Anonymized tissue samples remaining after the diagnostic evaluation were used in this project in the context of a study ("Molecular neuropathologic investigation of neurodegenerative diseases"; collection of biological samples named "CJD KIN-Biobank") approved by the Ethics Committee of the Medical University of Vienna (No. 396/2011) and followed the principles of the Declaration of Helsinki.
In summary, a database containing genomic information for approximately 900 cell lines, which are mostly chosen from the Chromosomal Aberrations Collection and Heritable Diseases Collection of the NIGMS repository and intensively analyzed by karyotype, FISH, and CMA assays at the Coriell Institute, has been constructed.
The majority of these samples were chosen from the Chromosomal Aberrations and Heritable Diseases collections.
Many clinical laboratories and research institutes use NIGMS Repository cell lines and/or DNA samples, particularly samples from the Chromosomal Aberrations and Heritable Diseases collections, as standards or reference materials to develop and validate their CMA assays.
Recently, approximately 900 cell lines, mostly chosen from the Chromosomal Aberrations and Heritable Diseases collections, have been further characterized in detail at the Coriell Institute using the Affymetrix Genome-Wide Human SNP Array 6.0 to detect copy number variations and copy number neutral loss of heterozygosity.
This editorial introduces the F1000Research rare disease collection.
To date, the Krabbe disease collection within the Biobank includes 36 families.
Traditionally, these patterns are tracked by active surveillance for invasive disease, collection of isolates, and centralized susceptibility testing.
Sera from Norwegian APECED and Addison disease collection, the Finnish APECED collection, a Sardinian APECED and unaffected heterozygous relative cohort, and some U.S. APECED patient sera and SLE sera from Tartu University Clinic serum bank were used for cytokine measurements.
We show for the first time how HPO annotation can be used to describe the phenotypes of individual cases within a large rare disease collection and how a novel statistical clustering approach using HPO data guides gene discovery.
Policymakers seduced by the rationalist appeal of technology may conflate the management of illness (ie, everything a person needs to do in order to live well with a condition) with the much narrower set of tasks linked to the management of disease (collection of a more limited data set of biometric data such as blood pressure, weight or peak expiratory flow rate).
