A brief introduction to web-based genome browsers

Wang, Jun; Kong, Lei; Gao, Ge; Luo, Jianxun

doi:10.1093/bib/bbs029

Cited by 51 publications

(32 citation statements)

References 35 publications

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“…Genome browsers can be divided into two major types: web-based applications running on a dedicated web server [89] and stand-alone tools, where most of them use a GUI. As all genome browsers with a GUI are implemented in Java, they can be used on platforms such as Windows, Mac and Linux systems.…”

Section: Ngs Variant Analysis Workflowmentioning

confidence: 99%

A survey of tools for variant analysis of next-generation genome sequencing data

Pabinger¹,

Dander

Fischer³

et al. 2013

Briefings in Bioinformatics

501

463

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Recent advances in genome sequencing technologies provide unprecedented opportunities to characterize individual genomic landscapes and identify mutations relevant for diagnosis and therapy. Specifically, whole-exome sequencing using next-generation sequencing (NGS) technologies is gaining popularity in the human genetics community due to the moderate costs, manageable data amounts and straightforward interpretation of analysis results. While whole-exome and, in the near future, whole-genome sequencing are becoming commodities, data analysis still poses significant challenges and led to the development of a plethora of tools supporting specific parts of the analysis workflow or providing a complete solution. Here, we surveyed 205 tools for whole-genome/whole-exome sequencing data analysis supporting five distinct analytical steps: quality assessment, alignment, variant identification, variant annotation and visualization. We report an overview of the functionality, features and specific requirements of the individual tools. We then selected 32 programs for variant identification, variant annotation and visualization, which were subjected to hands-on evaluation using four data sets: one set of exome data from two patients with a rare disease for testing identification of germline mutations, two cancer data sets for testing variant callers for somatic mutations, copy number variations and structural variations, and one semi-synthetic data set for testing identification of copy number variations. Our comprehensive survey and evaluation of NGS tools provides a valuable guideline for human geneticists working on Mendelian disorders, complex diseases and cancers.

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Section: Ngs Variant Analysis Workflowmentioning

confidence: 99%

A survey of tools for variant analysis of next-generation genome sequencing data

Pabinger¹,

Dander

Fischer³

et al. 2013

Briefings in Bioinformatics

501

463

View full text Add to dashboard Cite

show abstract

“…The NCBI Sequence Viewer was selected over other genome browsers because of its simplicity and the ability to embed it in any page without the need for local installation and administration [36]. The simplicity of the interface is crucial for clinicians and health professionals who are not familiar with complex applications currently available in biological research.…”

Section: Resultsmentioning

confidence: 99%

IthaGenes: An Interactive Database for Haemoglobin Variations and Epidemiology

et al. 2014

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Inherited haemoglobinopathies are the most common monogenic diseases, with millions of carriers and patients worldwide. At present, we know several hundred disease-causing mutations on the globin gene clusters, in addition to numerous clinically important trans-acting disease modifiers encoded elsewhere and a multitude of polymorphisms with relevance for advanced diagnostic approaches. Moreover, new disease-linked variations are discovered every year that are not included in traditional and often functionally limited locus-specific databases. This paper presents IthaGenes, a new interactive database of haemoglobin variations, which stores information about genes and variations affecting haemoglobin disorders. In addition, IthaGenes organises phenotype, relevant publications and external links, while embedding the NCBI Sequence Viewer for graphical representation of each variation. Finally, IthaGenes is integrated with the companion tool IthaMaps for the display of corresponding epidemiological data on distribution maps. IthaGenes is incorporated in the ITHANET community portal and is free and publicly available at http://www.ithanet.eu/db/ithagenes.

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“…Genome browsers [13,21,29,52,55,12] visualize genome sequences. They compare genomes by visualizing the position of each nucleotide and consider a genome as a long and linear sequence of nucleotides.…”

Section: Event Sequence Comparisonmentioning

confidence: 99%

Cohort Comparison of Event Sequences with Balanced Integration of Visual Analytics and Statistics

Malik

Monroe

et al. 2015

Proceedings of the 20th International Conference on Intelligent User Interfaces

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Finding the differences and similarities between two datasets is a common analytics task. With temporal event sequence data, this task is complex because of the many ways single events and event sequences can differ between the two datasets (or cohorts) of records: the structure of the event sequences (e.g., event order, co-occurring events, or event frequencies), the attributes of events and records (e.g., patient gender), or metrics about the timestamps themselves (e.g., event duration). In exploratory analyses, running statistical tests to cover all cases is time-consuming and determining which results are significant becomes cumbersome. Current analytics tools for comparing groups of event sequences emphasize a purely statistical or purely visual approach for comparison. This paper presents a taxonomy of metrics for comparing cohorts of temporal event sequences, showing that the problem-space is bounded. We also present a visual analytics tool, CoCo (for "Cohort Comparison"), which implements balanced integration of automated statistics with an intelligent user interface to guide users to significant, distinguishing features between the cohorts. Lastly, we describe two early case studies: the first with a research team studying medical team performance in the emergency department and the second with pharmacy researchers.

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A brief introduction to web-based genome browsers

Cited by 51 publications

References 35 publications

A survey of tools for variant analysis of next-generation genome sequencing data

A survey of tools for variant analysis of next-generation genome sequencing data

IthaGenes: An Interactive Database for Haemoglobin Variations and Epidemiology

Cohort Comparison of Event Sequences with Balanced Integration of Visual Analytics and Statistics

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