scholarly journals EvoFreq: Visualization of the Evolutionary Frequencies of Sequence and Model Data

2019 ◽  
Author(s):  
Chandler D. Gatenbee ◽  
Ryan O. Schenck ◽  
Rafael Bravo ◽  
Alexander R.A. Anderson
Keyword(s):  
High Throughput ◽  
Evolutionary Dynamics ◽  
Temporal Dynamics ◽  
Sequence Data ◽  
Single Point ◽  
Model Data ◽  
Genotype Frequencies ◽  
Tool Set ◽  
Over Time

AbstractHigh throughput sequence data has provided in depth means of molecular characterization of populations. When recorded at numerous time steps, such data can reveal the evolutionary dynamics of the population under study by tracking the changes in genotype frequencies over time. This necessitates a simple and flexible means of visualizing an increasingly complex set of data. Here we offer EvoFreq as a comprehensive tool set to visualize the evolutionary and population frequency dynamics of clones at a single point in time or as population frequencies over time using a variety of informative methods. EvoFreq expands substantially on previous means of visualizing the clonal, temporal dynamics and offers users a range of options for displaying their sequence or model data. EvoFreq, implemented in R with robust user options and few dependencies, offers a high-throughput means of quickly building, and interrogating the temporal dynamics of hereditary information across many systems. EvoFreq is freely available via https://github.com/MathOnco/EvoFreq.

scholarly journals EvoFreq: visualization of the Evolutionary Frequencies of sequence and model data

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Chandler D. Gatenbee ◽  
Ryan O. Schenck ◽  
Rafael R. Bravo ◽  
Alexander R. A. Anderson
Keyword(s):  
High Throughput ◽  
Evolutionary Dynamics ◽  
Temporal Dynamics ◽  
Sequence Data ◽  
Single Point ◽  
Model Data ◽  
Genotype Frequencies ◽  
Tool Set ◽  
Over Time

Abstract Background High throughput sequence data has provided in depth means of molecular characterization of populations. When recorded at numerous time steps, such data can reveal the evolutionary dynamics of the population under study by tracking the changes in genotype frequencies over time. This necessitates a simple and flexible means of visualizing an increasingly complex set of data. Results Here we offer EvoFreq as a comprehensive tool set to visualize the evolutionary and population frequency dynamics of clones at a single point in time or as population frequencies over time using a variety of informative methods. EvoFreq expands substantially on previous means of visualizing the clonal, temporal dynamics and offers users a range of options for displaying their sequence or model data. Conclusions EvoFreq, implemented in R with robust user options and few dependencies, offers a high-throughput means of quickly building, and interrogating the temporal dynamics of hereditary information across many systems. EvoFreq is freely available via https://github.com/MathOnco/EvoFreq.

scholarly journals GrigoraSNPs: Optimized HTS DNA Forensic SNP Analysis

2017 ◽  
Author(s):  
Darrell O. Ricke ◽  
Anna Shcherbina ◽  
Adam Michaleas ◽  
Philip Fremont-Smith
Keyword(s):  
High Throughput ◽  
Tandem Repeats ◽  
High Throughput Sequencing ◽  
Dna Analysis ◽  
Sequence Data ◽  
Snp Analysis ◽  
Analysis Pipeline ◽  
Sequencing Technologies ◽  
High Throughput Dna Sequencing

AbstractHigh throughput DNA sequencing technologies enable improved characterization of forensic DNA samples enabling greater insights into DNA contributor(s). Current DNA forensics techniques rely upon allele sizing of short tandem repeats by capillary electrophoresis. High throughput sequencing enables forensic sample characterizations for large numbers of single nucleotide polymorphism loci. The slowest computational component of the DNA forensics analysis pipeline is the characterization of raw sequence data. This paper optimizes the SNP calling module of the DNA analysis pipeline with runtime results that scale linearly with the number of HTS sequences (patent pending)[1]. GrigoraSNPs can analyze 100 million reads in less than 5 minutes using 3 threads on a 4.0 GHz Intel i7-6700K laptop CPU.

scholarly journals Spatio-Temporal Mutational Profile Appearances of Swedish SARS-CoV-2 during the Early Pandemic

Viruses ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1026 ◽  
Author(s):  
Jiaxin Ling ◽  
Rachel A. Hickman ◽  
Jinlin Li ◽  
Xi Lu ◽  
Johanna F. Lindahl ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Temporal Dynamics ◽  
Evolutionary Rate ◽  
Viral Pathogenesis ◽  
Bayesian Phylogenetic Analysis ◽  
Community Transmission ◽  
Spatio Temporal ◽  
Insight Into ◽  
Over Time

Background: During the COVID-19 pandemic, the virus evolved, and we therefore aimed to provide an insight into which genetic variants were enriched, and how they spread in Sweden. Methods: We analyzed 348 Swedish SARS-CoV-2 sequences freely available from GISAID obtained from 7 February 2020 until 14 May 2020. Results: We identified 14 variant sites ≥5% frequency in the population. Among those sites, the D936Y substitution in the viral Spike protein was under positive selection. The variant sites can distinguish 11 mutational profiles in Sweden. Nine of the profiles appeared in Stockholm in March 2020. Mutational profiles 3 (B.1.1) and 6 (B.1), which contain the D936Y mutation, became the predominant profiles over time, spreading from Stockholm to other Swedish regions during April and the beginning of May. Furthermore, Bayesian phylogenetic analysis indicated that SARS-CoV-2 could have emerged in Sweden on 27 December 2019, and community transmission started on February 1st with an evolutionary rate of 1.5425 × 10−3 substitutions per year. Conclusions: Our study provides novel knowledge on the spatio-temporal dynamics of Swedish SARS-CoV-2 variants during the early pandemic. Characterization of these viral variants can provide precious insights on viral pathogenesis and can be valuable for diagnostic and drug development approaches.

scholarly journals Reuse, temporal dynamics, interest sharing, and collaboration in social tagging systems

First Monday ◽  
2014 ◽  
Author(s):  
Elizeu Santos-Neto ◽  
David Condon ◽  
Nazareno Andrade ◽  
Adriana Iamnitchi ◽  
Matei Ripeanu
Keyword(s):  
Temporal Dynamics ◽  
Discussion Groups ◽  
User Generated Content ◽  
Social Aspects ◽  
Collaborative Tagging ◽  
Collaborative Behavior ◽  
The Social ◽  
The Relationship ◽  
Over Time

User–generated content shapes the dynamics of the World Wide Web. In particular, collaborative tagging represents a simple, yet powerful, feature that enables users to share and collaboratively annotate content such as photos and URLs. This collaborative behavior and the pool of user–generated metadata create opportunities to improve existing systems and to design new mechanisms. However, to realize this potential, it is necessary to first understand the usage characteristics of current systems.This work addresses this issue by characterizing three tagging systems (CiteULike, Connotea and del.icio.us) while focusing on three aspects: i) the patterns of information (tags and items) production; ii) the temporal dynamics of users’ tag vocabularies; and, iii) the social aspects of tagging systems. The analysis of the patterns of information production shows that users publish new content more often than they annotate already existing content in the system. The opposite, however, occurs for tags; the level of tag reuse is much higher. The study of the temporal dynamics of user vocabularies shows that the growth rate of tag vocabularies across the user population over time decreases at early ages, stabilizes, and returns to increase for older users. Moreover, a closer look into the change of vocabulary contents over time shows that despite the fact that tag vocabularies are slowly growing in size with user age, the relative frequency in which each tag is used converges relatively quickly in a users lifetime. Finally, the characterization of social aspects of tagging unveils the relationship between the implicit user ties, as inferred from the similarity between users’ activity, and their explicit social ties, as represented by co–membership in discussion groups or semantic similarity between tag vocabularies.

scholarly journals Quantifying eco-evolutionary contributions to trait divergence in spatially structured systems

2019 ◽  
Author(s):  
Lynn Govaert ◽  
Jelena H. Pantel ◽  
Luc De Meester
Keyword(s):  
Genetic Differentiation ◽  
Evolutionary Dynamics ◽  
Evolutionary Ecology ◽  
Temporal Dynamics ◽  
Similar Time ◽  
Spatial Studies ◽  
Trait Divergence ◽  
Structured Systems ◽  
Evolutionary Genetic ◽  
Over Time

AbstractEcological and evolutionary processes can occur at similar time scales, and hence influence one another. There has been much progress in the development of metrics that quantify contributions of ecological and evolutionary components to trait change over time. However, many empirical evolutionary ecology studies document genetic differentiation among populations structured in space. In both time and space, the observed differentiation in trait values among populations and communities can be the result of interactions between non-evolutionary (phenotypic plasticity, changes in the relative abundance of species) and evolutionary (genetic differentiation among populations) processes. However, the tools developed so far to quantify ecological and evolutionary contributions to trait change are implicitly addressing temporal dynamics because they require directionality of change from an ancestral to a derived state. Identifying directionality from one site to another in spatial studies of eco-evolutionary dynamics is not always possible and often not desired. We here suggest three modifications to existing metrics so they allow the partitioning of ecological and evolutionary contributions to changes in population and community trait values across landscapes. Applying these spatially modified metrics to published empirical examples shows how these metrics can be used to generate new empirical insights and to facilitate future comparative analyses. The possibility to apply eco-evolutionary partitioning metrics to populations and communities in real landscapes is critical as it will broaden our capacity to quantify eco-evolutionary interactions as they occur in nature.

Combinatorial Fabrication and High-Throughput Characterization of Thin Film Metal Oxide Libraries for Solar water Splitting

2018 ◽  
Author(s):  
Alfred Ludwig ◽  
Mona Nowak ◽  
Swati Kumari ◽  
Helge S. Stein ◽  
Ramona Gutkowski ◽  
...  
Keyword(s):  
Thin Film ◽  
Metal Oxide ◽  
Water Splitting ◽  
High Throughput ◽  
Solar Water ◽  
Solar Water Splitting

scholarly journals Clinical characterization of dysautonomia in long COVID-19 patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nicolas Barizien ◽  
Morgan Le Guen ◽  
Stéphanie Russel ◽  
Pauline Touche ◽  
Florent Huang ◽  
...  
Keyword(s):  
Mixed Models ◽  
Repeated Measures ◽  
Physical Medicine ◽  
Persistent Symptoms ◽  
Index Changes ◽  
Changes Over Time ◽  
And Control ◽  
Testing Group ◽  
Over Time

AbstractIncreasing numbers of COVID-19 patients, continue to experience symptoms months after recovering from mild cases of COVID-19. Amongst these symptoms, several are related to neurological manifestations, including fatigue, anosmia, hypogeusia, headaches and hypoxia. However, the involvement of the autonomic nervous system, expressed by a dysautonomia, which can aggregate all these neurological symptoms has not been prominently reported. Here, we hypothesize that dysautonomia, could occur in secondary COVID-19 infection, also referred to as “long COVID” infection. 39 participants were included from December 2020 to January 2021 for assessment by the Department of physical medicine to enhance their physical capabilities: 12 participants with COVID-19 diagnosis and fatigue, 15 participants with COVID-19 diagnosis without fatigue and 12 control participants without COVID-19 diagnosis and without fatigue. Heart rate variability (HRV) during a change in position is commonly measured to diagnose autonomic dysregulation. In this cohort, to reflect HRV, parasympathetic/sympathetic balance was estimated using the NOL index, a multiparameter artificial intelligence-driven index calculated from extracted physiological signals by the PMD-200 pain monitoring system. Repeated-measures mixed-models testing group effect were performed to analyze NOL index changes over time between groups. A significant NOL index dissociation over time between long COVID-19 participants with fatigue and control participants was observed (p = 0.046). A trend towards significant NOL index dissociation over time was observed between long COVID-19 participants without fatigue and control participants (p = 0.109). No difference over time was observed between the two groups of long COVID-19 participants (p = 0.904). Long COVID-19 participants with fatigue may exhibit a dysautonomia characterized by dysregulation of the HRV, that is reflected by the NOL index measurements, compared to control participants. Dysautonomia may explain the persistent symptoms observed in long COVID-19 patients, such as fatigue and hypoxia. Trial registration: The study was approved by the Foch IRB: IRB00012437 (Approval Number: 20-12-02) on December 16, 2020.

scholarly journals High-throughput single-cell chromatin accessibility CRISPR screens enable unbiased identification of regulatory networks in cancer

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sarah E. Pierce ◽  
Jeffrey M. Granja ◽  
William J. Greenleaf
Keyword(s):  
Transcription Factor ◽  
Single Cell ◽  
Cancer Cells ◽  
High Throughput ◽  
Regulatory Networks ◽  
Temporal Dynamics ◽  
Chromatin Accessibility ◽  
Regulatory Regions ◽  
Factor Binding ◽  
Genome Wide

AbstractChromatin accessibility profiling can identify putative regulatory regions genome wide; however, pooled single-cell methods for assessing the effects of regulatory perturbations on accessibility are limited. Here, we report a modified droplet-based single-cell ATAC-seq protocol for perturbing and evaluating dynamic single-cell epigenetic states. This method (Spear-ATAC) enables simultaneous read-out of chromatin accessibility profiles and integrated sgRNA spacer sequences from thousands of individual cells at once. Spear-ATAC profiling of 104,592 cells representing 414 sgRNA knock-down populations reveals the temporal dynamics of epigenetic responses to regulatory perturbations in cancer cells and the associations between transcription factor binding profiles.

Sign in / Sign up

Export Citation Format

Share Document