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1.
BMC Bioinformatics ; 20(1): 498, 2019 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-31615395

RESUMO

BACKGROUND: Selecting the proper parameter settings for bioinformatic software tools is challenging. Not only will each parameter have an individual effect on the outcome, but there are also potential interaction effects between parameters. Both of these effects may be difficult to predict. To make the situation even more complex, multiple tools may be run in a sequential pipeline where the final output depends on the parameter configuration for each tool in the pipeline. Because of the complexity and difficulty of predicting outcomes, in practice parameters are often left at default settings or set based on personal or peer experience obtained in a trial and error fashion. To allow for the reliable and efficient selection of parameters for bioinformatic pipelines, a systematic approach is needed. RESULTS: We present doepipeline, a novel approach to optimizing bioinformatic software parameters, based on core concepts of the Design of Experiments methodology and recent advances in subset designs. Optimal parameter settings are first approximated in a screening phase using a subset design that efficiently spans the entire search space, then optimized in the subsequent phase using response surface designs and OLS modeling. Doepipeline was used to optimize parameters in four use cases; 1) de-novo assembly, 2) scaffolding of a fragmented genome assembly, 3) k-mer taxonomic classification of Oxford Nanopore Technologies MinION reads, and 4) genetic variant calling. In all four cases, doepipeline found parameter settings that produced a better outcome with respect to the characteristic measured when compared to using default values. Our approach is implemented and available in the Python package doepipeline. CONCLUSIONS: Our proposed methodology provides a systematic and robust framework for optimizing software parameter settings, in contrast to labor- and time-intensive manual parameter tweaking. Implementation in doepipeline makes our methodology accessible and user-friendly, and allows for automatic optimization of tools in a wide range of cases. The source code of doepipeline is available at https://github.com/clicumu/doepipeline and it can be installed through conda-forge.


Assuntos
Genômica/métodos , Análise de Sequência de DNA/métodos , Software , Francisella tularensis/genética , Genoma Bacteriano , Nanoporos
2.
BMC Bioinformatics ; 20(1): 496, 2019 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-31615419

RESUMO

BACKGROUND: When applying genomic medicine to a rare disease patient, the primary goal is to identify one or more genomic variants that may explain the patient's phenotypes. Typically, this is done through annotation, filtering, and then prioritization of variants for manual curation. However, prioritization of variants in rare disease patients remains a challenging task due to the high degree of variability in phenotype presentation and molecular source of disease. Thus, methods that can identify and/or prioritize variants to be clinically reported in the presence of such variability are of critical importance. METHODS: We tested the application of classification algorithms that ingest variant annotations along with phenotype information for predicting whether a variant will ultimately be clinically reported and returned to a patient. To test the classifiers, we performed a retrospective study on variants that were clinically reported to 237 patients in the Undiagnosed Diseases Network. RESULTS: We treated the classifiers as variant prioritization systems and compared them to four variant prioritization algorithms and two single-measure controls. We showed that the trained classifiers outperformed all other tested methods with the best classifiers ranking 72% of all reported variants and 94% of reported pathogenic variants in the top 20. CONCLUSIONS: We demonstrated how freely available binary classification algorithms can be used to prioritize variants even in the presence of real-world variability. Furthermore, these classifiers outperformed all other tested methods, suggesting that they may be well suited for working with real rare disease patient datasets.


Assuntos
Algoritmos , Doenças Genéticas Inatas/diagnóstico , Genômica/métodos , Mutação , Doenças Raras/diagnóstico , Doenças Genéticas Inatas/genética , Predisposição Genética para Doença , Genoma Humano , Humanos , Fenótipo , Polimorfismo Genético , Medicina de Precisão/métodos , Doenças Raras/genética , Estudos Retrospectivos , Análise de Sequência de DNA/métodos , Software
3.
BMC Bioinformatics ; 20(1): 519, 2019 Oct 25.
Artigo em Inglês | MEDLINE | ID: mdl-31653197

RESUMO

BACKGROUND: As sequencing technology improves, the concept of a single reference genome is becoming increasingly restricting. In the case of Mycobacterium tuberculosis, one must often choose between using a genome that is closely related to the isolate, or one that is annotated in detail. One promising solution to this problem is through the graph based representation of collections of genomes as a single genome graph. Though there are currently a handful of tools that can create genome graphs and have demonstrated the advantages of this new paradigm, there still exists a need for flexible tools that can be used by researchers to overcome challenges in genomics studies. RESULTS: We present GenGraph, a Python toolkit and accompanying modules that use existing multiple sequence alignment tools to create genome graphs. Python is one of the most popular coding languages for the biological sciences, and by providing these tools, GenGraph makes it easier to experiment and develop new tools that utilise genome graphs. The conceptual model used is highly intuitive, and as much as possible the graph structure represents the biological relationship between the genomes. This design means that users will quickly be able to start creating genome graphs and using them in their own projects. We outline the methods used in the generation of the graphs, and give some examples of how the created graphs may be used. GenGraph utilises existing file formats and methods in the generation of these graphs, allowing graphs to be visualised and imported with widely used applications, including Cytoscape, R, and Java Script. CONCLUSIONS: GenGraph provides a set of tools for generating graph based representations of sets of sequences with a simple conceptual model, written in the widely used coding language Python, and publicly available on Github.


Assuntos
Genômica/métodos , Alinhamento de Sequência , Software , Genoma
4.
Genome Biol ; 20(1): 193, 2019 09 09.
Artigo em Inglês | MEDLINE | ID: mdl-31500668

RESUMO

Technical variation in feature measurements, such as gene expression and locus accessibility, is a key challenge of large-scale single-cell genomic datasets. We show that this technical variation in both scRNA-seq and scATAC-seq datasets can be mitigated by analyzing feature detection patterns alone and ignoring feature quantification measurements. This result holds when datasets have low detection noise relative to quantification noise. We demonstrate state-of-the-art performance of detection pattern models using our new framework, scBFA, for both cell type identification and trajectory inference. Performance gains can also be realized in one line of R code in existing pipelines.


Assuntos
Genômica/métodos , Análise de Célula Única/métodos , Perfilação da Expressão Gênica , Modelos Genéticos , Análise de Sequência de RNA , Software
5.
Nucleic Acids Res ; 47(18): 9511-9523, 2019 10 10.
Artigo em Inglês | MEDLINE | ID: mdl-31504766

RESUMO

We present Nucleosome Dynamics, a suite of programs integrated into a virtual research environment and created to define nucleosome architecture and dynamics from noisy experimental data. The package allows both the definition of nucleosome architectures and the detection of changes in nucleosomal organization due to changes in cellular conditions. Results are displayed in the context of genomic information thanks to different visualizers and browsers, allowing the user a holistic, multidimensional view of the genome/transcriptome. The package shows good performance for both locating equilibrium nucleosome architecture and nucleosome dynamics and provides abundant useful information in several test cases, where experimental data on nucleosome position (and for some cases expression level) have been collected for cells under different external conditions (cell cycle phase, yeast metabolic cycle progression, changes in nutrients or difference in MNase digestion level). Nucleosome Dynamics is a free software and is provided under several distribution models.


Assuntos
Genômica/métodos , Nucleossomos/genética , Software , Ciclo Celular/genética , Montagem e Desmontagem da Cromatina/genética , Genoma/genética , Nucleossomos/química , Nucleossomos/ultraestrutura , Saccharomyces cerevisiae/genética , Saccharomyces cerevisiae/metabolismo , Sítio de Iniciação de Transcrição , Transcriptoma/genética
6.
Cancer Treat Rev ; 80: 101894, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31518831

RESUMO

Despite advances in translating conventional research into multi-modal treatment for colorectal cancer (CRC), therapeutic resistance and relapse remain unresolved in advanced resectable and, particularly, non-resectable disease. Genome and transcriptome sequencing and editing technologies, coupled with interaction mapping and machine learning, are transforming biomedical research, representing the most rational hope to overcome unmet research and clinical challenges. Rapid progress in both bulk and single-cell next-generation sequencing (NGS) analyses in the identification of primary and metastatic intratumor genomic and transcriptional heterogeneity (ITH) and the detection of circulating cell-free DNA (cfDNA) alterations is providing critical insight into the origins and spatiotemporal evolution of genomic clones responsible for early and late therapeutic resistance and relapse. Moreover, DNA and RNA editing pave new avenues towards the discovery of novel drug targets. Breakthrough combinations of sequencing and editing systems with technologies exploring dynamic interaction networks within pioneering studies could delineate how coding and non-coding mutations perturb regulatory networks and gene expression. This review discusses latest data on genomic and transcriptomic landscapes in time and space, as well as early-phase clinical trials on targeted drug combinations, highlighting the transition from research to clinical Colorectal Cancer Precision Medicine, through non-invasive screening, individualized drug response prediction and development of multiple novel drugs. Future studies exploring the potential to target key transcriptional drivers and regulators will contribute to the next-generation pharmaceutical controllability of multi-layered aberrant transcriptional biocircuits.


Assuntos
Neoplasias Colorretais/genética , Animais , DNA de Neoplasias/genética , Genômica/métodos , Humanos , Medicina de Precisão , RNA Neoplásico/genética , Transcrição Genética
7.
Genome Biol ; 20(1): 199, 2019 09 13.
Artigo em Inglês | MEDLINE | ID: mdl-31519212

RESUMO

Considerable advances in genomics over the past decade have resulted in vast amounts of data being generated and deposited in global archives. The growth of these archives exceeds our ability to process their content, leading to significant analysis bottlenecks. Sketching algorithms produce small, approximate summaries of data and have shown great utility in tackling this flood of genomic data, while using minimal compute resources. This article reviews the current state of the field, focusing on how the algorithms work and how genomicists can utilize them effectively. References to interactive workbooks for explaining concepts and demonstrating workflows are included at https://github.com/will-rowe/genome-sketching .


Assuntos
Algoritmos , Genômica/métodos , Compressão de Dados , Software
8.
Nat Protoc ; 14(10): 3013-3031, 2019 10.
Artigo em Inglês | MEDLINE | ID: mdl-31520072

RESUMO

Functionally linked genes in bacterial and archaeal genomes are often organized into operons. However, the composition and architecture of operons are highly variable and frequently differ even among closely related genomes. Therefore, to efficiently extract reliable functional predictions for uncharacterized genes from comparative analyses of the rapidly growing genomic databases, dedicated computational approaches are required. We developed a protocol to systematically and automatically identify genes that are likely to be functionally associated with a 'bait' gene or locus by using relevance metrics. Given a set of bait loci and a genomic database defined by the user, this protocol compares the genomic neighborhoods of the baits to identify genes that are likely to be functionally linked to the baits by calculating the abundance of a given gene within and outside the bait neighborhoods and the distance to the bait. We exemplify the performance of the protocol with three test cases, namely, genes linked to CRISPR-Cas systems using the 'CRISPRicity' metric, genes associated with archaeal proviruses and genes linked to Argonaute genes in halobacteria. The protocol can be run by users with basic computational skills. The computational cost depends on the sizes of the genomic dataset and the list of reference loci and can vary from one CPU-hour to hundreds of hours on a supercomputer.


Assuntos
Biologia Computacional/métodos , Genes Arqueais , Genes Bacterianos , Genômica/métodos , Sistemas CRISPR-Cas , Genoma Arqueal , Genoma Bacteriano , Anotação de Sequência Molecular/métodos , Fases de Leitura Aberta , Óperon
9.
BMC Bioinformatics ; 20(1): 474, 2019 Sep 14.
Artigo em Inglês | MEDLINE | ID: mdl-31521109

RESUMO

BACKGROUND: In most mammals, a vast array of genes coding for chemosensory receptors mediates olfaction. Odorant receptor (OR) genes generally constitute the largest multifamily (> 1100 intact members in the mouse). From the whole pool, each olfactory neuron expresses a single OR allele following poorly characterized mechanisms termed OR gene choice. OR genes are found in genomic aggregations known as clusters. Nearby enhancers, named elements, are crucial regulators of OR gene choice. Despite their importance, searching for new elements is burdensome. Other chemosensory receptor genes responsible for smell adhere to expression modalities resembling OR gene choice, and are arranged in genomic clusters - often with chromosomal linkage to OR genes. Still, no elements are known for them. RESULTS: Here we present an inexpensive framework aimed at predicting elements. We redefine cluster identity by focusing on multiple receptor gene families at once, and exemplify thirty - not necessarily OR-exclusive - novel candidate enhancers. CONCLUSIONS: The pipeline we introduce could guide future in vivo work aimed at discovering/validating new elements. In addition, our study provides an updated and comprehensive classification of all genomic loci responsible for the transduction of olfactory signals in mammals.


Assuntos
Algoritmos , Elementos Facilitadores Genéticos , Genômica/métodos , Receptores Odorantes/genética , Análise de Sequência de DNA/normas , Animais , Humanos , Camundongos , Ratos
10.
BMC Bioinformatics ; 20(1): 467, 2019 Sep 11.
Artigo em Inglês | MEDLINE | ID: mdl-31510921

RESUMO

BACKGROUND: Cytogenetic nomenclature is used to describe chromosomal aberrations (or lack thereof) in a collection of cells, referred to as the cells' karyotype. The nomenclature identifies locations on chromosomes using a system of cytogenetic bands, each with a unique name and region on a chromosome. Each band is microscopically visible after staining, and encompasses a large portion of the chromosome. More modern analyses employ genomic coordinates, which precisely specify a chromosomal location according to its distance from the end of the chromosome. Currently, there is no tool to convert cytogenetic nomenclature into genomic coordinates. Since locations of genes and other genomic features are usually specified by genomic coordinates, a conversion tool will facilitate the identification of the features that are harbored in the regions of chromosomal gain and loss that are implied by a karyotype. RESULTS: Our tool, termed CytoConverter, takes as input either a single karyotype or a file consisting of multiple karyotypes from several individuals. All net chromosomal gains and losses implied by the karyotype are returned in standard genomic coordinates, along with the numbers of cells harboring each aberration if included in the input. CytoConverter also returns graphical output detailing areas of gains and losses of chromosomes and chromosomal segments. CONCLUSIONS: CytoConverter is available as a web-based application at https://jxw773.shinyapps.io/Cytogenetic__software/ and as an R script at https://sourceforge.net/projects/cytoconverter/ . Supplemental Material detailing the underlying algorithms is available.


Assuntos
Aberrações Cromossômicas , Citogenética/métodos , Genômica/métodos , Internet/instrumentação , Cariótipo , Humanos
11.
Genome Biol ; 20(1): 155, 2019 08 06.
Artigo em Inglês | MEDLINE | ID: mdl-31387612

RESUMO

We describe a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts or genomic regions from thousands of bulk samples or single cells in parallel. Multiplexing is based on a simple method that produces extensive matrices of diverse DNA barcodes attached to invariant primer sets, which are all pre-selected and optimized in silico. By applying the matrices in a novel workflow named Barcode Assembly foR Targeted Sequencing (BART-Seq), we analyze developmental states of thousands of single human pluripotent stem cells, either in different maintenance media or upon Wnt/ß-catenin pathway activation, which identifies the mechanisms of differentiation induction. Moreover, we apply BART-Seq to the genetic screening of breast cancer patients and identify BRCA mutations with very high precision. The processing of thousands of samples and dynamic range measurements that outperform global transcriptomics techniques makes BART-Seq first targeted sequencing technique suitable for numerous research applications.


Assuntos
Perfilação da Expressão Gênica/métodos , Genômica/métodos , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Análise de Sequência de RNA/métodos , Neoplasias da Mama/genética , Análise Custo-Benefício , Células-Tronco Embrionárias/metabolismo , Feminino , Perfilação da Expressão Gênica/economia , Genômica/economia , Sequenciamento de Nucleotídeos em Larga Escala/economia , Humanos , Células-Tronco Pluripotentes/metabolismo , Análise de Sequência de RNA/economia , Análise de Célula Única/economia , Análise de Célula Única/métodos , Via de Sinalização Wnt , Fluxo de Trabalho
12.
Implement Sci ; 14(1): 79, 2019 08 13.
Artigo em Inglês | MEDLINE | ID: mdl-31409417

RESUMO

BACKGROUND: Next-generation sequencing (NGS) is increasingly being translated into routine public health practice, affecting the surveillance and control of many pathogens. The purpose of this scoping review is to identify and characterize the recent literature concerning the application of bacterial pathogen genomics for public health practice and to assess the added value, challenges, and needs related to its implementation from an epidemiologist's perspective. METHODS: In this scoping review, a systematic PubMed search with forward and backward snowballing was performed to identify manuscripts in English published between January 2015 and September 2018. Included studies had to describe the application of NGS on bacterial isolates within a public health setting. The studied pathogen, year of publication, country, number of isolates, sampling fraction, setting, public health application, study aim, level of implementation, time orientation of the NGS analyses, and key findings were extracted from each study. Due to a large heterogeneity of settings, applications, pathogens, and study measurements, a descriptive narrative synthesis of the eligible studies was performed. RESULTS: Out of the 275 included articles, 164 were outbreak investigations, 70 focused on strategy-oriented surveillance, and 41 on control-oriented surveillance. Main applications included the use of whole-genome sequencing (WGS) data for (1) source tracing, (2) early outbreak detection, (3) unraveling transmission dynamics, (4) monitoring drug resistance, (5) detecting cross-border transmission events, (6) identifying the emergence of strains with enhanced virulence or zoonotic potential, and (7) assessing the impact of prevention and control programs. The superior resolution over conventional typing methods to infer transmission routes was reported as an added value, as well as the ability to simultaneously characterize the resistome and virulome of the studied pathogen. However, the full potential of pathogen genomics can only be reached through its integration with high-quality contextual data. CONCLUSIONS: For several pathogens, it is time for a shift from proof-of-concept studies to routine use of WGS during outbreak investigations and surveillance activities. However, some implementation challenges from the epidemiologist's perspective remain, such as data integration, quality of contextual data, sampling strategies, and meaningful interpretations. Interdisciplinary, inter-sectoral, and international collaborations are key for an appropriate genomics-informed surveillance.


Assuntos
Genoma Bacteriano , Genômica/métodos , Prática de Saúde Pública , Humanos , Sequenciamento Completo do Genoma
13.
Bioresour Technol ; 291: 121890, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31378447

RESUMO

In recent impetus of phycological research, microalgae have emerged as a potential candidate for various arena of application-driven research. Omics-based tactics are used for disentangling the regulation and network integration for biosynthesis/degradation of metabolic precursors, intermediates, end products, and identifying the networks that regulate the metabolic flux. Multi-omics coupled with data analytics have facilitated understanding of biological processes and allow ample access to diverse metabolic pathways utilized for genetic manipulations making microalgal factories more efficient. The present review discusses state-of-art "Algomics" and the prospect of microalgae and their role in symbiotic association by using omics approaches including genomics, transcriptomics, proteomics and metabolomics. Microalgal based uni- and multi-omics approaches are critically analyzed in wastewater treatment, metal toxicity and remediation, biofuel production, and therapeutics to provide an imminent outlook for an array of environmentally sustainable and economically viable microalgal applications.


Assuntos
Microalgas/metabolismo , Animais , Genômica/métodos , Humanos , Metabolômica , Proteômica , Águas Residuárias/química
14.
Microbiol Res ; 228: 126306, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31422233

RESUMO

The mariner transposon family of Himar1 has been widely used for the random mutagenesis of bacteria to generate single insertions into the chromosome. Here, a versatile toolbox of mariner transposon derivatives was generated and applied to the functional genomics investigation of fish pathogen Edwardsiella piscicida. In this study, we combined the merits of the random mutagenesis of mariner transposon and common efficient reporter marker genes or regulatory elements, mCherry, gfp, luxAB, lacZ, sacBR, and PBAD and antibiotic resistance cassettes to construct a series of derivative transposon vectors, pMmch, pMKGR, pMCGR, pMXKGR, pMLKGR, pMSGR, and pMPR, based on the initial transposon pMar2xT7. The function and effectiveness of the modified transposons were verified by introducing them into E. piscicida EIB202. Based on the toolbox, a transposon insertion mutant library containing approximately 3.0 × 105 distinct mutants was constructed to explore the upstream regulators of esrB, the master regulator of the type III and type VI secretion systems (T3/T6SS) in E. piscicida. Following analysis by Con-ARTIST, ETAE_3474, annotated as fabR and involved in fatty acid metabolism, was screened out and identified as a novel regulator mediating T3SS and T6SS expression. In addition, the fabR mutants displayed critical virulence attenuation in turbot. Due to the broad-range host compatibility of mariner transposons, the newly built transposon toolbox can be applied for functional genomics studies in various bacteria.


Assuntos
Proteínas de Bactérias/genética , Elementos de DNA Transponíveis , Edwardsiella/genética , Regulação Bacteriana da Expressão Gênica/genética , Testes Genéticos/métodos , Genoma Bacteriano/genética , Animais , Mapeamento Cromossômico , Farmacorresistência Bacteriana/genética , Ácidos Graxos/metabolismo , Doenças dos Peixes/microbiologia , Biblioteca Gênica , Genes Reporter/genética , Genômica/métodos , Mutagênese Insercional/métodos , Fatores de Transcrição/genética , Sistemas de Secreção Tipo III/genética , Sistemas de Secreção Tipo VI/genética , Virulência , Fatores de Virulência/genética
15.
BMC Infect Dis ; 19(1): 738, 2019 Aug 22.
Artigo em Inglês | MEDLINE | ID: mdl-31438880

RESUMO

BACKGROUND: The technique most frequently used to genotype HCV is quantitative RT-PCR. This technique is unable to provide an accurate genotype/subtype for many samples; we decided to develop an in-house method with the goal of accurately identifying the genotype of all samples. As a Belgium National Centre of reference for hepatitis, we developed in-house sequencing not only for 5'UTR and core regions starting from VERSANT LiPA amplicons but also for NS5B regions. The sequencing of VERSANT LiPA amplicons might be useful for many laboratories worldwide using the VERSANT LiPA assay to overcome undetermined results. METHODS: 100 samples from Hepatitis C virus infected patients analysed by the VERSANT HCV Genotype 2.0 LiPA Assay covering frequent HCV types and subtypes were included in this study. NS5B, 5'UTR and Core home-made sequencing were then performed on these samples. The sequences obtained were compared with the HCV genomic BLAST bank. RESULTS: All the samples were characterised by the VERSANT LiPA assay (8 G1a, 17 G1b, 6 G2, 11 G3, 13 G4, and 10 G6). It was not possible to discriminate between G6 and G1 by the VERSANT LiPA assay for 8 samples and 27 had an undetermined genotype. Forty-one samples were sequenced for the three regions: NS5B, 5'UTR and Core. Twenty-three samples were sequenced for two regions: 5' UTR and Core and 36 samples were sequenced only for NS5B. Of the 100 samples included, 64 samples were analysed for 5'UTR and Core sequencing and 79 samples were analysed for NS5B sequencing. The global agreement between VERSANT LiPA assay and sequencing was greater than 95%. CONCLUSIONS: In this study, we describe a new, original method to confirm HCV genotypes of samples not discriminated by a commercial assay, using amplicons already obtained by the screening method, here the VERSANT LiPA assay. This method thus saves one step if a confirmation assay is needed and might be of usefulness for many laboratories worldwide performing VERSANT LiPA assay in particular.


Assuntos
Técnicas de Genotipagem/métodos , Hepacivirus/genética , Hepatite C/diagnóstico , Técnicas de Sonda Molecular , Kit de Reagentes para Diagnóstico , Análise de Sequência de RNA/métodos , Regiões 5' não Traduzidas , Sequência de Bases , Comércio , Genômica/métodos , Genótipo , Técnicas de Genotipagem/economia , Hepacivirus/isolamento & purificação , Hepatite C/virologia , Humanos , Técnicas de Sonda Molecular/economia , Filogenia , RNA Viral/análise , RNA Viral/isolamento & purificação , Kit de Reagentes para Diagnóstico/economia , Estudos Retrospectivos , Análise de Sequência de RNA/economia , Centros de Atenção Terciária
16.
BMC Bioinformatics ; 20(1): 426, 2019 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-31416413

RESUMO

BACKGROUND: Advances in medical technology have allowed for customized prognosis, diagnosis, and treatment regimens that utilize multiple heterogeneous data sources. Multiple kernel learning (MKL) is well suited for the integration of multiple high throughput data sources. MKL remains to be under-utilized by genomic researchers partly due to the lack of unified guidelines for its use, and benchmark genomic datasets. RESULTS: We provide three implementations of MKL in R. These methods are applied to simulated data to illustrate that MKL can select appropriate models. We also apply MKL to combine clinical information with miRNA gene expression data of ovarian cancer study into a single analysis. Lastly, we show that MKL can identify gene sets that are known to play a role in the prognostic prediction of 15 cancer types using gene expression data from The Cancer Genome Atlas, as well as, identify new gene sets for the future research. CONCLUSION: Multiple kernel learning coupled with modern optimization techniques provides a promising learning tool for building predictive models based on multi-source genomic data. MKL also provides an automated scheme for kernel prioritization and parameter tuning. The methods used in the paper are implemented as an R package called RMKL package, which is freely available for download through CRAN at https://CRAN.R-project.org/package=RMKL .


Assuntos
Algoritmos , Mineração de Dados , Genômica/métodos , Bases de Dados Genéticas , Humanos , MicroRNAs/genética , MicroRNAs/metabolismo , Neoplasias/genética
17.
Cancer Invest ; 37(9): 427-431, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31451055

RESUMO

The genome represents a design for creating the body, with each one being different. In cancer genomic medicine, many genes are simultaneously examined using mainly cancer tissues (the oncogene panel test), and gene mutations are revealed. Cancer treatments are then initiated according to each individual's constitution and medical condition based on gene mutations. A system for cancer genome medical treatment is currently being developed. In the treatment of several types of cancer, the "oncogene test with an oncogene companion diagnosis" is already being performed as a standard test using cancer tissue to detect one or more gene mutations. On June 1, 2019, the cancer gene panel test was covered by the national health insurance system in Japan, and a system to initiate cancer genome medical treatment has begun. The prospects and problems associated with cancer genome medicine are discussed herein.


Assuntos
Genômica/métodos , Neoplasias/genética , Política de Saúde , Humanos , Japão , Mutação , Programas Nacionais de Saúde , Medicina de Precisão
19.
Lancet ; 394(10197): 511-520, 2019 Aug 10.
Artigo em Inglês | MEDLINE | ID: mdl-31395439

RESUMO

Advances in technologies for assessing genomic variation and an increasing understanding of the effects of genomic variants on health and disease are driving the transition of genomics from the research laboratory into clinical care. Genomic medicine, or the use of an individual's genomic information as part of their clinical care, is increasingly gaining acceptance in routine practice, including in assessing disease risk in individuals and their families, diagnosing rare and undiagnosed diseases, and improving drug safety and efficacy. We describe the major types and measurement tools of genomic variation that are currently of clinical importance, review approaches to interpreting genomic sequence variants, identify publicly available tools and resources for genomic test interpretation, and discuss several key barriers in using genomic information in routine clinical practice.


Assuntos
Genômica/métodos , Medicina de Precisão/métodos , Predisposição Genética para Doença , Humanos , Variantes Farmacogenômicos
20.
Lancet ; 394(10198): 604-610, 2019 Aug 17.
Artigo em Inglês | MEDLINE | ID: mdl-31395443

RESUMO

Human genomic sequencing has potential diagnostic, prognostic, and therapeutic value across a wide breadth of clinical disciplines. One barrier to widespread adoption is the paucity of evidence for improved outcomes in patients who do not already have an indication for more focused testing. In this Series paper, we review clinical outcome studies in genomic medicine and discuss the important features and key challenges to building evidence for next generation sequencing in the context of routine patient care.


Assuntos
Genômica/métodos , Medicina de Precisão/métodos , Testes Diagnósticos de Rotina , Genoma Humano , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Avaliação de Resultados da Assistência ao Paciente , Padrão de Cuidado
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