Автор: Administrator
Четверг, 13 марта 2014, 18.00
МГУ, лаб. корпус Б (факультет биоинженерии и биоинформатики), к. 221.
Инна Дубчак
Lawrence Berkeley National Laboratory
Visualization of genomic data: results, challenges, and open questions
As our ability to generate huge amounts of sequencing data continues to
increase, data analysis is becoming the rate-limiting step in genomics
studies. Visualization tools facilitate analysis tasks by enabling
researchers to explore, interpret and manipulate their data. There are a
number of graphical methods designed for the analysis of de novo
sequencing assemblies and read alignments, genome browsing, comparative
genomics, etc. All available visualization tools have their strengths
and limitations.
We will highlight new challenges in visualization that are not only a
consequence of the sheer volume and complexity of genomic data, but also
its increasing utility outside genomics research. Traditional genome
visualization approaches do not meet the needs of emerging fields such
as medical genomics and metagenomics, and new paradigms are needed.
Clinicians require efficient presentation of critical information in
order to form a diagnosis, and biobanks and population studies produce
detailed phenotype descriptions too complex to represent as a heat map
or other form of tabular visualization. These data can reveal the effect
of spatial and environmental factors on population and ecosystem
structure, but interactive, extensible, easy to use tools must be
provided to enable their analysis and exploration.
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