Paper progress – started hacking at the new intro. Looks like related work will be pretty sparse – maybe pull in CAESAR as “in the style of but completely different” , just like GO overrepresentation as being “kinda the same but we have way more detail”. Maybe call it MeSH Overrepresentation?
VanBUG had a pair of excellent speakers today.
Parisa Shooshtari presented a variation of spectral clustering (spectral == graph cut) for very large number of points (when polynomial just doesn’t cut it). Idea is that uniform random sampling won’t sample very often from sparsely covered areas – and perhaps you don’t want to lose the really sparse areas. The Fix? Faithful sampling, where you grab points at random, but when you take a point, you also take all points “nearby” (some fixed distance) – this forms a “community” represented by the point. Then you make a graph of the representatives – you lose some info, but since you can save the community of each point, you can make the edges in the graph be some kind of “average weight” of all the points in the community. Might be fancier if you could somehow do some kind of “sub-clustering” to form the communities – some kind of “fractal clustering”.
Evan Eichler from UWash talked a lot about copy number variations – his def was really geared towards variation > 1kb. Two main types: Large, rare, bumps lots of genes (but can’t stay all that long in the population?). vs. Multi-copy common susceptibility/risk factor.
Usually CNV are thought to be the product of highly repetitive/similar/duplicated sequence + recombination error (and for some reason humans/ape family have a lot more of this than other species)
Ideal technology will get copy #, content (sequence) and structure (part of a gene/promoter/etc)
Current tech maps sequence to genome looking for things like unusual distance between paired end reads (sequencing/ArrayCGH/microarray) – but different technologies find different variation == no tech can cover it all yet (or lots of error?)
mrFAST – BLAST style searching of genomes (to map the variation)
Variation Hunter – uses mrFAST to map, then set cover to minimise …
Nexgen sequences – different bias, as no biased to shorter cnvs/more difficulty mapping (since there’s more sequence to map) (more false positives? more potential matches?)
Can use read depth to get copy number (e.g. shotgun sequencing reads, mapped to our ref. genome). More reads (corrected for paralogues, homologs etc) == more CNV.
Use multiple seq align on copies to find unique seq, which can then be used to search for the presence of these CNVs.
All in all, really liked this talk. Went longer than usual VanBUG, and speaker was really quiet/mike was busted, but even so didn’t have any trouble following.
[VanBUG] reminder Wed, Jan 13, 6pm – Evan Eichler, Human Genome Structural Variation, Disease and Evolution
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Stefanie Butland
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show details Jan 12 (1 day ago)
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Please post seminar poster available at http://www.vanbug.org
—————————————————–
Next VanBUG happens *Wednesday*, January 13 at 6pm.
This session is co-hosted with MITACS ( http://www.mitacs.ca). Seminar is
followed by pizza, refreshments and great networking.
*Intro speaker* (10mins): Parisa Shooshtari, PhD Candidate (Gupta and
Brinkman labs), School of Computing Science, SFU
Title: Faithful Sampling for Spectral Clustering to Analyse High Throughput Flow Cytometry Data
*Featured speaker*: Evan Eichler, Professor, Department of Genome
Sciences, HHMI, University of Washington, Seattle
http://eichlerlab.gs.washington.edu/
Human Genome Structural Variation, Disease and Evolution
Structural variation of the genome is an important aspect in our
understanding of human disease and evolution. Accurately characterizing
such variation an unmet challenge of both bioinformatics and genomics. I
will focus on the genome-wide discovery, analysis and distribution of
copy-number variants (CNV) and inversion polymorphisms within human and
great ape species. I will present methods to accurately resolve the
copy, content and structure of these regions based on traditional and
next-generation sequence datasets. I will discuss our efforts to
characterize regions of the genome that are prone to recurrent deletion,
duplication and inversion and provide examples of their importance as
recurrent and de novo sources of neuropsychiatric and neurocognitive
disease.
Location:
675 West 10th Avenue
Gordon and Leslie Diamond Family Theatre
BC Cancer Agency
Date/Time:
Start Date: 01/13/2010
Start Time: 6:00 PM
End Time: 7:30 PM
Contact Name:
Stefanie Butland
dev@vanbug.org
http://vanbug.org
VanBUG is generously sponsored by the CIHR/MSFHR Bioinformatics Training
Program, MITACS, GenomeBC, IBM and the Canadian Bioinformatics Workshops
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