Algorithms for Characterizing Copy Number Variation in Human Genome

Not long ago, it was discovered that individuals may differ in copy numbers of their genes, meaning that a segment of DNA may have more or less copies than usual in an individual's chromosome. Recent research suggests that these variations are associated with many diseases including Autism and Schizophrenia. Copy number variation (CNV) in somatic cells also underly various cancers. Copy numbers are usually identified using SNP microarrays, however, short-read sequence data is emerging as an important resource for characterizing structural variation in human genome. As an interdisciplinary group of researchers at Case Western Reserve University, we develop algorithms for fast and accurate identification of rare and de novo CNVs, as well as copy number polymorphisms (CNPs) and other forms of genomic variation (e.g., loss of heterozygosity) from these two data sources. We further extend these algorithms to identify small indels with applications to error correction in next generation sequencing, fine tuning of the alignment of short reads to the reference human genome, and characterization of tissue heterogeneity. With a view to enabling personalized genomics applications, we apply these algorithms to the identification of copy number variants, as well as single nucleotide polymorphisms, genes, genetic interactions, pathways, and networks that are associated with complex diseases. Copy Number Variation


  • LOQUM: A logistic regression based algorithm for recalibrating the mapping quality of short-read sequence alignments.

  • SEAL: A comprehensive short read sequencing simulation and alignment tool evaluation suite implemented in Java.

  • COKGEN: An R package for optimization-based identification of rare and de novo copy number variants from SNP microarray data.


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Katie Wilkins

Undergraduate Student, Computer Science/Biochemistry
(Now Ph.D. student at Cornell University)

Matthew Ruffalo

Ph.D. Student, Computer Science

Daniel Savel

Ph.D. Student, Computer Science

Marzieh Ayati

Ph.D. Student, Computer Science

Gokhan Yavas

Ph.D. Student, Computer Science
(Now post-doctoral fellow at Case Comprehensive Cancer Center)

Thomas LaFramboise

Associate Professor, Genetics & Genome Sciences

Mehmet Koyuturk

Associate Professor, Electrical Engineering & Computer Science


This project is supported by National Science Foundation Award IIS-0916102.