NOPresentation.ppt

Report
PhenCode: Connecting
genome to phenotype
Belinda Giardine
Cathy Riemer
Ross Hardison
Webb Miller
Jim Kent
PSU and UCSC
Aims of PhenCode
 Connect genome data (evolutionary
history, function) with phenotype and
clinical data
 Facilitate better understanding of the
associations between genotype and
phenotype
 Generate novel explanations for
mechanisms of disease
Connectivity in PhenCode
PhenCode tracks
See rest of example on poster 1201C
Current data in PhenCode
databases
ARdb
BGMUT
BTKbase
CFMDB
HbVar
PAHdb
SRD5A2
Swiss-Prot
TOTAL
#entries
329
1605
512
1,400
1,530
513
42
22,454
28,382
links to source
no
yes
yes
yes
yes
yes
no
yes
Any LSDB with clearly defined
mutations can join PhenCode
 The essential information is the same as for HGVS style
nomenclature or entry in Central Repository
 Reference sequence
 Position(s) in reference sequence
 The change in amino acid or nucleotide sequence
 This information, in combination with alignments
between the reference sequence and the chromosome
sequence, gives all the required information to add the
mutations to the track.
 Additional attributes such as the phenotype associated
with the variant make the track even more useful.
URLs and Acknowledgements

URLS
genome.ucsc.edu
 www.bx.psu.edu


UCSC and PSU

Work was supported by NIH grants
HG002238 (WM) and DK65806 (RH), NHGRI
grant 1P41HG02371 (WJK)
Work accomplished




Tools for converting from reference sequence
coordinates to genome coordinates
Table schema fast enough for Genome Browser,
and general enough to handle varied fields for
details page
Customized detail page, track coloring and
filtering
Position box searches on HGVS names and
common names for variants.
Composition of Locus Variants track
Work in progress




Add more Locus Specific Databases
Expand capabilities of tools used in
mapping variants to genome
Documentation
Automation of track updates

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