University of Pittsburgh

David Gerard Peters

Tianjiao Chu

David Finegold

Lisa Ann Pan

Computational techniques are disclosed for using methylation profiles to classify the medication condition of a person. Initial sequence data is obtained containing sequences of an initial set of nucleic acids from a biological sample of a person. The initial sequence data is filtered to generate filtered sequence data that describes sequences of a filtered subset of nucleic acids from the biological sample. A methylation profile is determined for the filtered subset of nucleic acids from the biological sample. The methylation profile can be processed to determine a likelihood that the person has the specified medical condition. The system outputs an indication of the likelihood that the person has the specified medical condition.

Computational filtering of methylated sequence data for predictive modeling

Methods are provided for detecting an aneuploidy in a fetus. These methods can be used to detect trisomy 13, 8 or 21, amongst other aneupoloidies. In some embodiments, the methods include selectively purifying fetal DNA from a maternal biological sample using the methylation status of a CpG containing genomic sequence and genotyping the fetus using the purified fetal DNA, thereby detecting aneuploidy in the fetus.

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Pittsburgh, PA, United States of America

David Gerard Peters