Detecting Copy Number Variations Using Cumulative Plots
Author Information
Author(s): Li Wentian, Lee Annette, Gregersen Peter K
Primary Institution: The Robert S Boas Center for Genomics and Human Genetics, Feinstein Institute for Medical Research, North Shore LIJ Health System
Hypothesis
Can cumulative plots effectively detect regions of copy number variation and alteration in genomic data?
Conclusion
Cumulative plots are an intuitive and effective tool for detecting copy number variations and alterations, especially in smaller regions.
Supporting Evidence
- Cumulative plots can detect a 9 Mb hemizygous deletion and a 1 Mb homozygous deletion on chromosome 13.
- The method is scale-free and does not require a fixed window size for analysis.
- Cumulative plots can delineate the borders of CNV/CNA regions with higher accuracy.
Takeaway
This study shows that we can use special graphs called cumulative plots to find changes in DNA that might be linked to diseases, even when those changes are very small.
Methodology
The study used cumulative plots to analyze SNP genotyping data from a chronic lymphocytic leukemia patient to detect copy number variations.
Limitations
The method's effectiveness may vary based on the quality of DNA samples and the distribution of SNPs.
Participant Demographics
One chronic lymphocytic leukemia patient.
Digital Object Identifier (DOI)
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