Release 33
(Aug 26, 2017):
A sum of 10,384 new QTL
added to the database. The current total number of QTL in the database: 136,137
[Breakdown by species -- Cattle: 99,652; Chicken: 7,812; Horse: 1,278;
Pig: 25,610; Sheep: 1,658; Rainbow trout: 127] (New additions less
obsolete/retracted ones: Catfish: 0; Cattle: 1,562; Chicken: 1,021;
Horse: 3; Pig: 7,655; Sheep: 143; Rainbow trout: 0 -- Net increase: 10,384).
(
This is a joint release with the 1st CorrDB release)
Database developments:
(1) A "permanent record locator" has been implemented in the AnimalQTLdb
to provide unique and stable links to all curated QTL/association
data for a publication. The new "permanent record locator" is a
replacement of a "URL Link" function introduced two years ago and
overcomes some of its shortcomings. It can be used by the authors to
refer to their published data, to provide proof of evidence of data
entry at the Animal QTLdb to journal editors/manuscript reviewers,
and to serve other purposes. All QTLdb curators/editors have access
to this tool for their curated data.
(2) The backend database structure and processes to handle curation of
QTL traits paralleled with VT/LPT/CMO ontology developments have been
undergoing further improvements in terms of facilitating curation of
trait terms modified by a diversified list of entities such as time,
anatomical locations, measurement methods, etc. This is in conjunction
with Animal Correlation Database (CorrDB) development. Stay tuned for
further news.
(3) We have registered 5 users for new curator accounts this year. We
encourage users to apply for an Animal QTLdb curator account to learn
how it may help their research, and to possibly be more involved in
database development. We love to work with you and appreciate your
useful ideas, suggestions, and/or requests, which all help to make the
database/tools more useful to the community.
(4) Periodic data checks on "on-hold", "conditionally released" (such as
QTL/associations marked with 'ss' SNPs), and "suspended" data have been
automated. This helps to make sure no sub-optimal data goes unnoticed.