Multi Locus View: an extensible web-based tool for the analysis of genomic data.

被引:3
|
作者
Sergeant, Martin J. [1 ]
Hughes, Jim R. [1 ,2 ]
Hentges, Lance [1 ]
Lunter, Gerton [1 ,3 ]
Downes, Damien J. [2 ]
Taylor, Stephen [1 ]
机构
[1] Univ Oxford, MRC WIMM Ctr Computat Biol, MRC Weatherall Inst Mol Med, Oxford, England
[2] Univ Oxford, MRC Weatherall Inst Mol Med, MRC Mol Haematol Unit, Oxford, England
[3] Univ Groningen, Univ Med Ctr Groningen, Dept Epidemiol, Groningen, Netherlands
基金
英国惠康基金; 英国医学研究理事会; 美国国家卫生研究院;
关键词
D O I
10.1038/s42003-021-02097-y
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Tracking and understanding data quality, analysis and reproducibility are critical concerns in the biological sciences. This is especially true in genomics where next generation sequencing (NGS) based technologies such as ChIP-seq, RNA-seq and ATAC-seq are generating a flood of genome-scale data. However, such data are usually processed with automated tools and pipelines, generating tabular outputs and static visualisations. Interpretation is normally made at a high level without the ability to visualise the underlying data in detail. Conventional genome browsers are limited to browsing single locations and do not allow for interactions with the dataset as a whole. Multi Locus View (MLV), a web-based tool, has been developed to allow users to fluidly interact with genomics datasets at multiple scales. The user is able to browse the raw data, cluster, and combine the data with other analysis and annotate the data. User datasets can then be shared with other users or made public for quick assessment from the academic community. MLV is publically available at https://mlv.molbiol.ox.ac.uk. Martin Sergeant et al. develop a web-based tool called Multi Locus View that allows researchers to interact with genomics datasets at multiple scales. Users can browse, annotate, combine or analyse raw data on this interface. The user datasets generated in this tool can also be made public. This tool is expected to increase public access to the entirety of genomic data.
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页数:7
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