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| Title: | Epistemological issues in omics and high-dimensional biology: give the people what they want |
| Author (s): | Mehta, Tapan S. Zakharkin, Stanislav O. Gadbury, Gary L. Allison, David B. |
| Department/Lab Affiliations: | Mathematics & Statistics |
| Keywords: | microarray experiments statistical genonics |
| Subject Terms: | Proteomics. |
| Issue Date: | 2006 |
| Publisher: | American Physiological Society |
| Citation: | Mehta, T.S., Zakharkin, S.O., Gadbury, G.L., and Allison, D.B. (2006), “Epistemological Issues in Omics and High-Dimensional Biology: Give the People What They Want,” Physiological Genomics. 28, 24 – 32. |
| Abstract: | Gene expression microarrays have been the vanguard of new analytic approaches in high-dimensional biology. Draft sequences of several genomes coupled with new technologies allow study of the influences and responses of entire genomes rather than isolated genes. This has opened a new realm of highly dimensional biology where questions involve multiplicity at unprecedented scales: thousands of genetic polymorphisms, gene expression levels, protein measurements, genetic sequences, or any combination of these and their interactions. Such situations demand creative approaches to the processes of inference, estimation, prediction, classification, and study design. Although bench scientists intuitively grasp the need for flexibility in the inferential process, the elaboration of formal supporting statistical frameworks is just at the very start. Here, we will discuss some of the unique statistical challenges facing investigators studying high-dimensional biology, describe some approaches being developed by statistical scientists, and offer an epistemological framework for the validation of proffered statistical procedures. A key theme will be the challenge in providing methods that a statistician judges to be sound and a biologist finds informative. The shift from family-wise error rate control to false discovery rate estimation and to assessment of ranking and other forms of stability will be portrayed as illustrative of approaches to this challenge. |
| Type: | Article - Journal text |
| In Title: | Physiological Genomics |
| Copyright Notice: | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. FULL COPYRIGHT INFORMATION: |
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| title | Epistemological issues in omics and high-dimensional biology: give the people what they want |
| contributor.author | Mehta, Tapan S. |
| contributor.author | Zakharkin, Stanislav O. |
| contributor.author | Gadbury, Gary L. |
| contributor.author | Allison, David B. |
| contributor.deptlab | Mathematics & Statistics |
| subject | microarray experiments |
| subject | statistical genonics |
| subject.LCSH | Proteomics. |
| date.issued | 2006 |
| publisher | American Physiological Society |
| identifier.citation | Mehta, T.S., Zakharkin, S.O., Gadbury, G.L., and Allison, D.B. (2006), “Epistemological Issues in Omics and High-Dimensional Biology: Give the People What They Want,” Physiological Genomics. 28, 24 – 32. |
| identifier.pub.URI | |
| description.abstract | Gene expression microarrays have been the vanguard of new analytic approaches in high-dimensional biology. Draft sequences of several genomes coupled with new technologies allow study of the influences and responses of entire genomes rather than isolated genes. This has opened a new realm of highly dimensional biology where questions involve multiplicity at unprecedented scales: thousands of genetic polymorphisms, gene expression levels, protein measurements, genetic sequences, or any combination of these and their interactions. Such situations demand creative approaches to the processes of inference, estimation, prediction, classification, and study design. Although bench scientists intuitively grasp the need for flexibility in the inferential process, the elaboration of formal supporting statistical frameworks is just at the very start. Here, we will discuss some of the unique statistical challenges facing investigators studying high-dimensional biology, describe some approaches being developed by statistical scientists, and offer an epistemological framework for the validation of proffered statistical procedures. A key theme will be the challenge in providing methods that a statistician judges to be sound and a biologist finds informative. The shift from family-wise error rate control to false discovery rate estimation and to assessment of ranking and other forms of stability will be portrayed as illustrative of approaches to this challenge. |
| type | Article - Journal |
| type.DCMIType | text |
| type.status | Final version |
| rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. |
| rights.URI | |
| relation.isPartOf | Physiological Genomics |
| date.accessioned | 2007-04-11T17:00:48Z |
| date.available | 2008-05-07T15:02:31Z |
| identifier.persist.URI |