ArticleProceedings of the National Academy of Sciences of the United States of America2012
Reducing system noise in copy number data using principal components of self-self hybridizations.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Detection of Copy Number Variants by Short Multiply Aggregated Sequence Homologies.The Journal of molecular diagnostics : JMD · 2020Article
- The role of de novo mutations in the genetics of autism spectrum disorders.Nature reviews. Genetics · 2014Review
- Article
- Copy Number Studies in Noisy Samples.Microarrays (Basel, Switzerland) · 2013Article
- Expanding probe repertoire and improving reproducibility in human genomic hybridization.Nucleic acids research · 2013Article
- Evaluation of calling algorithms for array-CGH.Frontiers in genetics · 2013Article
- Rare de novo germline copy-number variation in testicular cancer.American journal of human genetics · 2012Article
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Authors and funding
11 authors.
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Abstract
Genomic copy number variation underlies genetic disorders such as autism, schizophrenia, and congenital heart disease. Copy number variations are commonly detected by array based comparative genomic hybridization of sample to reference DNAs, but probe and operational variables combine to create correlated system noise that degrades detection of genetic events. To correct for this we have explored hybridizations in which no genetic signal is expected, namely "self-self" hybridizations (SSH) comparing DNAs from the same genome. We show that SSH trap a variety of correlated system noise present also in sample-reference (test) data. Through singular value decomposition of SSH, we are able to determine the principal components (PCs) of this noise. The PCs themselves offer deep insights into the sources of noise, and facilitate detection of artifacts. We present evidence that linear and piecewise linear correction of test data with the PCs does not introduce detectable spurious signal, yet improves signal-to-noise metrics, reduces false positives, and facilitates copy number determination.
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