scholarly journals RERconverge: an R package for associating evolutionary rates with convergent traits

2018 ◽  
Author(s):  
Amanda Kowalczyk ◽  
Wynn K Meyer ◽  
Raghavendran Partha ◽  
Weiguang Mao ◽  
Nathan L Clark ◽  
...  
Keyword(s):  
Molecular Basis ◽  
Evolutionary Rate ◽  
Source Code ◽  
R Package ◽  
Evolutionary Rates ◽  
Supplementary Information ◽  
Genome Sequences ◽  
Link Type ◽  
Convergent Rate ◽  
Tests For Association

AbstractMotivation: When different lineages of organisms independently adapt to similar environments, selection often acts repeatedly upon the same genes, leading to signatures of convergent evolutionary rate shifts at these genes. With the increasing availability of genome sequences for organisms displaying a variety of convergent traits, the ability to identify genes with such convergent rate signatures would enable new insights into the molecular basis of these traits.Results: Here we present the R package RERconverge, which tests for association between relative evolutionary rates of genes and the evolution of traits across a phylogeny. RERconverge can perform associations with binary and continuous traits, and it contains tools for visualization and enrichment analyses of association results.Availability: RERconverge source code, documentation, and a detailed usage walk-through are freely available at https://github.com/nclark-lab/RERconverge. Datasets for mammals, Drosophila, and yeast are available at https://bit.ly/2J2QBnj.Contact:[email protected] information: Supplementary information, containing detailed vignettes for usage of RERconverge, are available at Bioinformatics online.

scholarly journals RERconverge: an R package for associating evolutionary rates with convergent traits

2019 ◽  
Vol 35 (22) ◽  
pp. 4815-4817 ◽  
Author(s):  
Amanda Kowalczyk ◽  
Wynn K Meyer ◽  
Raghavendran Partha ◽  
Weiguang Mao ◽  
Nathan L Clark ◽  
...  
Keyword(s):  
Molecular Basis ◽  
Evolutionary Rate ◽  
Source Code ◽  
R Package ◽  
Evolutionary Rates ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Genome Sequences ◽  
Convergent Rate ◽  
Tests For Association

Abstract Motivation When different lineages of organisms independently adapt to similar environments, selection often acts repeatedly upon the same genes, leading to signatures of convergent evolutionary rate shifts at these genes. With the increasing availability of genome sequences for organisms displaying a variety of convergent traits, the ability to identify genes with such convergent rate signatures would enable new insights into the molecular basis of these traits. Results Here we present the R package RERconverge, which tests for association between relative evolutionary rates of genes and the evolution of traits across a phylogeny. RERconverge can perform associations with binary and continuous traits, and it contains tools for visualization and enrichment analyses of association results. Availability and implementation RERconverge source code, documentation and a detailed usage walk-through are freely available at https://github.com/nclark-lab/RERconverge. Datasets for mammals, Drosophila and yeast are available at https://bit.ly/2J2QBnj. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals hypeR: An R Package for Geneset Enrichment Workflows

2019 ◽  
Author(s):  
Anthony Federico ◽  
Stefano Monti
Keyword(s):  
High Throughput Sequencing ◽  
R Package ◽  
Supplementary Information ◽  
Sequencing Data ◽  
Wide Audience ◽  
Popular Method ◽  
Link Type ◽  
High Throughput Sequencing Data ◽  
One Stop ◽  
Recent Version

ABSTRACTSummaryGeneset enrichment is a popular method for annotating high-throughput sequencing data. Existing tools fall short in providing the flexibility to tackle the varied challenges researchers face in such analyses, particularly when analyzing many signatures across multiple experiments. We present a comprehensive R package for geneset enrichment workflows that offers multiple enrichment, visualization, and sharing methods in addition to novel features such as hierarchical geneset analysis and built-in markdown reporting. hypeR is a one-stop solution to performing geneset enrichment for a wide audience and range of use cases.Availability and implementationThe most recent version of the package is available at https://github.com/montilab/hypeR.Supplementary informationComprehensive documentation and tutorials, are available at https://montilab.github.io/hypeR-docs.

scholarly journals GalaxyCloudRunner: enhancing scalable computing for Galaxy

2020 ◽  
Author(s):  
N Goonasekera ◽  
A Mahmoud ◽  
J Chilton ◽  
E Afgan
Keyword(s):  
Source Code ◽  
Supplementary Information ◽  
Scalable Computing ◽  
Link Type ◽  
Cloud Providers ◽  
Galaxy Server ◽  
Cloud Resources

AbstractSummaryThe existence of more than 100 public Galaxy servers with service quotas is indicative of the need for an increased availability of compute resources for Galaxy to use. The GalaxyCloudRunner enables a Galaxy server to easily expand its available compute capacity by sending user jobs to cloud resources. User jobs are routed to the acquired resources based on a set of configurable rules and the resources can be dynamically acquired from any of 4 popular cloud providers (AWS, Azure, GCP, or OpenStack) in an automated fashion.Availability and implementationGalaxyCloudRunner is implemented in Python and leverages Docker containers. The source code is MIT licensed and available at https://github.com/cloudve/galaxycloudrunner. The documentation is available at http://gcr.cloudve.org/.ContactEnis Afgan ([email protected])Supplementary informationNone

scholarly journals Temporal signal and the phylodynamic threshold of SARS-CoV-2

2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Sebastian Duchene ◽  
Leo Featherstone ◽  
Melina Haritopoulou-Sinanidou ◽  
Andrew Rambaut ◽  
Philippe Lemey ◽  
...  
Keyword(s):  
Time Scales ◽  
Sequence Variation ◽  
Evolutionary Rate ◽  
Sequence Data ◽  
Genomic Variation ◽  
Evolutionary Rates ◽  
Data Sets ◽  
Genome Sequences ◽  
First Time ◽  
Time Of Origin

Abstract The ongoing SARS-CoV-2 outbreak marks the first time that large amounts of genome sequence data have been generated and made publicly available in near real time. Early analyses of these data revealed low sequence variation, a finding that is consistent with a recently emerging outbreak, but which raises the question of whether such data are sufficiently informative for phylogenetic inferences of evolutionary rates and time scales. The phylodynamic threshold is a key concept that refers to the point in time at which sufficient molecular evolutionary change has accumulated in available genome samples to obtain robust phylodynamic estimates. For example, before the phylodynamic threshold is reached, genomic variation is so low that even large amounts of genome sequences may be insufficient to estimate the virus’s evolutionary rate and the time scale of an outbreak. We collected genome sequences of SARS-CoV-2 from public databases at eight different points in time and conducted a range of tests of temporal signal to determine if and when the phylodynamic threshold was reached, and the range of inferences that could be reliably drawn from these data. Our results indicate that by 2 February 2020, estimates of evolutionary rates and time scales had become possible. Analyses of subsequent data sets, that included between 47 and 122 genomes, converged at an evolutionary rate of about 1.1 × 10−3 subs/site/year and a time of origin of around late November 2019. Our study provides guidelines to assess the phylodynamic threshold and demonstrates that establishing this threshold constitutes a fundamental step for understanding the power and limitations of early data in outbreak genome surveillance.

scholarly journals blupADC: An R package and shiny toolkit for comprehensive genetic data analysis in animal and plant breeding

2021 ◽  
Author(s):  
Quanshun Mei ◽  
Chuanke Fu ◽  
Jieling Li ◽  
Shuhong Zhao ◽  
Tao Xiang
Keyword(s):  
Genetic Analysis ◽  
Plant Breeding ◽  
Genomic Data ◽  
R Package ◽  
Genotype Imputation ◽  
Supplementary Information ◽  
Composition Analysis ◽  
Relationship Matrix ◽  
Link Type ◽  
Plant Breeding Program

AbstractSummaryGenetic analysis is a systematic and complex procedure in animal and plant breeding. With fast development of high-throughput genotyping techniques and algorithms, animal and plant breeding has entered into a genomic era. However, there is a lack of software, which can be used to process comprehensive genetic analyses, in the routine animal and plant breeding program. To make the whole genetic analysis in animal and plant breeding straightforward, we developed a powerful, robust and fast R package that includes genomic data format conversion, genomic data quality control and genotype imputation, breed composition analysis, pedigree tracing, analysis and visualization, pedigree-based and genomic-based relationship matrix construction, and genomic evaluation. In addition, to simplify the application of this package, we also developed a shiny toolkit for users.Availability and implementationblupADC is developed primarily in R with core functions written in C++. The development version is maintained at https://github.com/TXiang-lab/blupADC.Supplementary informationSupplementary data are available online

scholarly journals Comparing complex variants in family trios

2018 ◽  
Author(s):  
Berke Ç. Toptaş ◽  
Goran Rakocevic ◽  
Péter Kómár ◽  
Deniz Kural
Keyword(s):  
Source Code ◽  
Supplementary Information ◽  
Analysis Tool ◽  
Matching Problem ◽  
Concordance Analysis ◽  
Link Type ◽  
Comparison Methods ◽  
Multiple Variants

AbstractMotivation: Several tools exist to count Mendelian violations in family trios by comparing variants at the same genomic positions. This naive variant comparison however, fails to assess regions where multiple variants need to be examined together, resulting in reduced accuracy of existing Mendelian violation checking tools.Results: We introduce VBT, a trio concordance analysis tool, that identifies Mendelian violations by approximately solving the 3-way variant matching problem to resolve variant representation differences in family trios. We show that VBT outperforms previous trio comparison methods by accuracy.Availability: VBT is implemented in C++ and source code is available under GNU GPLv3 license at the following URL: https://github.com/sbg/VBT-TrioAnalysis.gitContact:[email protected] information: Supplementary materials are available at Biorxiv.

scholarly journals gwasurvivr: an R package for genome wide survival analysis

2018 ◽  
Author(s):  
Abbas A Rizvi ◽  
Ezgi Karaesmen ◽  
Martin Morgan ◽  
Leah Preus ◽  
Junke Wang ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Cox Model ◽  
R Package ◽  
Supplementary Information ◽  
Parameter Estimates ◽  
Survival Analyses ◽  
Link Type ◽  
Genome Wide ◽  
Size Number ◽  
Simple Interface

ABSTRACTSummaryTo address the limited software options for performing survival analyses with millions of SNPs, we developed gwasurvivr, an R/Bioconductor package with a simple interface for conducting genome wide survival analyses using VCF (outputted from Michigan or Sanger imputation servers), IMPUTE2 or PLINK files. To decrease the number of iterations needed for convergence when optimizing the parameter estimates in the Cox model we modified the R package survival; covariates in the model are first fit without the SNP, and those parameter estimates are used as initial points. We benchmarked gwasurvivr with other software capable of conducting genome wide survival analysis (genipe, SurvivalGWAS_SV, and GWASTools). gwasurvivr is significantly faster and shows better scalability as sample size, number of SNPs and number of covariates increases.Availability and implementationgwasurvivr, including source code, documentation, and vignette are available at: http://bioconductor.org/packages/gwasurvivrContactAbbas Rizvi, [email protected]; Lara E Sucheston-Campbell, [email protected] information: Supplementary data are available at https://github.com/suchestoncampbelllab/gwasurvivr_manuscript

scholarly journals PhyloFold: Precise and Swift Prediction of RNA Secondary Structures to Incorporate Phylogeny among Homologs

2020 ◽  
Author(s):  
Masaki Tagashira
Keyword(s):  
Secondary Structure ◽  
Rna Secondary Structure ◽  
Prediction Accuracy ◽  
Structural Alignment ◽  
Source Code ◽  
Secondary Structures ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Link Type ◽  
Structural Alignments

AbstractMotivationThe simultaneous consideration of sequence alignment and RNA secondary structure, or structural alignment, is known to help predict more accurate secondary structures of homologs. However, the consideration is heavy and can be done only roughly to decompose structural alignments.ResultsThe PhyloFold method, which predicts secondary structures of homologs considering likely pairwise structural alignments, was developed in this study. The method shows the best prediction accuracy while demanding comparable running time compared to conventional methods.AvailabilityThe source code of the programs implemented in this study is available on “https://github.com/heartsh/phylofold” and “https://github.com/heartsh/phyloalifold“.Contact“[email protected]”.Supplementary informationSupplementary data are available.

scholarly journals NanoPack: visualizing and processing long read sequencing data

2017 ◽  
Author(s):  
Wouter De Coster ◽  
Svenn D’Hert ◽  
Darrin T. Schultz ◽  
Marc Cruts ◽  
Christine Van Broeckhoven
Keyword(s):  
Web Service ◽  
Graphical User Interface ◽  
Source Code ◽  
Supplementary Information ◽  
Command Line ◽  
Sequencing Data ◽  
Link Type ◽  
Oxford Nanopore ◽  
Long Read ◽  
Oxford Nanopore Technologies

AbstractSummary: Here we describe NanoPack, a set of tools developed for visualization and processing of long read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences.Availability and Implementation: The NanoPack tools are written in Python3 and released under the GNU GPL3.0 Licence. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.Contact:[email protected] information: Supplementary tables and figures are available at Bioinformatics online.

scholarly journals intansv: an R package for integrative analysis of structural variations

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e8867
Author(s):  
Lihua Jia ◽  
Na Liu ◽  
Fangfang Huang ◽  
Zhengfu Zhou ◽  
Xin He ◽  
...  
Keyword(s):  
Source Code ◽  
R Package ◽  
Integrative Analysis ◽  
Structural Variations ◽  
Link Type ◽  
Golden Standard

Identification of structural variations between individuals is very important for the understanding of phenotype variations and diseases. Despite the existence of dozens of programs for prediction of structural variations, none of them is the golden standard in this field and the results of multiple programs were usually integrated to get more reliable predictions. Annotation and visualization of structural variations are important for the understanding of their functions. However, no program provides these functions currently as far as we are concerned. We report an R package, intansv, which can integrate the predictions of multiple programs as well as annotate and visualize structural variations. The source code and the help manual of intansv is freely available at https://github.com/venyao/intansv and http://www.bioconductor.org/packages/devel/bioc/html/intansv.html.

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