A New Test Statistic Based on Shrunken Sample Variance for Identifying Differentially Expressed Genes in Small Microarray Experiments
Choosing an appropriate statistic and precisely evaluating the false discovery rate (FDR) are both essential for devising an effective method for identifying differentially expressed genes in microarray data. The t-type score proposed by Pan et al. (2003) succeeded in suppressing false positives by...
Main Authors: | Isao Yoshimura, Chikuma Hamada, Yasunori Sato, Akihiro Hirakawa |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2008-01-01
|
Series: | Bioinformatics and Biology Insights |
Subjects: | |
Online Access: | http://la-press.com/article.php?article_id=575 |
Similar Items
-
Estimating the False Discovery Rate Using Mixed Normal Distribution for Identifying Differentially Expressed Genes in Microarray Data Analysis
by: Chikuma Hamada, et al.
Published: (2007-01-01) -
Predicting the categories of colon cancer using microarray data and nearest shrunken centroid
by: Mehri Khoshhali, et al.
Published: (2015-10-01) -
A New Test Statistic Based on Shrunken Sample Variance for Identifying Differentially Expressed Genes in Small Microarray Experiments
by: Akihiro Hirakawa, et al.
Published: (2008-01-01) -
A New Test Statistic Based on Shrunken Sample Variance for Identifying Differentially Expressed Genes in Small Microarray Experiments
by: Akihiro Hirakawa, et al.
Published: (2008-02-01) -
Robust gene selection methods using weighting schemes for microarray data analysis
by: Suyeon Kang, et al.
Published: (2017-09-01)