التفاصيل البيبلوغرافية
| العنوان: |
Approaches to multiplicity issues in complex research in microarray analysis |
| المؤلفون: |
Yekutieli, Daniel, Reiner‐Benaim, Anat, Benjamini, Yoav, Elmer, Gregory I., Kafkafi, Neri, Letwin, Noah E., Lee, Norman H. |
| المصدر: |
Statistica Neerlandica ; volume 60, issue 4, page 414-437 ; ISSN 0039-0402 1467-9574 |
| بيانات النشر: |
Wiley |
| سنة النشر: |
2006 |
| المجموعة: |
Wiley Online Library (Open Access Articles via Crossref) |
| الوصف: |
The multiplicity problem is evident in the simplest form of statistical analysis of gene expression data – the identification of differentially expressed genes. In more complex analysis, the problem is compounded by the multiplicity of hypotheses per gene. Thus, in some cases, it may be necessary to consider testing millions of hypotheses. We present three general approaches for addressing multiplicity in large research problems. (a) Use the scalability of false discovery rate (FDR) controlling procedures; (b) apply FDR‐controlling procedures to a selected subset of hypotheses; (c) apply hierarchical FDR‐controlling procedures. We also offer a general framework for ensuring reproducible results in complex research, where a researcher faces more than just one large research problem. We demonstrate these approaches by analyzing the results of a complex experiment involving the study of gene expression levels in different brain regions across multiple mouse strains. |
| نوع الوثيقة: |
article in journal/newspaper |
| اللغة: |
English |
| DOI: |
10.1111/j.1467-9574.2006.00343.x |
| الإتاحة: |
https://doi.org/10.1111/j.1467-9574.2006.00343.xTest |
| حقوق: |
http://onlinelibrary.wiley.com/termsAndConditions#vorTest |
| رقم الانضمام: |
edsbas.A6980A2 |
| قاعدة البيانات: |
BASE |
