biostudies-literatureZhang LCCTSNIH/NCI CCSGCPRITMD Anderson Moon Shot ProgramsNHLBI NIH HHSProstate Cancer SPORENIH R01126https://www.ebi.ac.uk/biostudies/studies/S-EPMC7972227biostudies-literatureUnknown22(1)<h4>Background</h4>Identification of features is a critical task in microbiome studies that is complicated by the fact that microbial data are high dimensional and heterogeneous. Masked by the complexity of the data, the problem of separating signals (differential features between groups) from noise (features that are not differential between groups) becomes challenging and troublesome. For instance, when performing differential abundance tests, multiple testing adjustments tend to be overconservative, as the probability of a type I error (false positive) increases dramatically with the large numbers of hypotheses. Moreover, the grouping effect of interest can be obscured by heterogeneity. These factors can incorrectly lead to the conclusion that there are no differences in the microbiome BMC bioinformaticsProgPerm: Progressive permutation for a dynamic representation of the robustness of microbiome discoveries.PMC7972227P30CA0166725UL1TR000371HL124112R01 HL124112P50CA140388RR160089RP160693Peterson CBDo KAJenq RRZhang LShi YfalseProgPerm: Progressive permutation for a dynamic representation of the robustness of microbiome discoveries.<h4>Background</h4>Identification of features is a critical task in microbiome studies that is complicated by the fact that microbial data are high dimensional and heterogeneous. Masked by the complexity of the data, the problem of separating signals (differential features between groups) from noise (features that are not differential between groups) becomes challenging and troublesome. For instance, when performing differential abundance tests, multiple testing adjustments tend to be overconservative, as the probability of a type I error (false positive) increases dramatically with the large numbers of hypotheses. Moreover, the grouping effect of interest can be obscured by heterogeneity. These factors can incorrectly lead to the conclusion that there are no differences in the microbiome 2021-01-01T00:00:00Z2021 Mar2025-04-22T08:16:31.399Z2024-11-07T14:11:34.117ZS-EPMC79722273373101610.1186/s12859-021-04061-3