait similarity between interacting organisms affect the likelihood of plant survival in novel locations? (3) Does the effect of tripartite interactions on the invasion success of a plant depend on whether organisms interact through trait similarity [Enemy Release Hypothesis (ERH)] or dissimilarity (Biotic Resistance Hypothesis)? We found that it was much more difficult for plants to invade under the ERH but that beneficial microbes increase the probability of plant survival in a novel range under both hypotheses. To our knowledge, this model is the first to use tripartite interactions to explore novel species introductions. It represents a step towards gaining a better understanding of the factors influencing establishment of exotic species to prevent future invasions. © 2017, The Author(s)