VINYL: Variant prIoritizatioN by survivaL analysis

AbstractMotivationClinical applications of genome re-sequencing technologies typically generate large amounts of data that need to be carefully annotated and interpreted to identify genetic variants associated with pathological conditions. In this context, accurate and reproducible methods for the functional annotation and prioritization of genetic variants are of fundamental importance, especially when large volumes of data - like those produced by modern sequencing technologies - are involved.ResultsIn this paper, we present VINYL, a highly accurate and fully automated system for the functional annotation and prioritization of genetic variants in large scale clinical studies. Extensive analyses of both real and simulated datasets suggest that VINYL show higher accuracy and sensitivity when compared to equivalent state of the art methods, allowing the rapid and systematic identification of potentially pathogenic variants in different experimental settings.

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CorGAT: a tool for the functional annotation of SARS-CoV-2 genomes

Bioinformatics ◽

10.1093/bioinformatics/btaa1047 ◽

2020 ◽

Author(s):

Matteo Chiara ◽

Federico Zambelli ◽

Marco Antonio Tangaro ◽

Pietro Mandreoli ◽

David S Horner ◽

...

Keyword(s):

Functional Annotation ◽

Ad Hoc ◽

State Of The Art ◽

Supplementary Information ◽

Genomic Sequences ◽

Supplementary Data ◽

Evolutionary Patterns ◽

Genomic Variants ◽

Art Methods ◽

Available Resources

Abstract Summary While over 200 000 genomic sequences are currently available through dedicated repositories, ad hoc methods for the functional annotation of SARS-CoV-2 genomes do not harness all currently available resources for the annotation of functionally relevant genomic sites. Here, we present CorGAT, a novel tool for the functional annotation of SARS-CoV-2 genomic variants. By comparisons with other state of the art methods we demonstrate that, by providing a more comprehensive and rich annotation, our method can facilitate the identification of evolutionary patterns in the genome of SARS-CoV-2. Availabilityand implementation Galaxy http://corgat.cloud.ba.infn.it/galaxy; software: https://github.com/matteo14c/CorGAT/tree/Revision_V1; docker: https://hub.docker.com/r/laniakeacloud/galaxy_corgat. Supplementary information Supplementary data are available at Bioinformatics online.

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StateHub-StatePaintR: rapid and reproducible chromatin state evaluation for custom genome annotation

F1000Research ◽

10.12688/f1000research.13535.2 ◽

2020 ◽

Vol 7 ◽

pp. 214 ◽

Cited By ~ 2

Author(s):

Simon G. Coetzee ◽

Zachary Ramjan ◽

Huy Q. Dinh ◽

Benjamin P. Berman ◽

Dennis J. Hazelett

Keyword(s):

Genome Annotation ◽

Functional Annotation ◽

Clinical Applications ◽

Chromatin State ◽

Methodological Framework ◽

Web Database ◽

Variant Prioritization ◽

Original Source ◽

State Evaluation ◽

Functional Biology

Genome annotation is critical to understand the function of disease variants, especially for clinical applications. To meet this need there are segmentations available from public consortia reflecting varying unsupervised approaches to functional annotation based on epigenetics data, but there remains a need for transparent, reproducible, and easily interpreted genomic maps of the functional biology of chromatin. We introduce a new methodological framework for defining a combinatorial epigenomic model of chromatin state on a web database, StateHub. In addition, we created an annotation tool for bioconductor, StatePaintR, which accesses these models and uses them to rapidly (on the order of seconds) produce chromatin state segmentations in standard genome browser formats. Annotations are fully documented with change history and versioning, authorship information, and original source files. StatePaintR calculates ranks for each state from next-gen sequencing peak statistics, facilitating variant prioritization, enrichment testing, and other types of quantitative analysis. StateHub hosts annotation tracks for major public consortia as a resource, and allows users to submit their own alternative models.

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Seqminer2: an efficient tool to query and retrieve genotypes for statistical genetics analyses from biobank scale sequence dataset

Bioinformatics ◽

10.1093/bioinformatics/btaa628 ◽

2020 ◽

Vol 36 (19) ◽

pp. 4951-4954

Author(s):

Lina Yang ◽

Shuang Jiang ◽

Bibo Jiang ◽

Dajiang J Liu ◽

Xiaowei Zhan

Keyword(s):

Genetic Variants ◽

Method Development ◽

State Of The Art ◽

R Package ◽

Supplementary Information ◽

Efficient Tool ◽

File Formats ◽

Software Prototyping ◽

Novel Variant ◽

Scale Sequence

Abstract Summary Here, we present a highly efficient R-package seqminer2 for querying and retrieving sequence variants from biobank scale datasets of millions of individuals and hundreds of millions of genetic variants. Seqminer2 implements a novel variant-based index for querying VCF/BCF files. It improves the speed of query and retrieval by several magnitudes compared to the state-of-the-art tools based upon tabix. It also reimplements support for BGEN and PLINK format, which improves speed over alternative implementations. The improved efficiency and comprehensive support for popular file formats will facilitate method development, software prototyping and data analysis of biobank scale sequence datasets in R. Availability and implementation The seqminer2 R package is available from https://github.com/zhanxw/seqminer. Scripts used for the benchmarks are available in https://github.com/yang-lina/seqminer/blob/master/seqminer2%20benchmark%20script.txt. Supplementary information Supplementary data are available at Bioinformatics online.

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StateHub-StatePaintR: rapid and reproducible chromatin state evaluation for custom genome annotation

F1000Research ◽

10.12688/f1000research.13535.1 ◽

2018 ◽

Vol 7 ◽

pp. 214 ◽

Cited By ~ 4

Author(s):

Simon G. Coetzee ◽

Zachary Ramjan ◽

Huy Q. Dinh ◽

Benjamin P. Berman ◽

Dennis J. Hazelett

Keyword(s):

Genome Annotation ◽

Functional Annotation ◽

Clinical Applications ◽

Chromatin State ◽

Methodological Framework ◽

Web Database ◽

Variant Prioritization ◽

Original Source ◽

State Evaluation ◽

Functional Biology

Genome annotation is critical to understand the function of disease variants, especially for clinical applications. To meet this need there are segmentations available from public consortia reflecting varying unsupervised approaches to functional annotation based on epigenetics data, but there remains a need for transparent, reproducible, and easily interpreted genomic maps of the functional biology of chromatin. We introduce a new methodological framework for defining a combinatorial epigenomic model of chromatin state on a web database, StateHub. In addition, we created an annotation tool for bioconductor, StatePaintR, which accesses these models and uses them to rapidly (on the order of seconds) produce chromatin state segmentations in standard genome browser formats. Annotations are fully documented with change history and versioning, authorship information, and original source files. StatePaintR calculates ranks for each state from next-gen sequencing peak statistics, facilitating variant prioritization, enrichment testing, and other types of quantitative analysis. StateHub hosts annotation tracks for major public consortia as a resource, and allows users to submit their own alternative models.

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deSAMBA: fast and accurate classification of metagenomics long reads with sparse approximate matches

10.1101/736777 ◽

2019 ◽

Author(s):

Gaoyang Li ◽

Bo Liu ◽

Yadong Wang

Keyword(s):

State Of The Art ◽

Supplementary Information ◽

Alignment Algorithm ◽

Classification Approach ◽

Fast Speed ◽

Sequencing Technologies ◽

Long Reads ◽

Good Classification ◽

Long Read

AbstractSummaryLong read sequencing technologies are promising to metagenomics studies. However, there is still lack of read classification tools to fast and accurately identify the taxonomies of noisy long reads, which is a bottleneck to the use of long read sequencing. Herein, we propose deSAMBA, a tailored long read classification approach that uses a novel sparse approximate match block (SAMB)-based pseudo alignment algorithm. Benchmarks on real datasets demonstrate that deSAMBA enables to simultaneously achieve fast speed and good classification yields, which outperforms state-of-the-art tools and has many potentials to cutting-edge metagenomics studies.Availability and Implementationhttps://github.com/hitbc/deSAMBA.Supplementary information:

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RabbitQC: high-speed scalable quality control for sequencing data

Bioinformatics ◽

10.1093/bioinformatics/btaa719 ◽

2020 ◽

Author(s):

Zekun Yin ◽

Hao Zhang ◽

Meiyang Liu ◽

Wen Zhang ◽

Honglei Song ◽

...

Keyword(s):

Quality Control ◽

High Speed ◽

State Of The Art ◽

Supplementary Information ◽

Control Methods ◽

Sequencing Data ◽

Sequencing Technologies ◽

Oxford Nanopore ◽

Quality Control Tool ◽

Computing Platforms

Abstract Motivation Modern sequencing technologies continue to revolutionize many areas of biology and medicine. Since the generated datasets are error-prone, downstream applications usually require quality control methods to pre-process FASTQ files. However, existing tools for this task are currently not able to fully exploit the capabilities of computing platforms leading to slow runtimes. Results We present RabbitQC, an extremely fast integrated quality control tool for FASTQ files, which can take full advantage of modern hardware. It includes a variety of operations and supports different sequencing technologies (Illumina, Oxford Nanopore and PacBio). RabbitQC achieves speedups between one and two orders-of-magnitude compared to other state-of-the-art tools. Availability and implementation C++ sources and binaries are available at https://github.com/ZekunYin/RabbitQC. Supplementary information Supplementary data are available at Bioinformatics online.

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StateHub-StatePaintR: rapid and reproducible chromatin state evaluation for custom genome annotation

10.1101/127720 ◽

2017 ◽

Cited By ~ 1

Author(s):

Simon G. Coetzee ◽

Zachary Ramjan ◽

Huy Q. Dinh ◽

Benjamin P. Berman ◽

Dennis J. Hazelett

Keyword(s):

Genome Annotation ◽

Functional Annotation ◽

Clinical Applications ◽

Chromatin State ◽

Methodological Framework ◽

Web Database ◽

Variant Prioritization ◽

Original Source ◽

State Evaluation ◽

Functional Biology

AbstractGenome annotation is critical to understand the function of disease variants, especially for clinical applications. To meet this need there are segmentations available from public consortia reflecting varying unsupervised approaches to functional annotation based on epigenetics data, but there remains a need for transparent, reproducible, and easily interpreted genomic maps of the functional biology of chromatin. We introduce a new methodological framework for defining a combinatorial epigenomic model of chromatin state on a web database, StateHub. In addition, we created an annotation tool for bioconductor, StatePaintR, which accesses these models and uses them to rapidly (on the order of seconds) produce chromatin state segmentations in standard genome browser formats. Annotations are fully documented with change history and versioning, authorship information, and original source files. StatePaintR calculates ranks for each state from next-gen sequencing peak statistics, facilitating variant prioritization, enrichment testing, and other types of quantitative analysis. StateHub hosts annotation tracks for major public consortia as a resource, and allows users to submit their own alternative models.

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From Exosome Glycobiology to Exosome Glycotechnology, the Role of Natural Occurring Polysaccharides

Polysaccharides ◽

10.3390/polysaccharides2020021 ◽

2021 ◽

Vol 2 (2) ◽

pp. 311-338

Author(s):

Giulia Della Rosa ◽

Clarissa Ruggeri ◽

Alessandra Aloisi

Keyword(s):

State Of The Art ◽

Cell Communication ◽

Pathological Conditions ◽

New Findings ◽

Cell Type Specific ◽

New Perspective ◽

And Function ◽

And Personalized Medicine ◽

Innate Ability

Exosomes (EXOs) are nano-sized informative shuttles acting as endogenous mediators of cell-to-cell communication. Their innate ability to target specific cells and deliver functional cargo is recently claimed as a promising theranostic strategy. The glycan profile, actively involved in the EXO biogenesis, release, sorting and function, is highly cell type-specific and frequently altered in pathological conditions. Therefore, the modulation of EXO glyco-composition has recently been considered an attractive tool in the design of novel therapeutics. In addition to the available approaches involving conventional glyco-engineering, soft technology is becoming more and more attractive for better exploiting EXO glycan tasks and optimizing EXO delivery platforms. This review, first, explores the main functions of EXO glycans and associates the potential implications of the reported new findings across the nanomedicine applications. The state-of-the-art of the last decade concerning the role of natural polysaccharides—as targeting molecules and in 3D soft structure manufacture matrices—is then analysed and highlighted, as an advancing EXO biofunction toolkit. The promising results, integrating the biopolymers area to the EXO-based bio-nanofabrication and bio-nanotechnology field, lay the foundation for further investigation and offer a new perspective in drug delivery and personalized medicine progress.

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GAMIBHEAR: whole-genome haplotype reconstruction from Genome Architecture Mapping data

Bioinformatics ◽

10.1093/bioinformatics/btab238 ◽

2021 ◽

Author(s):

Julia Markowski ◽

Rieke Kempfer ◽

Alexander Kukalev ◽

Ibai Irastorza-Azcarate ◽

Gesa Loof ◽

...

Keyword(s):

Genetic Variants ◽

Embryonic Stem Cell Line ◽

Embryonic Stem ◽

Mouse Embryonic Stem Cell ◽

Supplementary Information ◽

Model Organisms ◽

Genome Architecture ◽

Chromatin Conformation ◽

Haplotype Reconstruction ◽

Allele Specific

Abstract Motivation Genome Architecture Mapping (GAM) was recently introduced as a digestion- and ligation-free method to detect chromatin conformation. Orthogonal to existing approaches based on chromatin conformation capture (3C), GAM’s ability to capture both inter- and intra-chromosomal contacts from low amounts of input data makes it particularly well suited for allele-specific analyses in a clinical setting. Allele-specific analyses are powerful tools to investigate the effects of genetic variants on many cellular phenotypes including chromatin conformation, but require the haplotypes of the individuals under study to be known a-priori. So far however, no algorithm exists for haplotype reconstruction and phasing of genetic variants from GAM data, hindering the allele-specific analysis of chromatin contact points in non-model organisms or individuals with unknown haplotypes. Results We present GAMIBHEAR, a tool for accurate haplotype reconstruction from GAM data. GAMIBHEAR aggregates allelic co-observation frequencies from GAM data and employs a GAM-specific probabilistic model of haplotype capture to optimise phasing accuracy. Using a hybrid mouse embryonic stem cell line with known haplotype structure as a benchmark dataset, we assess correctness and completeness of the reconstructed haplotypes, and demonstrate the power of GAMIBHEAR to infer accurate genome-wide haplotypes from GAM data. Availability GAMIBHEAR is available as an R package under the open source GPL-2 license at https://bitbucket.org/schwarzlab/gamibhear Maintainer [email protected] Supplementary information Supplementary information is available at Bioinformatics online.

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