FDR control

In high-throughput studies, hundreds to millions of hypotheses are typically tested. Statistical methods that control the false discovery rate (FDR) have emerged as popular and powerful tools for error rate control. While classic FDR methods use only p values as input, more modern FDR methods have been shown to increase power by incorporating complementary information as informative covariates to prioritize, weight, and group hypotheses.

21p vigalileogalilei 27-02-2022 9 1   Download

RNA sequencing studies with complex designs and transcript-resolution analyses involve multiple hypotheses per gene; however, conventional approaches fail to control the false discovery rate (FDR) at gene level. We propose stageR, a two-stage testing paradigm that leverages the increased power of aggregated gene-level tests and allows post hoc assessment for significant genes.

14p vialfrednobel 29-01-2022 11 1   Download

Accurate discovery of somatic variants is of central importance in cancer research. However, count statistics on discovered somatic insertions and deletions (indels) indicate that large amounts of discoveries are missed because of the quantification of uncertainties related to gap and alignment ambiguities, twilight zone indels, cancer heterogeneity, sample purity, sampling, and strand bias.

25p viarchimedes 26-01-2022 8 0   Download

Epigenome-wide association studies (EWAS), which seek the association between epigenetic marks and an outcome or exposure, involve multiple hypothesis testing. False discovery rate (FDR) control has been widely used for multiple testing correction. However, traditional FDR control methods do not use auxiliary covariates, and they could be less powerful if the covariates could inform the likelihood of the null hypothesis.

19p viarchimedes 26-01-2022 10 1   Download

In mass spectrometry-based proteomics, protein identification is an essential task. Evaluating the statistical significance of the protein identification result is critical to the success of proteomics studies. Controlling the false discovery rate (FDR) is the most common method for assuring the overall quality of the set of identifications.

10p vitzuyu2711 29-09-2021 12 1   Download

When many (up to millions) of statistical tests are conducted in discovery set analyses such as genome-wide association studies (GWAS), approaches controlling family-wise error rate (FWER) or false discovery rate (FDR) are required to reduce the number of false positive decisions.

10p viconnecticut2711 28-10-2020 10 1   Download

Procedures for controlling the false discovery rate (FDR) are widely applied as a solution to the multiple comparisons problem of high-dimensional statistics. Current FDR-controlling procedures require accurately calculated p-values and rely on extrapolation into the unknown and unobserved tails of the null distribution.

8p viconnecticut2711 28-10-2020 10 2   Download

In shotgun proteomics, database searching of tandem mass spectra results in a great number of peptide-spectrum matches (PSMs), many of which are false positives. Quality control of PSMs is a multiple hypothesis testing problem, and the false discovery rate (FDR) or the posterior error probability (PEP) is the commonly used statistical confidence measure.

17p vicolorado2711 22-10-2020 13 0   Download

Protein Kinase C (PKC) is a serine/threonine kinase that involved in controlling of many cellular processes such as cell proliferation and differentiation. We have observed previously that TPA (12-O-tetradecanoylphorbol 13acetate) induces cell cycle arrest in G0/G1 phase in human hepatoma HepG2 cells. However, is there any miRNA involved in PKCα mediated cell growth arrest is still unknown. Methods: We first surveyed 270 miRNA expression profiles in 20 pairs of human hepatoma tissues.

9p toshiba23 18-11-2011 44 3   Download