Gaining Weights... and Feeling Good about It!

Ernst Wit; Vilda Purutcuoglu; Lucy O'Donovan; Ximin Zhu

Gaining Weights... and Feeling Good about It!

Ernst Wit, Vilda Purutcuoglu, Lucy O'Donovan, Ximin Zhu

Probability and Statistics

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Abstract

Two problems that dog current microarrays analyses are (i) the relatively arbitrary nature of data preprocessing and (ii) the inability to incorporate spot quality information in inference except by all-or-nothing spot filtering. In this chapter we propose an approach based on using weights to overcome these two problems. The first approach uses weighted p-values to make inference robust to normalization and the second approach uses weighted spot intensity values to improve inference without any filtering.

Original language	English
Title of host publication	EPRINTS-BOOK-TITLE
Publisher	University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science
Number of pages	8
Publication status	Published - 2007

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title = "Gaining Weights... and Feeling Good about It!",

abstract = "Two problems that dog current microarrays analyses are (i) the relatively arbitrary nature of data preprocessing and (ii) the inability to incorporate spot quality information in inference except by all-or-nothing spot filtering. In this chapter we propose an approach based on using weights to overcome these two problems. The first approach uses weighted p-values to make inference robust to normalization and the second approach uses weighted spot intensity values to improve inference without any filtering.",

author = "Ernst Wit and Vilda Purutcuoglu and Lucy O'Donovan and Ximin Zhu",

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AU - Wit, Ernst

AU - Purutcuoglu, Vilda

AU - O'Donovan, Lucy

AU - Zhu, Ximin

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N2 - Two problems that dog current microarrays analyses are (i) the relatively arbitrary nature of data preprocessing and (ii) the inability to incorporate spot quality information in inference except by all-or-nothing spot filtering. In this chapter we propose an approach based on using weights to overcome these two problems. The first approach uses weighted p-values to make inference robust to normalization and the second approach uses weighted spot intensity values to improve inference without any filtering.

AB - Two problems that dog current microarrays analyses are (i) the relatively arbitrary nature of data preprocessing and (ii) the inability to incorporate spot quality information in inference except by all-or-nothing spot filtering. In this chapter we propose an approach based on using weights to overcome these two problems. The first approach uses weighted p-values to make inference robust to normalization and the second approach uses weighted spot intensity values to improve inference without any filtering.

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BT - EPRINTS-BOOK-TITLE

PB - University of Groningen, Johann Bernoulli Institute for Mathematics and Computer Science

ER -

Gaining Weights... and Feeling Good about It!

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