scholarly journals LRez: C ++ API and toolkit for analyzing and managing Linked-Reads data

2021 ◽  
Author(s):  
Pierre Morisse ◽  
Claire Lemaitre ◽  
Fabrice Legeai
Keyword(s):  
Genome Assembly ◽  
Low Cost ◽  
Variant Calling ◽  
Supplementary Information ◽  
Supplementary Data ◽  
High Quality ◽  
Dna Molecule ◽  
Sequencing Technologies ◽  
Wide Range ◽  
Genomic Regions

Abstract Motivation Linked-Reads technologies combine both the high-quality and low cost of short-reads sequencing and long-range information, through the use of barcodes tagging reads which originate from a common long DNA molecule. This technology has been employed in a broad range of applications including genome assembly, phasing and scaffolding, as well as structural variant calling. However, to date, no tool or API dedicated to the manipulation of Linked-Reads data exist. Results We introduce LRez, a C ++ API and toolkit which allows easy management of Linked-Reads data. LRez includes various functionalities, for computing numbers of common barcodes between genomic regions, extracting barcodes from BAM files, as well as indexing and querying BAM, FASTQ and gzipped FASTQ files to quickly fetch all reads or alignments containing a given barcode. LRez is compatible with a wide range of Linked-Reads sequencing technologies, and can thus be used in any tool or pipeline requiring barcode processing or indexing, in order to improve their performances. Availability and implementation LRez is implemented in C ++, supported on Unix-based platforms, and available under AGPL-3.0 License at https://github.com/morispi/LRez, and as a bioconda module. Supplementary information Supplementary data are available at Bioinformatics Advances

scholarly journals Efficient long single molecule sequencing for cost effective and accurate sequencing, haplotyping, and de novo assembly

2018 ◽  
Author(s):  
Ou Wang ◽  
Robert Chin ◽  
Xiaofang Cheng ◽  
Michelle Ka Wu ◽  
Qing Mao ◽  
...  
Keyword(s):  
Single Molecule ◽  
Genome Assembly ◽  
De Novo ◽  
Low Cost ◽  
Variant Calling ◽  
Cost Effective ◽  
High Quality ◽  
Single Molecule Sequencing ◽  
Single Tube ◽  
Complex Structural

Obtaining accurate sequences from long DNA molecules is very important for genome assembly and other applications. Here we describe single tube long fragment read (stLFR), a technology that enables this a low cost. It is based on adding the same barcode sequence to sub-fragments of the original long DNA molecule (DNA co-barcoding). To achieve this efficiently, stLFR uses the surface of microbeads to create millions of miniaturized barcoding reactions in a single tube. Using a combinatorial process up to 3.6 billion unique barcode sequences were generated on beads, enabling practically non-redundant co-barcoding with 50 million barcodes per sample. Using stLFR, we demonstrate efficient unique co-barcoding of over 8 million 20-300 kb genomic DNA fragments. Analysis of the genome of the human genome NA12878 with stLFR demonstrated high quality variant calling and phasing into contigs up to N50 34 Mb. We also demonstrate detection of complex structural variants and complete diploid de novo assembly of NA12878. These analyses were all performed using single stLFR libraries and their construction did not significantly add to the time or cost of whole genome sequencing (WGS) library preparation. stLFR represents an easily automatable solution that enables high quality sequencing, phasing, SV detection, scaffolding, cost-effective diploid de novo genome assembly, and other long DNA sequencing applications.

scholarly journals PgRC: pseudogenome-based read compressor

2019 ◽  
Vol 36 (7) ◽  
pp. 2082-2089 ◽  
Author(s):  
Tomasz M Kowalski ◽  
Szymon Grabowski
Keyword(s):  
Compression Ratio ◽  
High Throughput Sequencing ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Sequencing Data ◽  
High Quality ◽  
Sequencing Technologies ◽  
Significant Interest ◽  
The One ◽  
Shortest Common Superstring

Abstract Motivation The amount of sequencing data from high-throughput sequencing technologies grows at a pace exceeding the one predicted by Moore’s law. One of the basic requirements is to efficiently store and transmit such huge collections of data. Despite significant interest in designing FASTQ compressors, they are still imperfect in terms of compression ratio or decompression resources. Results We present Pseudogenome-based Read Compressor (PgRC), an in-memory algorithm for compressing the DNA stream, based on the idea of building an approximation of the shortest common superstring over high-quality reads. Experiments show that PgRC wins in compression ratio over its main competitors, SPRING and Minicom, by up to 15 and 20% on average, respectively, while being comparably fast in decompression. Availability and implementation PgRC can be downloaded from https://github.com/kowallus/PgRC. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Epidemiological modeling in StochSS Live!

2021 ◽  
Author(s):  
Richard Jiang ◽  
Bruno Jacob ◽  
Matthew Geiger ◽  
Sean Matthew ◽  
Bryan Rumsey ◽  
...  
Keyword(s):  
Stochastic Model ◽  
Epidemiological Model ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Web Based ◽  
Epidemiological Modeling ◽  
Modeling Simulation ◽  
Wide Range ◽  
Biochemical Systems

Abstract Summary We present StochSS Live!, a web-based service for modeling, simulation and analysis of a wide range of mathematical, biological and biochemical systems. Using an epidemiological model of COVID-19, we demonstrate the power of StochSS Live! to enable researchers to quickly develop a deterministic or a discrete stochastic model, infer its parameters and analyze the results. Availability and implementation StochSS Live! is freely available at https://live.stochss.org/ Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Identifying the causes and consequences of assembly gaps using a multiplatform genome assembly of a bird-of-paradise

2019 ◽  
Author(s):  
Valentina Peona ◽  
Mozes P.K. Blom ◽  
Luohao Xu ◽  
Reto Burri ◽  
Shawn Sullivan ◽  
...  
Keyword(s):  
Dark Matter ◽  
Genome Assembly ◽  
Sex Chromosome ◽  
De Novo ◽  
Model Organism ◽  
Technology Choice ◽  
High Quality ◽  
Sequencing Technologies ◽  
Downstream Analysis ◽  
Genome Assemblies

AbstractGenome assemblies are currently being produced at an impressive rate by consortia and individual laboratories. The low costs and increasing efficiency of sequencing technologies have opened up a whole new world of genomic biodiversity. Although these technologies generate high-quality genome assemblies, there are still genomic regions difficult to assemble, like repetitive elements and GC-rich regions (genomic “dark matter”). In this study, we compare the efficiency of currently used sequencing technologies (short/linked/long reads and proximity ligation maps) and combinations thereof in assembling genomic dark matter starting from the same sample. By adopting different de-novo assembly strategies, we were able to compare each individual draft assembly to a curated multiplatform one and identify the nature of the previously missing dark matter with a particular focus on transposable elements, multi-copy MHC genes, and GC-rich regions. Thanks to this multiplatform approach, we demonstrate the feasibility of producing a high-quality chromosome-level assembly for a non-model organism (paradise crow) for which only suboptimal samples are available. Our approach was able to reconstruct complex chromosomes like the repeat-rich W sex chromosome and several GC-rich microchromosomes. Telomere-to-telomere assemblies are not a reality yet for most organisms, but by leveraging technology choice it is possible to minimize genome assembly gaps for downstream analysis. We provide a roadmap to tailor sequencing projects around the completeness of both the coding and non-coding parts of the genomes.

scholarly journals Genome Assembly and Population Resequencing Reveal the Geographical Divergence of 'Shanmei'(Rubus corchorifolius)

2021 ◽  
Author(s):  
Yinqing Yang ◽  
Kang Zhang ◽  
Ya Xiao ◽  
Lingkui Zhang ◽  
Yile Huang ◽  
...  
Keyword(s):  
Genome Assembly ◽  
Ancestral Population ◽  
Effective Population ◽  
High Quality ◽  
Local Environments ◽  
Rubus Species ◽  
Rubus Chingii ◽  
Rubus Chingii Hu ◽  
Genomic Regions ◽  
High Quality Genome

Rubus corchorifolius (Shanmei or mountain berry, 2n =14) is widely distributed in China, and its fruit has high nutritional and medicinal values. Here, we report a high-quality chromosome-scale genome assembly of Shanmei, with a size of 215.69 Mb and encompassing 26696 genes. Genome comparisons among Rosaceae species show that Shanmei and Fupenzi(Rubus chingii Hu) are most closely related, and then is blackberry (Rubus occidentalis). Further resequencing of 101 samples of Shanmei collected from four regions in provinces of Yunnan, Hunan, Jiangxi and Sichuan in South China reveals that the Hunan population of Shanmei possesses the highest diversity and may represent the relatively more ancestral population. Moreover, the Yunnan population undergoes strong selection based on nucleotide diversity, linkage disequilibrium and the historical effective population size analyses. Furthermore, genes from candidate genomic regions that show strong divergence are significantly enriched in flavonoid biosynthesis and plant hormone signal transduction, indicating the genetic basis of adaptation of Shanmei to the local environments. The high-quality genome sequences and the variome dataset of Shanmei provide valuable resources for breeding applications and for elucidating the genome evolution and ecological adaptation of Rubus species.

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 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 Genome Assembly and Annotation of Botryosphaeria dothidea sdau11-99, a Latent Pathogen of Apple Fruit Ring Rot in China

Plant Disease ◽  
2020 ◽  
Author(s):  
Chengming Yu ◽  
Yufei Diao ◽  
Quan Lu ◽  
Jiaping Zhao ◽  
Shengnan Cui ◽  
...  
Keyword(s):  
Genome Sequence ◽  
Genome Assembly ◽  
Fungal Pathogen ◽  
Woody Plants ◽  
Reference Genome ◽  
Apple Fruit ◽  
Botryosphaeria Dothidea ◽  
High Quality ◽  
Ring Rot ◽  
Wide Range

Botryosphaeria dothidea is a latent and important fungal pathogen on a wide range of woody plants. Fruit ring rot caused by B. dothidea is a major disease in China on apple. This study establishes a high quality, nearly complete and well annotated genome sequence of B. dothidea strain sdau11-99. The findings of this research provide a reference genome resource for further research on the apple fruit ring rot pathogen on apple and other hosts.

Top-Down Garbage Collector: a tool for selecting high-quality top-down proteomics mass spectra

2019 ◽  
Vol 35 (18) ◽  
pp. 3489-3490 ◽  
Author(s):  
Diogo B Lima ◽  
André R F Silva ◽  
Mathieu Dupré ◽  
Marlon D M Santos ◽  
Milan A Clasen ◽  
...  
Keyword(s):  
Quality Control ◽  
Mass Spectra ◽  
Rate Increase ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Top Down ◽  
High Quality ◽  
Garbage Collector ◽  
E Coli ◽  
Spectral Libraries

Abstract Motivation We present the first tool for unbiased quality control of top-down proteomics datasets. Our tool can select high-quality top-down proteomics spectra, serve as a gateway for building top-down spectral libraries and, ultimately, improve identification rates. Results We demonstrate that a twofold rate increase for two E. coli top-down proteomics datasets may be achievable. Availability and implementation http://patternlabforproteomics.org/tdgc, freely available for academic use. Supplementary information Supplementary data are available at Bioinformatics online.

Minirmd: accurate and fast duplicate removal tool for short reads via multiple minimizers

2020 ◽  
Author(s):  
Yuansheng Liu ◽  
Xiaocai Zhang ◽  
Quan Zou ◽  
Xiangxiang Zeng
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
De Novo ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Complementary Strand ◽  
Short Reads ◽  
Sequencing Technologies ◽  
Computational Resources

Abstract Summary Removing duplicate and near-duplicate reads, generated by high-throughput sequencing technologies, is able to reduce computational resources in downstream applications. Here we develop minirmd, a de novo tool to remove duplicate reads via multiple rounds of clustering using different length of minimizer. Experiments demonstrate that minirmd removes more near-duplicate reads than existing clustering approaches and is faster than existing multi-core tools. To the best of our knowledge, minirmd is the first tool to remove near-duplicates on reverse-complementary strand. Availability and implementation https://github.com/yuansliu/minirmd. Supplementary information Supplementary data are available at Bioinformatics online.

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