Resampling adjusted likelihood and average estimate approaches for microarray data analysis
Keywords:
Multiple testing, likelihood approach, average estimate approachAbstract
The burgeoning field of genomics has reinvigorated interest in multiple-testing methods as it introduces new methodological and computational challenges. Whole genome microarray studies (e.g., differential expression, differential methylation, ChIP-chip) offer the possibility to test millions of traits in one genome. This article discusses the preterment of Adjusted likelihood approach and Average estimate approach (see Ewhida, Alammari and Ihwil, 2022; Jiang and Doerge, 2008) for estimating the proportion of true nulls π0 for CHIP-on-chip experiment data. Which has been done by Elnfati, Iles and Miller 2016, to express where the protein and DNA are bound, and the sample was taken from Drosophila fly (Fruit flies) in three replicates to determine the effect of HISTONE protein on fetus growth. The study demonstrates that, the Adjusted likelihood approach estimator performs very well.
Downloads
References
Cheng Y, Gao D, Tong T. 2015. Boas and variance reduction in estimating the proportion of true null hypotheses. Biostatistics; 16: 189-204.
Elnfati AH, Iles D, Miller D. 2016. Nucleosomal chromatin in the mature sperm of Drosophila melanogaster. Genomics Data; 7: 175-177.
Ewhida A, Alammari A and Ihiwil E. 2022. Adjusted likelihood approach to estimate the proportion of true null hypotheses in multiple tests.
Hualing Z, Hanfeng C. 2021. Estimating the Proportion of True Null Hypotheses: a Likelihood Approach. Global Journal of Science Frontier Research: F Mathematics and Decision Sciences; 21(5): 2249-4626.
Jiang H, Doerge R. 2008. Estimating the proportion of true null hypotheses for multiple comparisons. Cancer Informatics; 6: 26-32.
Langaas M, Lindqvist BH, Ferkingstad E. 2005. Estimating the proportion of true null hypotheses with application to DNA microarray data. J. R. Stat. Soc B; 67: 555-572.
Oluyemi O, Hanfeng C.2016. Estimating the proportion of true null hypotheses in multiple testing problems. Journal of Probability statistics, Article ID 3937056.
Mosig MO, Lipkin E, Galina K, et al. 2001. A Whole Genome Scan for Quantitative Trait Loci Affecting Milk Protein Percentage in Israeli-Holstein Cattle, by Means of Selective Milk DNA Pooling in a Daughter Design, Using an Adjusted False Discovery Rate Criterion. Genetics; 157: 1683 -1698.
Nettleton D, Hwang JTG, Caldo RA, Wise RP. 2006. Estimating the Number of true null hypotheses from a Histogram of p-values. Biological, and Environmental statistics: 11: 337 - 356.
Tong T, Feng Z, Hilton JS, Zhao H. 2013. Estimating the proportion of true null hypotheses using the pattern of observed p-value. J. Appl. Stat.; 40: 1949-1964.
Shimazaki H, Shinomoto S. 2007. A Method for Selecting the Bin Size of a Time Histogram. Neural Computation 19(6):1503-27.
Wu B, Guan Z, Zhao H. 2006. Parametric and nonparametric FDR estimation revisited. Biometrics; 62: 735-744.
Zhao H, Wu X, Zhang H, Chen H. 2012. Estimating the proportion of true null hypotheses in nonparametric exponential mixture model with application to the leukemia gene expression data. Communication in statistics-simulation and Computation; 41: 1580-1592.
English (original from the PDF):
Cheng Y, Gao D, Tong T. 2015. Boas and variance reduction in estimating the proportion of true null hypotheses. Biostatistics; 16: 189-204.
Elnfati AH, Iles D, Miller D. 2016. Nucleosomal chromatin in the mature sperm of Drosophila melanogaster. Genomics Data; 7: 175-177
Ewhida A, Alammari A and Ihiwil E. 2022. Adjusted likelihood approach to estimate the proportion of true null hypotheses in multiple tests.
Hualing Z, Hanfeng C. 2021. Estimating the Proportion of True Null Hypotheses: a Likelihood Approach. Global Journal of Science Frontier Research: F Mathematics and Decision Sciences; 21(5): 2249-4626
Jiang H, Doerge R. 2008. Estimating the proportion of true null hypotheses for multiple comparisons. Cancer Informatics; 6: 26-32.
Langaas M, Lindqvist BH, Ferkingstad E. 2005. Estimating the proportion of true null hypotheses with application to DNA microarray data. J. R. Stat. Soc B; 67: 555-572.
Oluyemi O, Hanfeng C.2016. Estimating the proportion of true null hypotheses in multiple testing problems. Journal of Probability statistics, Article ID 3937056.
Mosig MO, Lipkin E, Galina K, et al. 2001. A Whole Genome Scan for Quantitative Trait Loci Affecting Milk Protein Percentage in Israeli-Holstein Cattle, by Means of Selective Milk DNA Pooling in a Daughter Design, Using an Adjusted False Discovery Rate Criterion. Genetics; 157: 1683 -1698.
Nettleton D, Hwang JTG, Caldo RA, Wise RP. 2006. Estimating the Number of true null hypotheses from a Histogram of p-values. Biological, and Environmental statistics: 11: 337 - 356.
Tong T, Feng Z, Hilton JS, Zhao H. 2013. Estimating the proportion of true null hypotheses using the pattern of observed p-value. J. Appl. Stat.; 40: 1949-1964.
Shimazaki H, Shinomoto S. 2007. A Method for Selecting the Bin Size of a Time Histogram. Neural Computation 19(6):1503-27.
Wu B, Guan Z, Zhao H. 2006. Parametric and nonparametric FDR estimation revisited. Biometrics; 62: 735-744.
Zhao H, Wu X, Zhang H, Chen H. 2012. Estimating the proportion of true null hypotheses in nonparametric exponential mixture model with application to the leukemia gene expression data. Communication in statistics-simulation and Computation; 41: 1580-1592.
