Christopher A Cassa
Affiliation: Massachusetts Institute of Technology
- A novel, privacy-preserving cryptographic approach for sharing sequencing dataChristopher A Cassa
Division of Genetics, Brigham and Women s Hospital, Boston, MA 02215, USA
J Am Med Inform Assoc 20:69-76. 2013..We present a cryptographic scheme to securely transmit externally generated sequence data which does not require any patient identifiers, public key infrastructure, or the transmission of passwords...
- Disclosing pathogenic genetic variants to research participants: quantifying an emerging ethical responsibilityChristopher A Cassa
Children s Hospital Informatics Program, Children s Hospital Boston, Boston, Massachusetts 02115, USA
Genome Res 22:421-8. 2012..Additionally, if the growth rate from the previous 4 yr continues, we estimate that the total number of disease-associated variants will grow 37% over the next 4 yr...
- Re-identification of home addresses from spatial locations anonymized by Gaussian skewChristopher A Cassa
Children s Hospital Informatics Program, Children s Hospital Boston, Boston, MA, USA
Int J Health Geogr 7:45. 2008..If several such versions are available, each can be used to incrementally refine estimates of the original geocoded location...
- Automated validation of genetic variants from large databases: ensuring that variant references refer to the same genomic locationsMark Y Tong
Harvard Medical School, Boston, MA 02115, USA
Bioinformatics 27:891-3. 2011..The frequency of unresolved mutation annotations varied widely among the databases, ranging from 4 to 23%. A taxonomy of primary causes for unresolved mutations was produced...
- Large Numbers of Genetic Variants Considered to be Pathogenic are Common in Asymptomatic IndividualsChristopher A Cassa
Brigham and Women s Hospital, Division of Genetics Boston, Massachusetts Division of Genetics, Harvard Medical School, Boston, Massachusetts Massachusetts Institute of Technology, Cambridge, Massachusetts Broad Institute of Harvard and MIT, Cambridge, Massachusetts
Hum Mutat 34:1216-20. 2013..01 (4.6%) and 2,837 variants with MAF ≥ 0.05 (3.5%). This indicates that many of these variants may be erroneous findings or have lower penetrance than previously expected. ..
- A context-sensitive approach to anonymizing spatial surveillance data: impact on outbreak detectionChristopher A Cassa
Children s Hospital Boston, Informatics Program Mandl Group, 1 Autumn Street, 721, Boston, MA 02215 5362 USA
J Am Med Inform Assoc 13:160-5. 2006..Further, we measure the impact of the skew on detection of spatial clustering as measured by a spatial scanning statistic...
- An unsupervised classification method for inferring original case locations from low-resolution disease mapsJohn S Brownstein
Children s Hospital Informatics Program at the Harvard MIT Division of Health Sciences and Technology, 1 Autumn St, Boston, MA, USA
Int J Health Geogr 5:56. 2006..In this report, a method is presented to evaluate whether patient privacy is being breached in the publication of low-resolution disease maps...