| Coding SNPs as intrinsic markers for sample tracking in large-scale transcriptome studies. | |
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MedLine Citation:
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PMID: 22668418 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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Large-scale transcriptome profiling in clinical studies often involves assaying multiple samples of a patient to monitor disease progression, treatment effect, and host response in multiple tissues. Such profiling is prone to human error, which often results in mislabeled samples. Here, we present a method to detect mislabeled sample outliers using coding single nucleotide polymorphisms (cSNPs) specifically designed on the microarray and demonstrate that the mislabeled samples can be efficiently identified by either simple clustering of allele-specific expression scores or Mahalanobis distance-based outlier detection method. Based on our results, we recommend the incorporation of cSNPs into future transcriptome array designs as intrinsic markers for sample tracking. |
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Authors:
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Weihong Xu; Hong Gao; Junhee Seok; Julie Wilhelmy; Michael N Mindrinos; Ronald W Davis; Wenzhong Xiao |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: BioTechniques Volume: 52 ISSN: 1940-9818 ISO Abbreviation: BioTechniques Publication Date: 2012 Jun |
Date Detail:
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Created Date: 2012-06-06 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8306785 Medline TA: Biotechniques Country: England |
Other Details:
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Languages: eng Pagination: 386-8 Citation Subset: IM |
Affiliation:
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Stanford Genome Technology Center, Stanford University, Palo Alto, CA, USA. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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