scholarly journals mixtureS: a novel tool for bacterial strain genome reconstruction from reads

2020 ◽  
Author(s):  
Xin Li ◽  
Haiyan Hu ◽  
Xiaoman Li
Keyword(s):  
Environmental Samples ◽  
De Novo ◽  
Source Code ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Bacterial Strains ◽  
Metagenomic Sample ◽  
Almost All ◽  
User Friendly ◽  
Strain Genome

Abstract Motivation It is essential to study bacterial strains in environmental samples. Existing methods and tools often depend on known strains or known variations, cannot work on individual samples, not reliable, or not easy to use, etc. It is thus important to develop more user-friendly tools that can identify bacterial strains more accurately. Results We developed a new tool called mixtureS that can de novo identify bacterial strains from shotgun reads of a clonal or metagenomic sample, without prior knowledge about the strains and their variations. Tested on 243 simulated datasets and 195 experimental datasets, mixtureS reliably identified the strains, their numbers and their abundance. Compared with three tools, mixtureS showed better performance in almost all simulated datasets and the vast majority of experimental datasets. Availability and implementation The source code and tool mixtureS is available at http://www.cs.ucf.edu/˜xiaoman/mixtureS/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Temporal network alignment via GoT-WAVE

2019 ◽  
Vol 35 (18) ◽  
pp. 3527-3529 ◽  
Author(s):  
David Aparício ◽  
Pedro Ribeiro ◽  
Tijana Milenković ◽  
Fernando Silva
Keyword(s):  
User Interface ◽  
State Of The Art ◽  
Source Code ◽  
Network Alignment ◽  
Supplementary Information ◽  
Temporal Network ◽  
Temporal Networks ◽  
Supplementary Data ◽  
Node Similarity ◽  
User Friendly

Abstract Motivation Network alignment (NA) finds conserved regions between two networks. NA methods optimize node conservation (NC) and edge conservation. Dynamic graphlet degree vectors are a state-of-the-art dynamic NC measure, used within the fastest and most accurate NA method for temporal networks: DynaWAVE. Here, we use graphlet-orbit transitions (GoTs), a different graphlet-based measure of temporal node similarity, as a new dynamic NC measure within DynaWAVE, resulting in GoT-WAVE. Results On synthetic networks, GoT-WAVE improves DynaWAVE’s accuracy by 30% and speed by 64%. On real networks, when optimizing only dynamic NC, the methods are complementary. Furthermore, only GoT-WAVE supports directed edges. Hence, GoT-WAVE is a promising new temporal NA algorithm, which efficiently optimizes dynamic NC. We provide a user-friendly user interface and source code for GoT-WAVE. Availability and implementation http://www.dcc.fc.up.pt/got-wave/ Supplementary information Supplementary data are available at Bioinformatics online.

KEC: unique sequence search by K-mer exclusion

2021 ◽  
Author(s):  
Pavel Beran ◽  
Dagmar Stehlíková ◽  
Stephen P Cohen ◽  
Vladislav Čurn
Keyword(s):  
Amino Acid ◽  
Nucleic Acid ◽  
Source Code ◽  
Unique Sequence ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Laptop Computers ◽  
Sequence Search ◽  
Target Sequences ◽  
Cross Reference

Abstract Summary Searching for amino acid or nucleic acid sequences unique to one organism may be challenging depending on size of the available datasets. K-mer elimination by cross-reference (KEC) allows users to quickly and easily find unique sequences by providing target and non-target sequences. Due to its speed, it can be used for datasets of genomic size and can be run on desktop or laptop computers with modest specifications. Availability and implementation KEC is freely available for non-commercial purposes. Source code and executable binary files compiled for Linux, Mac and Windows can be downloaded from https://github.com/berybox/KEC. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals BioCommons: a robust java library for RNA structural bioinformatics

2021 ◽  
Author(s):  
Tomasz Zok
Keyword(s):  
Source Code ◽  
Structural Bioinformatics ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Bioinformatic Tools ◽  
Data Formats ◽  
Central Repository ◽  
Diverse Data ◽  
2D And 3D ◽  
Java Library

Abstract Motivation Biomolecular structures come in multiple representations and diverse data formats. Their incompatibility with the requirements of data analysis programs significantly hinders the analytics and the creation of new structure-oriented bioinformatic tools. Therefore, the need for robust libraries of data processing functions is still growing. Results BioCommons is an open-source, Java library for structural bioinformatics. It contains many functions working with the 2D and 3D structures of biomolecules, with a particular emphasis on RNA. Availability and implementation The library is available in Maven Central Repository and its source code is hosted on GitHub: https://github.com/tzok/BioCommons Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals SVIM-asm: Structural variant detection from haploid and diploid genome assemblies

2020 ◽  
Author(s):  
David Heller ◽  
Martin Vingron
Keyword(s):  
Genetic Information ◽  
Source Code ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Diploid Genome ◽  
Insertions And Deletions ◽  
Structural Variant ◽  
Sequencing Technologies ◽  
Variant Detection ◽  
Genome Assemblies

AbstractMotivationWith the availability of new sequencing technologies, the generation of haplotype-resolved genome assemblies up to chromosome scale has become feasible. These assemblies capture the complete genetic information of both parental haplotypes, increase structural variant (SV) calling sensitivity and enable direct genotyping and phasing of SVs. Yet, existing SV callers are designed for haploid genome assemblies only, do not support genotyping or detect only a limited set of SV classes.ResultsWe introduce our method SVIM-asm for the detection and genotyping of six common classes of SVs from haploid and diploid genome assemblies. Compared against the only other existing SV caller for diploid assemblies, DipCall, SVIM-asm detects more SV classes and reached higher F1 scores for the detection of insertions and deletions on two recently published assemblies of the HG002 individual.Availability and ImplementationSVIM-asm has been implemented in Python and can be easily installed via bioconda. Its source code is available at github.com/eldariont/[email protected] informationSupplementary data are available online.

scholarly journals ExpansionHunter: a sequence-graph-based tool to analyze variation in short tandem repeat regions

2019 ◽  
Vol 35 (22) ◽  
pp. 4754-4756 ◽  
Author(s):  
Egor Dolzhenko ◽  
Viraj Deshpande ◽  
Felix Schlesinger ◽  
Peter Krusche ◽  
Roman Petrovski ◽  
...  
Keyword(s):  
Tandem Repeat ◽  
Broad Class ◽  
Source Code ◽  
Computational Method ◽  
Supplementary Information ◽  
Dna Repeats ◽  
Supplementary Data ◽  
Sequence Graph ◽  
Version 2.0 ◽  
Short Tandem

Abstract Summary We describe a novel computational method for genotyping repeats using sequence graphs. This method addresses the long-standing need to accurately genotype medically important loci containing repeats adjacent to other variants or imperfect DNA repeats such as polyalanine repeats. Here we introduce a new version of our repeat genotyping software, ExpansionHunter, that uses this method to perform targeted genotyping of a broad class of such loci. Availability and implementation ExpansionHunter is implemented in C++ and is available under the Apache License Version 2.0. The source code, documentation, and Linux/macOS binaries are available at https://github.com/Illumina/ExpansionHunter/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals LIONS: analysis suite for detecting and quantifying transposable element initiated transcription from RNA-seq

2019 ◽  
Vol 35 (19) ◽  
pp. 3839-3841 ◽  
Author(s):  
Artem Babaian ◽  
I Richard Thompson ◽  
Jake Lever ◽  
Liane Gagnier ◽  
Mohammad M Karimi ◽  
...  
Keyword(s):  
Transposable Elements ◽  
Transposable Element ◽  
Test Data ◽  
Source Code ◽  
Supplementary Information ◽  
Transcriptional Networks ◽  
Supplementary Data ◽  
Rna Seq ◽  
Transcriptional Initiation ◽  
Instruction Manual

Abstract Summary Transposable elements (TEs) influence the evolution of novel transcriptional networks yet the specific and meaningful interpretation of how TE-derived transcriptional initiation contributes to the transcriptome has been marred by computational and methodological deficiencies. We developed LIONS for the analysis of RNA-seq data to specifically detect and quantify TE-initiated transcripts. Availability and implementation Source code, container, test data and instruction manual are freely available at www.github.com/ababaian/LIONS. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals OpenBioLink: a benchmarking framework for large-scale biomedical link prediction

2020 ◽  
Vol 36 (13) ◽  
pp. 4097-4098 ◽  
Author(s):  
Anna Breit ◽  
Simon Ott ◽  
Asan Agibetov ◽  
Matthias Samwald
Keyword(s):  
Link Prediction ◽  
Large Scale ◽  
Source Code ◽  
Machine Learning Algorithms ◽  
Knowledge Networks ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Biomedical Knowledge ◽  
High Quality ◽  
Baseline Evaluation

Abstract Summary Recently, novel machine-learning algorithms have shown potential for predicting undiscovered links in biomedical knowledge networks. However, dedicated benchmarks for measuring algorithmic progress have not yet emerged. With OpenBioLink, we introduce a large-scale, high-quality and highly challenging biomedical link prediction benchmark to transparently and reproducibly evaluate such algorithms. Furthermore, we present preliminary baseline evaluation results. Availability and implementation Source code and data are openly available at https://github.com/OpenBioLink/OpenBioLink. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals YeastSpotter: accurate and parameter-free web segmentation for microscopy images of yeast cells

2019 ◽  
Vol 35 (21) ◽  
pp. 4525-4527 ◽  
Author(s):  
Alex X Lu ◽  
Taraneh Zarin ◽  
Ian S Hsu ◽  
Alan M Moses
Keyword(s):  
Image Analysis ◽  
Web Application ◽  
Single Cells ◽  
Yeast Cells ◽  
Supplementary Information ◽  
Supplementary Data ◽  
User Friendly ◽  
Microscopy Images

Abstract Summary We introduce YeastSpotter, a web application for the segmentation of yeast microscopy images into single cells. YeastSpotter is user-friendly and generalizable, reducing the computational expertise required for this critical preprocessing step in many image analysis pipelines. Availability and implementation YeastSpotter is available at http://yeastspotter.csb.utoronto.ca/. Code is available at https://github.com/alexxijielu/yeast_segmentation. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals DiscoRhythm: an easy-to-use web application and R package for discovering rhythmicity

2019 ◽  
Author(s):  
Matthew Carlucci ◽  
Algimantas Kriščiūnas ◽  
Haohan Li ◽  
Povilas Gibas ◽  
Karolis Koncevičius ◽  
...  
Keyword(s):  
Web Application ◽  
Statistical Significance ◽  
R Package ◽  
Biological Data ◽  
Supplementary Information ◽  
Statistical Knowledge ◽  
Health And Disease ◽  
Phase Amplitude ◽  
Almost All ◽  
User Friendly

Abstract Motivation Biological rhythmicity is fundamental to almost all organisms on Earth and plays a key role in health and disease. Identification of oscillating signals could lead to novel biological insights, yet its investigation is impeded by the extensive computational and statistical knowledge required to perform such analysis. Results To address this issue, we present DiscoRhythm (Discovering Rhythmicity), a user-friendly application for characterizing rhythmicity in temporal biological data. DiscoRhythm is available as a web application or an R/Bioconductor package for estimating phase, amplitude, and statistical significance using four popular approaches to rhythm detection (Cosinor, JTK Cycle, ARSER, and Lomb-Scargle). We optimized these algorithms for speed, improving their execution times up to 30-fold to enable rapid analysis of -omic-scale datasets in real-time. Informative visualizations, interactive modules for quality control, dimensionality reduction, periodicity profiling, and incorporation of experimental replicates make DiscoRhythm a thorough toolkit for analyzing rhythmicity. Availability and Implementation The DiscoRhythm R package is available on Bioconductor (https://bioconductor.org/packages/DiscoRhythm), with source code available on GitHub (https://github.com/matthewcarlucci/DiscoRhythm) under a GPL-3 license. The web application is securely deployed over HTTPS (https://disco.camh.ca) and is freely available for use worldwide. Local instances of the DiscoRhythm web application can be created using the R package or by deploying the publicly available Docker container (https://hub.docker.com/r/mcarlucci/discorhythm). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Capybara: equivalence ClAss enumeration of coPhylogenY event-BAsed ReconciliAtions

2020 ◽  
Vol 36 (14) ◽  
pp. 4197-4199
Author(s):  
Yishu Wang ◽  
Arnaud Mary ◽  
Marie-France Sagot ◽  
Blerina Sinaimeri
Keyword(s):  
Source Code ◽  
Supplementary Information ◽  
Optimal Solutions ◽  
Supplementary Data ◽  
Huge Number ◽  
Tree Reconciliation ◽  
Class Enumeration ◽  
Suboptimal Solutions ◽  
The Many ◽  
Event Based

Abstract Motivation Phylogenetic tree reconciliation is the method of choice in analyzing host-symbiont systems. Despite the many reconciliation tools that have been proposed in the literature, two main issues remain unresolved: (i) listing suboptimal solutions (i.e. whose score is ‘close’ to the optimal ones) and (ii) listing only solutions that are biologically different ‘enough’. The first issue arises because the optimal solutions are not always the ones biologically most significant; providing many suboptimal solutions as alternatives for the optimal ones is thus very useful. The second one is related to the difficulty to analyze an often huge number of optimal solutions. In this article, we propose Capybara that addresses both of these problems in an efficient way. Furthermore, it includes a tool for visualizing the solutions that significantly helps the user in the process of analyzing the results. Availability and implementation The source code, documentation and binaries for all platforms are freely available at https://capybara-doc.readthedocs.io/. Contact [email protected] or [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

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