scholarly journals halSynteny: a fast, easy-to-use conserved synteny block construction method for multiple whole-genome alignments

GigaScience ◽  
2020 ◽  
Vol 9 (6) ◽  
Author(s):  
Ksenia Krasheninnikova ◽  
Mark Diekhans ◽  
Joel Armstrong ◽  
Aleksei Dievskii ◽  
Benedict Paten ◽  
...  
Keyword(s):  
Large Scale ◽  
Pairwise Alignment ◽  
Synteny Block ◽  
Rapid Identification ◽  
Full Genome Sequence ◽  
Whole Genome ◽  
Full Genome ◽  
Genome Data ◽  
Multiple Alignments ◽  
Binary Format

Abstract Background Large-scale sequencing projects provide high-quality full-genome data that can be used for reconstruction of chromosomal exchanges and rearrangements that disrupt conserved syntenic blocks. The highest resolution of cross-species homology can be obtained on the basis of whole-genome, reference-free alignments. Very large multiple alignments of full-genome sequence stored in a binary format demand an accurate and efficient computational approach for synteny block production. Findings halSynteny performs efficient processing of pairwise alignment blocks for any pair of genomes in the alignment. The tool is part of the HAL comparative genomics suite and is targeted to build synteny blocks for multi-hundred–way, reference-free vertebrate alignments built with the Cactus system. Conclusions halSynteny enables an accurate and rapid identification of synteny in multiple full-genome alignments. The method is implemented in C++11 as a component of the halTools software and released under MIT license. The package is available at https://github.com/ComparativeGenomicsToolkit/hal/.

scholarly journals Seave: a comprehensive web platform for storing and interrogating human genomic variation

2018 ◽  
Author(s):  
Velimir Gayevskiy ◽  
Tony Roscioli ◽  
Marcel E Dinger ◽  
Mark J Cowley
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Variant Calling ◽  
Genomic Variation ◽  
Whole Genome ◽  
Genome Data ◽  
Pathogenicity Prediction ◽  
Data Scaling ◽  
Human Genomic ◽  
Web Platform

AbstractCapability for genome sequencing and variant calling has increased dramatically, enabling large scale genomic interrogation of human disease. However, discovery is hindered by the current limitations in genomic interpretation, which remains a complicated and disjointed process. We introduce Seave, a web platform that enables variants to be easily filtered and annotated with in silico pathogenicity prediction scores and annotations from popular disease databases. Seave stores genomic variation of all types and sizes, and allows filtering for specific inheritance patterns, quality values, allele frequencies and gene lists. Seave is open source and deployable locally, or on a cloud computing provider, and works readily with gene panel, exome and whole genome data, scaling from single labs to multi-institution scale.

scholarly journals VCF2PopTree: a one-click client-side software to construct population phylogeny from genome-wide SNPs

2019 ◽  
Author(s):  
Sankar Subramanian ◽  
Umayal Ramasamy ◽  
David Chen
Keyword(s):  
Phylogenetic Trees ◽  
Large Scale ◽  
Web Applications ◽  
Third Party ◽  
Genotype Data ◽  
Whole Genome ◽  
Genome Data ◽  
Genome Wide ◽  
Software Programs ◽  
Computationally Intensive

In the past decades a number of software programs have been developed to deduce the phylogenetic relationship between populations. However, these programs are not suited for large-scale whole genome data. Recently, a few standalone or web applications have been developed to handle genome-wide data, but they were either computationally intensive, dependent on third party software or required significant time and resource of a web server. In the post-genomic era, researchers are able to obtain bioinformatically processed high-quality publication-ready whole genome data for many individuals in a population from next generation sequencing companies due to the reduction in the cost of sequencing and analysis. Such genotype data is typically presented in the Variant Call Format (VCF) and there is no simple software available that uses this data to construct the phylogeny of populations in a short time. To address this limitation, we have developed a one-click user-friendly software, VCF2PopTree that uses gnome-wide SNPs to construct and display phylogenetic trees in seconds to minutes. For example, it reads a 1 GB VCF file and draws a tree in less than 5 minutes. VCF2PopTree accepts genotype data from a local machine, constructs a tree using UPGMA and Neighbour-Joining algorithms and displays it on a web-browser. It also produces pairwise-diversity matrix in MEGA and PHYLIP file formats as well as trees in the Newick format which could be directly used by other popular phylogenetic software programs. The software including the source code, a test VCF input file and short documentation are available at: https://github.com/sansubs/vcf2pop.

scholarly journals VCF2PopTree: a one-click client-side software to construct population phylogeny from genome-wide SNPs

2019 ◽  
Author(s):  
Sankar Subramanian ◽  
Umayal Ramasamy ◽  
David Chen
Keyword(s):  
Phylogenetic Trees ◽  
Large Scale ◽  
Web Applications ◽  
Third Party ◽  
Genotype Data ◽  
Whole Genome ◽  
Genome Data ◽  
Genome Wide ◽  
Software Programs ◽  
Computationally Intensive

In the past decades a number of software programs have been developed to deduce the phylogenetic relationship between populations. However, these programs are not suited for large-scale whole genome data. Recently, a few standalone or web applications have been developed to handle genome-wide data, but they were either computationally intensive, dependent on third party software or required significant time and resource of a web server. In the post-genomic era, researchers are able to obtain bioinformatically processed high-quality publication-ready whole genome data for many individuals in a population from next generation sequencing companies due to the reduction in the cost of sequencing and analysis. Such genotype data is typically presented in the Variant Call Format (VCF) and there is no simple software available that uses this data to construct the phylogeny of populations in a short time. To address this limitation, we have developed a one-click user-friendly software, VCF2PopTree that uses gnome-wide SNPs to construct and display phylogenetic trees in seconds to minutes. For example, it reads a 1 GB VCF file and draws a tree in less than 5 minutes. VCF2PopTree accepts genotype data from a local machine, constructs a tree using UPGMA and Neighbour-Joining algorithms and displays it on a web-browser. It also produces pairwise-diversity matrix in MEGA and PHYLIP file formats as well as trees in the Newick format which could be directly used by other popular phylogenetic software programs. The software including the source code, a test VCF input file and short documentation are available at: http://sankarsubramanian.net/dat/index.html.

scholarly journals Practical guide for managing large-scale human genome data in research

2020 ◽  
Vol 66 (1) ◽  
pp. 39-52
Author(s):  
Tomoya Tanjo ◽  
Yosuke Kawai ◽  
Katsushi Tokunaga ◽  
Osamu Ogasawara ◽  
Masao Nagasaki
Keyword(s):  
Data Processing ◽  
Whole Genome Sequencing ◽  
Human Genome ◽  
Genome Sequencing ◽  
Large Scale ◽  
Genomic Data ◽  
Whole Genome ◽  
Sequencing Data ◽  
Genome Data ◽  
Human Genome Data

AbstractStudies in human genetics deal with a plethora of human genome sequencing data that are generated from specimens as well as available on public domains. With the development of various bioinformatics applications, maintaining the productivity of research, managing human genome data, and analyzing downstream data is essential. This review aims to guide struggling researchers to process and analyze these large-scale genomic data to extract relevant information for improved downstream analyses. Here, we discuss worldwide human genome projects that could be integrated into any data for improved analysis. Obtaining human whole-genome sequencing data from both data stores and processes is costly; therefore, we focus on the development of data format and software that manipulate whole-genome sequencing. Once the sequencing is complete and its format and data processing tools are selected, a computational platform is required. For the platform, we describe a multi-cloud strategy that balances between cost, performance, and customizability. A good quality published research relies on data reproducibility to ensure quality results, reusability for applications to other datasets, as well as scalability for the future increase of datasets. To solve these, we describe several key technologies developed in computer science, including workflow engine. We also discuss the ethical guidelines inevitable for human genomic data analysis that differ from model organisms. Finally, the future ideal perspective of data processing and analysis is summarized.

scholarly journals Whole-Genome Sequencing of Macrolide-Resistant Mycoplasma pneumoniae Strain S355, Isolated in China

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Shaoli Li ◽  
Fei Liu ◽  
Hongmei Sun ◽  
Baoli Zhu ◽  
Na Lv ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Mycoplasma Pneumoniae ◽  
Genome Sequence ◽  
Full Genome Sequence ◽  
Whole Genome ◽  
Full Genome ◽  
Insight Into

Macrolide-resistant Mycoplasma pneumoniae plays an important role in refractory M. pneumoniae pneumonia. Here, we present the whole-genome sequencing of the macrolide-resistant M. pneumoniae strain S355. The annotated full-genome sequence might provide a new insight into drug resistance in M. pneumoniae and can help pediatricians recognize the disease earlier.

scholarly journals VCF2PopTree: a one-click client-side software to construct population phylogeny from genome-wide SNPs

2019 ◽  
Author(s):  
Sankar Subramanian ◽  
Umayal Ramasamy ◽  
David Chen
Keyword(s):  
Phylogenetic Trees ◽  
Large Scale ◽  
Web Applications ◽  
Third Party ◽  
Genotype Data ◽  
Whole Genome ◽  
Genome Data ◽  
Genome Wide ◽  
Software Programs ◽  
Computationally Intensive

In the past decades a number of software programs have been developed to deduce the phylogenetic relationship between populations. However, these programs are not suited for large-scale whole genome data. Recently, a few standalone or web applications have been developed to handle genome-wide data, but they were either computationally intensive, dependent on third party software or required significant time and resource of a web server. In the post-genomic era, researchers are able to obtain bioinformatically processed high-quality publication-ready whole genome data for many individuals in a population from next generation sequencing companies due to the reduction in the cost of sequencing and analysis. Such genotype data is typically presented in the Variant Call Format (VCF) and there is no simple software available that uses this data to construct the phylogeny of populations in a short time. To address this limitation, we have developed a one-click user-friendly software, VCF2PopTree that uses gnome-wide SNPs to construct and display phylogenetic trees in seconds to minutes. For example, it reads a 1 GB VCF file and draws a tree in less than 5 minutes. VCF2PopTree accepts genotype data from a local machine, constructs a tree using UPGMA and Neighbour-Joining algorithms and displays it on a web-browser. It also produces pairwise-diversity matrix in MEGA and PHYLIP file formats as well as trees in the Newick format which could be directly used by other popular phylogenetic software programs. The software including the source code, a test VCF input file and short documentation are available at: https://github.com/sansubs/vcf2pop.

scholarly journals UK circulating strains of human parainfluenza 3: an amplicon based next generation sequencing method and phylogenetic analysis

2018 ◽  
Vol 3 ◽  
pp. 118
Author(s):  
Anna Smielewska ◽  
Edward Emmott ◽  
Kyriaki Ranellou ◽  
Ashley Popay ◽  
Ian Goodfellow ◽  
...  
Keyword(s):  
Phylogenetic Analysis ◽  
Genome Sequence ◽  
Sequence Data ◽  
Hypervariable Region ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Full Genome ◽  
Genome Sequences ◽  
Genome Data ◽  
The Uk

Background:Human parainfluenza viruses type 3 (HPIV3) are a prominent cause of respiratory infection with a significant impact in both pediatric and transplant patient cohorts.  Currently there is a paucity of whole genome sequence data that would allow for detailed epidemiological and phylogenetic analysis of circulating strains in the UK. Although it is known that HPIV3 peaks annually in the UK, to date there are no whole genome sequences of HPIV3 UK strains available. Methods:Clinical strains were obtained from HPIV3 positive respiratory patient samples collected between 2011 and 2015.  These were then amplified using an amplicon based method, sequenced on the Illumina platform and assembled using a new robust bioinformatics pipeline. Phylogenetic analysis was carried out in the context of other epidemiological studies and whole genome sequence data currently available with stringent exclusion of significantly culture-adapted strains of HPIV3.Results:In the current paper we have presented twenty full genome sequences of UK circulating strains of HPIV3 and a detailed phylogenetic analysis thereof.  We have analysed the variability along the HPIV3 genome and identified a short hypervariable region in the non-coding segment between the M (matrix) and F (fusion) genes. The epidemiological classifications obtained by using this region and whole genome data were then compared and found to be identical.Conclusions:The majority of HPIV3 strains were observed at different geographical locations and with a wide temporal spread, reflecting the global distribution of HPIV3. Consistent with previous data, a particular subcluster or strain was not identified as specific to the UK, suggesting that a number of genetically diverse strains circulate at any one time. A small hypervariable region in the HPIV3 genome was identified and it was shown that, in the absence of full genome data, this region could be used for epidemiological surveillance of HPIV3.

scholarly journals VCF2PopTree: a client-side software to construct population phylogeny from genome-wide SNPs

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e8213 ◽  
Author(s):  
Sankar Subramanian ◽  
Umayal Ramasamy ◽  
David Chen
Keyword(s):  
Phylogenetic Trees ◽  
Large Scale ◽  
Web Applications ◽  
Third Party ◽  
Genotype Data ◽  
Whole Genome ◽  
Genome Data ◽  
Genome Wide ◽  
Software Programs ◽  
Computationally Intensive

In the past decades a number of software programs have been developed to infer phylogenetic relationships between populations. However, most of these programs typically use alignments of sequences from genes to build phylogeny. Recently, many standalone or web applications have been developed to handle large-scale whole genome data, but they are either computationally intensive, dependent on third party software or required significant time and resource of a web server. In the post-genomic era, researchers are able to obtain bioinformatically processed high-quality publication-ready whole genome data for many individuals in a population from next generation sequencing companies due to the reduction in the cost of sequencing and analysis. Such genotype data is typically presented in the Variant Call Format (VCF) and there is no simple software available that directly uses this data format to construct the phylogeny of populations in a short time. To address this limitation, we have developed a user-friendly software, VCF2PopTree that uses genome-wide SNPs to construct and display phylogenetic trees in seconds to minutes. For example, it reads a VCF file containing 4 million SNPs and draws a tree in less than 30 seconds. VCF2PopTree accepts genotype data from a local machine, constructs a tree using UPGMA and Neighbour-Joining algorithms and displays it on a web-browser. It also produces pairwise-diversity matrix in MEGA and PHYLIP file formats as well as trees in the Newick format which could be directly used by other popular phylogenetic software programs. The software including the source code, a test VCF file and a documentation are available at: https://github.com/sansubs/vcf2pop.

scholarly journals Whole-genome microsynteny-based phylogeny of angiosperms

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Tao Zhao ◽  
Arthur Zwaenepoel ◽  
Jia-Yu Xue ◽  
Shu-Min Kao ◽  
Zhen Li ◽  
...  
Keyword(s):  
Large Scale ◽  
Phylogenetic Inference ◽  
Data Sets ◽  
Whole Genome ◽  
Data Set ◽  
Genome Data ◽  
Structural Differences ◽  
Evolution Dynamics ◽  
Plant Families ◽  
Early Diverging Eudicots

AbstractPlant genomes vary greatly in size, organization, and architecture. Such structural differences may be highly relevant for inference of genome evolution dynamics and phylogeny. Indeed, microsynteny—the conservation of local gene content and order—is recognized as a valuable source of phylogenetic information, but its use for the inference of large phylogenies has been limited. Here, by combining synteny network analysis, matrix representation, and maximum likelihood phylogenetic inference, we provide a way to reconstruct phylogenies based on microsynteny information. Both simulations and use of empirical data sets show our method to be accurate, consistent, and widely applicable. As an example, we focus on the analysis of a large-scale whole-genome data set for angiosperms, including more than 120 available high-quality genomes, representing more than 50 different plant families and 30 orders. Our ‘microsynteny-based’ tree is largely congruent with phylogenies proposed based on more traditional sequence alignment-based methods and current phylogenetic classifications but differs for some long-contested and controversial relationships. For instance, our synteny-based tree finds Vitales as early diverging eudicots, Saxifragales within superasterids, and magnoliids as sister to monocots. We discuss how synteny-based phylogenetic inference can complement traditional methods and could provide additional insights into some long-standing controversial phylogenetic relationships.

scholarly journals UK circulating strains of human parainfluenza 3: an amplicon based next generation sequencing method and phylogenetic analysis

2018 ◽  
Vol 3 ◽  
pp. 118 ◽  
Author(s):  
Anna Smielewska ◽  
Edward Emmott ◽  
Kyriaki Ranellou ◽  
Ashley Popay ◽  
Ian Goodfellow ◽  
...  
Keyword(s):  
Phylogenetic Analysis ◽  
Genome Sequence ◽  
Sequence Data ◽  
Hypervariable Region ◽  
Whole Genome Sequence ◽  
Whole Genome ◽  
Full Genome ◽  
Genome Sequences ◽  
Genome Data ◽  
The Uk

Background:Human parainfluenza viruses type 3 (HPIV3) are a prominent cause of respiratory infection with a significant impact in both pediatric and transplant patient cohorts.  Currently there is a paucity of whole genome sequence data that would allow for detailed epidemiological and phylogenetic analysis of circulating strains in the UK. Although it is known that HPIV3 peaks annually in the UK, to date there are no whole genome sequences of HPIV3 UK strains available. Methods:Clinical strains were obtained from HPIV3 positive respiratory patient samples collected between 2011 and 2015.  These were then amplified using an amplicon based method, sequenced on the Illumina platform and assembled using a new robust bioinformatics pipeline. Phylogenetic analysis was carried out in the context of other epidemiological studies and whole genome sequence data currently available with stringent exclusion of significantly culture-adapted strains of HPIV3.Results:In the current paper we have presented twenty full genome sequences of UK circulating strains of HPIV3 and a detailed phylogenetic analysis thereof.  We have analysed the variability along the HPIV3 genome and identified a short hypervariable region in the non-coding segment between the M (matrix) and F (fusion) genes. The epidemiological classifications obtained by using this region and whole genome data were then compared and found to be identical.Conclusions:The majority of HPIV3 strains were observed at different geographical locations and with a wide temporal spread, reflecting the global distribution of HPIV3. Consistent with previous data, a particular subcluster or strain was not identified as specific to the UK, suggesting that a number of genetically diverse strains circulate at any one time. A small hypervariable region in the HPIV3 genome was identified and it was shown that, in the absence of full genome data, this region could be used for epidemiological surveillance of HPIV3.

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