scholarly journals MapOptics: a light-weight, cross-platform visualization tool for optical mapping alignment

2018 ◽  
Vol 35 (15) ◽  
pp. 2671-2673 ◽  
Author(s):  
Josephine Burgin ◽  
Corentin Molitor ◽  
Fady Mohareb
Keyword(s):  
Large Scale ◽  
Optical Mapping ◽  
Java Virtual Machine ◽  
Supplementary Information ◽  
Desktop Computer ◽  
Draft Assembly ◽  
Simple Alternative ◽  
Mapping Analysis ◽  
Cross Platform ◽  
Genomic Map

Abstract Summary Bionano optical mapping is a technology that can assist in the final stages of genome assembly by lengthening and ordering scaffolds in a draft assembly by aligning the assembly to a genomic map. However, currently, tools for visualization are limited to use on a Windows operating system or are developed initially for visualizing large-scale structural variation. MapOptics is a lightweight cross-platform tool that enables the user to visualize and interact with the alignment of Bionano optical mapping data and can be used for in depth exploration of hybrid scaffolding alignments. It provides a fast, simple alternative to the large optical mapping analysis programs currently available for this area of research. Availability and implementation MapOptics is implemented in Java 1.8 and released under an MIT licence. MapOptics can be downloaded from https://github.com/FadyMohareb/mapoptics and run on any standard desktop computer equipped with a Java Virtual Machine (JVM). Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Meta-Apo improves accuracy of 16S-amplicon-based prediction of microbiome function

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Gongchao Jing ◽  
Yufeng Zhang ◽  
Wenzhi Cui ◽  
Lu Liu ◽  
Jian Xu ◽  
...  
Keyword(s):  
16S Rrna ◽  
Large Scale ◽  
Low Cost ◽  
Human Microbiome ◽  
Amplicon Sequencing ◽  
Training Sample ◽  
Rrna Gene ◽  
16S Amplicon Sequencing ◽  
Cross Platform ◽  
Functional Profiles

Abstract Background Due to their much lower costs in experiment and computation than metagenomic whole-genome sequencing (WGS), 16S rRNA gene amplicons have been widely used for predicting the functional profiles of microbiome, via software tools such as PICRUSt 2. However, due to the potential PCR bias and gene profile variation among phylogenetically related genomes, functional profiles predicted from 16S amplicons may deviate from WGS-derived ones, resulting in misleading results. Results Here we present Meta-Apo, which greatly reduces or even eliminates such deviation, thus deduces much more consistent diversity patterns between the two approaches. Tests of Meta-Apo on > 5000 16S-rRNA amplicon human microbiome samples from 4 body sites showed the deviation between the two strategies is significantly reduced by using only 15 WGS-amplicon training sample pairs. Moreover, Meta-Apo enables cross-platform functional comparison between WGS and amplicon samples, thus greatly improve 16S-based microbiome diagnosis, e.g. accuracy of gingivitis diagnosis via 16S-derived functional profiles was elevated from 65 to 95% by WGS-based classification. Therefore, with the low cost of 16S-amplicon sequencing, Meta-Apo can produce a reliable, high-resolution view of microbiome function equivalent to that offered by shotgun WGS. Conclusions This suggests that large-scale, function-oriented microbiome sequencing projects can probably benefit from the lower cost of 16S-amplicon strategy, without sacrificing the precision in functional reconstruction that otherwise requires WGS. An optimized C++ implementation of Meta-Apo is available on GitHub (https://github.com/qibebt-bioinfo/meta-apo) under a GNU GPL license. It takes the functional profiles of a few paired WGS:16S-amplicon samples as training, and outputs the calibrated functional profiles for the much larger number of 16S-amplicon samples.

scholarly journals Personalized medicine for reconstruction of critical-size bone defects – a translational approach with customizable vascularized bone tissue

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Annika Kengelbach-Weigand ◽  
Carolina Thielen ◽  
Tobias Bäuerle ◽  
Rebekka Götzl ◽  
Thomas Gerber ◽  
...  
Keyword(s):  
Personalized Medicine ◽  
Large Scale ◽  
Critical Size ◽  
Therapeutic Option ◽  
Living Organism ◽  
Bone Defects ◽  
Sheep Model ◽  
Simple Alternative ◽  
Translational Approach ◽  
Near Future

AbstractTissue engineering principles allow the generation of functional tissues for biomedical applications. Reconstruction of large-scale bone defects with tissue-engineered bone has still not entered the clinical routine. In the present study, a bone substitute in combination with mesenchymal stem cells (MSC) and endothelial progenitor cells (EPC) with or without growth factors BMP-2 and VEGF-A was prevascularized by an arteriovenous (AV) loop and transplanted into a critical-size tibia defect in the sheep model. With 3D imaging and immunohistochemistry, we could show that this approach is a feasible and simple alternative to the current clinical therapeutic option. This study serves as proof of concept for using large-scale transplantable, vascularized, and customizable bone, generated in a living organism for the reconstruction of load-bearing bone defects, individually tailored to the patient’s needs. With this approach in personalized medicine for the reconstruction of critical-size bone defects, regeneration of parts of the human body will become possible in the near future.

scholarly journals TreeMerge: a new method for improving the scalability of species tree estimation methods

2019 ◽  
Vol 35 (14) ◽  
pp. i417-i426 ◽  
Author(s):  
Erin K Molloy ◽  
Tandy Warnow
Keyword(s):  
Large Scale ◽  
Species Tree ◽  
New Method ◽  
Divide And Conquer ◽  
Supplementary Information ◽  
Estimation Methods ◽  
Running Time ◽  
Tree Estimation ◽  
Computationally Intensive ◽  
A Minor

Abstract Motivation At RECOMB-CG 2018, we presented NJMerge and showed that it could be used within a divide-and-conquer framework to scale computationally intensive methods for species tree estimation to larger datasets. However, NJMerge has two significant limitations: it can fail to return a tree and, when used within the proposed divide-and-conquer framework, has O(n5) running time for datasets with n species. Results Here we present a new method called ‘TreeMerge’ that improves on NJMerge in two ways: it is guaranteed to return a tree and it has dramatically faster running time within the same divide-and-conquer framework—only O(n2) time. We use a simulation study to evaluate TreeMerge in the context of multi-locus species tree estimation with two leading methods, ASTRAL-III and RAxML. We find that the divide-and-conquer framework using TreeMerge has a minor impact on species tree accuracy, dramatically reduces running time, and enables both ASTRAL-III and RAxML to complete on datasets (that they would otherwise fail on), when given 64 GB of memory and 48 h maximum running time. Thus, TreeMerge is a step toward a larger vision of enabling researchers with limited computational resources to perform large-scale species tree estimation, which we call Phylogenomics for All. Availability and implementation TreeMerge is publicly available on Github (http://github.com/ekmolloy/treemerge). Supplementary information Supplementary data are available at Bioinformatics online.

EARRINGS: an efficient and accurate adapter trimmer entails no a priori adapter sequences

2021 ◽  
Author(s):  
Ting-Hsuan Wang ◽  
Cheng-Ching Huang ◽  
Jui-Hung Hung
Keyword(s):  
Open Source Software ◽  
Large Scale ◽  
A Priori ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Comparable Accuracy ◽  
Meta Analyses ◽  
Next Generation Sequencing Ngs ◽  
Adapter Trimming ◽  
Generation Sequencing

Abstract Motivation Cross-sample comparisons or large-scale meta-analyses based on the next generation sequencing (NGS) involve replicable and universal data preprocessing, including removing adapter fragments in contaminated reads (i.e. adapter trimming). While modern adapter trimmers require users to provide candidate adapter sequences for each sample, which are sometimes unavailable or falsely documented in the repositories (such as GEO or SRA), large-scale meta-analyses are therefore jeopardized by suboptimal adapter trimming. Results Here we introduce a set of fast and accurate adapter detection and trimming algorithms that entail no a priori adapter sequences. These algorithms were implemented in modern C++ with SIMD and multithreading to accelerate its speed. Our experiments and benchmarks show that the implementation (i.e. EARRINGS), without being given any hint of adapter sequences, can reach comparable accuracy and higher throughput than that of existing adapter trimmers. EARRINGS is particularly useful in meta-analyses of a large batch of datasets and can be incorporated in any sequence analysis pipelines in all scales. Availability and implementation EARRINGS is open-source software and is available at https://github.com/jhhung/EARRINGS. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals TADOSS: computational estimation of tandem domain swap stability

2018 ◽  
Vol 35 (14) ◽  
pp. 2507-2508 ◽  
Author(s):  
Aleix Lafita ◽  
Pengfei Tian ◽  
Robert B Best ◽  
Alex Bateman
Keyword(s):  
Large Scale ◽  
Domain Swapping ◽  
Coarse Grained ◽  
Supplementary Information ◽  
Simulation Studies ◽  
Computational Tools ◽  
Domain Swap ◽  
Computational Estimation ◽  
High Propensity ◽  
The Stability

Abstract Summary Proteins with highly similar tandem domains have shown an increased propensity for misfolding and aggregation. Several molecular explanations have been put forward, such as swapping of adjacent domains, but there is a lack of computational tools to systematically analyze them. We present the TAndem DOmain Swap Stability predictor (TADOSS), a method to computationally estimate the stability of tandem domain-swapped conformations from the structures of single domains, based on previous coarse-grained simulation studies. The tool is able to discriminate domains susceptible to domain swapping and to identify structural regions with high propensity to form hinge loops. TADOSS is a scalable method and suitable for large scale analyses. Availability and implementation Source code and documentation are freely available under an MIT license on GitHub at https://github.com/lafita/tadoss. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals GWASpro: a high-performance genome-wide association analysis server

2018 ◽  
Vol 35 (14) ◽  
pp. 2512-2514 ◽  
Author(s):  
Bongsong Kim ◽  
Xinbin Dai ◽  
Wenchao Zhang ◽  
Zhaohong Zhuang ◽  
Darlene L Sanchez ◽  
...  
Keyword(s):  
High Performance ◽  
Large Scale ◽  
Linear Mixed Model ◽  
Association Studies ◽  
Learning Curves ◽  
Experimental Designs ◽  
Genome Wide Association ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Genome Wide

Abstract Summary We present GWASpro, a high-performance web server for the analyses of large-scale genome-wide association studies (GWAS). GWASpro was developed to provide data analyses for large-scale molecular genetic data, coupled with complex replicated experimental designs such as found in plant science investigations and to overcome the steep learning curves of existing GWAS software tools. GWASpro supports building complex design matrices, by which complex experimental designs that may include replications, treatments, locations and times, can be accounted for in the linear mixed model. GWASpro is optimized to handle GWAS data that may consist of up to 10 million markers and 10 000 samples from replicable lines or hybrids. GWASpro provides an interface that significantly reduces the learning curve for new GWAS investigators. Availability and implementation GWASpro is freely available at https://bioinfo.noble.org/GWASPRO. Supplementary information Supplementary data are available at Bioinformatics online.

Study on Temperature Distribution of Pebble-Bed HTR Fuel Element by Using Boundary Element Method

2013 ◽  
Author(s):  
Haitao Wang ◽  
Xin Wang
Keyword(s):  
Fuel Element ◽  
Boundary Element ◽  
Large Scale ◽  
Maximum Temperature ◽  
Element Formulation ◽  
Desktop Computer ◽  
Pebble Bed ◽  
Graphite Matrix ◽  
Fuel Particles ◽  
Fuel Elements

Spherical fuel elements with a diameter of 60mm are basic units of the nuclear fuel for the pebble-bed high temperature gas-cooled reactor (HTR). Each fuel element is treated as a graphite matrix containing around 10,000 randomly distributed fuel particles. The essential safety concept of the pebble-bed HTR is based on the objective that maximum temperature of the fuel particles does not exceed the design value. In this paper, a microstructure-based boundary element model is proposed for the large-scale thermal analysis of a spherical fuel element. This model presents detailed structural information of a large number of coated fuel particles dispersed in a spherical graphite matrix in order that temperature distributions at the level of fuel particles can be evaluated. The model is meshed with boundary elements in conjunction with the fast multipole method (FMM) in order that such large-scale computation is performed only in a personal desktop computer. Taking advantage of the fact that fuel particles are of the same shape, a similar sub-domain approach is used to establish the temperature translation mechanism between various layers of each fuel particle and to simplify the associated boundary element formulation. The numerical results demonstrate large-scale capacity of the proposed method for the multi-level temperature evaluation of the pebble-bed HTR fuel elements.

scholarly journals Global sequence characterization of rice centromeric satellite based on oligomer frequency analysis in large-scale sequencing data

2010 ◽  
Vol 26 (17) ◽  
pp. 2101-2108 ◽  
Author(s):  
Jiří Macas ◽  
Pavel Neumann ◽  
Petr Novák ◽  
Jiming Jiang
Keyword(s):  
Large Scale ◽  
Rice Genome ◽  
Supplementary Information ◽  
Sequencing Data ◽  
Satellite Repeat ◽  
Frequency Spectra ◽  
Consensus Sequences ◽  
Chip Sequencing ◽  
Conserved Sequence ◽  
Centromeric Satellite

Abstract Motivation: Satellite DNA makes up significant portion of many eukaryotic genomes, yet it is relatively poorly characterized even in extensively sequenced species. This is, in part, due to methodological limitations of traditional methods of satellite repeat analysis, which are based on multiple alignments of monomer sequences. Therefore, we employed an alternative, alignment-free, approach utilizing k-mer frequency statistics, which is in principle more suitable for analyzing large sets of satellite repeat data, including sequence reads from next generation sequencing technologies. Results: k-mer frequency spectra were determined for two sets of rice centromeric satellite CentO sequences, including 454 reads from ChIP-sequencing of CENH3-bound DNA (7.6 Mb) and the whole genome Sanger sequencing reads (5.8 Mb). k-mer frequencies were used to identify the most conserved sequence regions and to reconstruct consensus sequences of complete monomers. Reconstructed consensus sequences as well as the assessment of overall divergence of k-mer spectra revealed high similarity of the two datasets, suggesting that CentO sequences associated with functional centromeres (CENH3-bound) do not significantly differ from the total population of CentO, which includes both centromeric and pericentromeric repeat arrays. On the other hand, considerable differences were revealed when these methods were used for comparison of CentO populations between individual chromosomes of the rice genome assembly, demonstrating preferential sequence homogenization of the clusters within the same chromosome. k-mer frequencies were also successfully used to identify and characterize smRNAs derived from CentO repeats. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

scholarly journals DeepMAsED: evaluating the quality of metagenomic assemblies

2020 ◽  
Vol 36 (10) ◽  
pp. 3011-3017 ◽  
Author(s):  
Olga Mineeva ◽  
Mateo Rojas-Carulla ◽  
Ruth E Ley ◽  
Bernhard Schölkopf ◽  
Nicholas D Youngblut
Keyword(s):  
Large Scale ◽  
State Of The Art ◽  
Ground Truth ◽  
Supplementary Information ◽  
Learning Approach ◽  
Wide Range ◽  
Metagenome Assembly ◽  
Model Training ◽  
Reference Genomes

Abstract Motivation Methodological advances in metagenome assembly are rapidly increasing in the number of published metagenome assemblies. However, identifying misassemblies is challenging due to a lack of closely related reference genomes that can act as pseudo ground truth. Existing reference-free methods are no longer maintained, can make strong assumptions that may not hold across a diversity of research projects, and have not been validated on large-scale metagenome assemblies. Results We present DeepMAsED, a deep learning approach for identifying misassembled contigs without the need for reference genomes. Moreover, we provide an in silico pipeline for generating large-scale, realistic metagenome assemblies for comprehensive model training and testing. DeepMAsED accuracy substantially exceeds the state-of-the-art when applied to large and complex metagenome assemblies. Our model estimates a 1% contig misassembly rate in two recent large-scale metagenome assembly publications. Conclusions DeepMAsED accurately identifies misassemblies in metagenome-assembled contigs from a broad diversity of bacteria and archaea without the need for reference genomes or strong modeling assumptions. Running DeepMAsED is straight-forward, as well as is model re-training with our dataset generation pipeline. Therefore, DeepMAsED is a flexible misassembly classifier that can be applied to a wide range of metagenome assembly projects. Availability and implementation DeepMAsED is available from GitHub at https://github.com/leylabmpi/DeepMAsED. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals tHapMix: simulating tumour samples through haplotype mixtures

2016 ◽  
Author(s):  
Sergii Ivakhno ◽  
Camilla Colombo ◽  
Stephen Tanner ◽  
Philip Tedder ◽  
Stefano Berri ◽  
...  
Keyword(s):  
Copy Number ◽  
Large Scale ◽  
Variant Calling ◽  
Copy Number Variant ◽  
Supplementary Information ◽  
Genome Diversity ◽  
Simulation Framework ◽  
Somatic Genome ◽  
Copy Number Changes ◽  
Sequencing Platforms

AbstractMotivationLarge-scale rearrangements and copy number changes combined with different modes of cloevolution create extensive somatic genome diversity, making it difficult to develop versatile and scalable oriant calling tools and create well-calibrated benchmarks.ResultsWe developed a new simulation framework tHapMix that enables the creation of tumour samples with different ploidy, purity and polyclonality features. It easily scales to simulation of hundreds of somatic genomes, while re-use of real read data preserves noise and biases present in sequencing platforms. We further demonstrate tHapMix utility by creating a simulated set of 140 somatic genomes and showing how it can be used in training and testing of somatic copy number variant calling tools.Availability and implementationtHapMix is distributed under an open source license and can be downloaded from https://github.com/Illumina/[email protected] informationSupplementary data are available at Bioinformatics online.

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