上述的3个函数各自的功能是，fdr_od是根据设置的阈值进行一次的FDR估计；fdrTbl是根据设置的上下界限（-log10（P）的值），按照增加的步长，逐步的计算对应阈值下的FDR；FDRplot是将fdrTbl的结果可视化。

This function can be used to estimate FDR, corresponding confidence interval, and pi0, the proportion of true null hypotheses, given a selected significance threshold, and results from permuted data. fdr_od ( obsp , permp , pnm , ntests , thres , cl = 0.95 , c1 = NA )

This function can be used to estimate FDR, corresponding confidence interval, and pi0, the proportion of true null hypotheses, given a selected significance threshold, and results from permuted data.

The function fdr_od() can be used to estimate FDR and and a confidence interval along with pi0, the proportion of true null hypotheses, given a selected significance threshold. The function fdrTbl()uses fdr_od() to create a table of results over a sequence of …

2022年10月18日 · This function can be used to estimate FDR, corresponding confidence interval, and pi0, the proportion of true null hypotheses, given a selected significance threshold, and results from permuted data. Usage fdr_od( obsp, permp = NULL, pnm, ntests, thres, cl = 0.95, c1 = NA, meff = TRUE, seff = TRUE, mymat, nperms = 5 ) Arguments

The function fdr_od() can be used to estimate FDR and and a confidence interval along with pi0, the proportion of true null hypotheses, given a selected significance threshold. The function fdrTbl()uses fdr_od() to create a table of results over a sequence of …

2024年6月29日 · Permutation-Based FDR and Confidence Interval Description. This function can be used to estimate FDR, corresponding confidence interval, and pi0, the proportion of true null hypotheses, given a selected significance threshold, and results from permuted data. Usage fdr.od(obsp, permp, pnm, ntests, thres, cl=.95, od=NA) Arguments

FDR functions for permutation-based estimators, including pi0 as well as FDR confidence intervals. The confidence intervals account for dependencies between tests by the incorporation of an overdispersion parameter, which is estimated from the permuted data. Also included are options for an analog parametric approach.

fdrTbl calls fdr_od for a series of discovery thresholds. Output from fdrTbl() can be used for FDRplot() input. If correct = "BH", then confidence intervals will be corrected according to the thresholds specified by lowerbound, upperbound, and incr. Thresholds will be selected if FDR is determined to be significantly different than 1.

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