Powerful and robust non-parametric association testing for microbiome data via a zero-inflated quantile approach (ZINQ) is a research paper published in Microbiome (2021). On theSindex it has a DataRank of 0. It has been cited 43 times.
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National Institutes of Health
Grant: R01-GM129512
National Heart, Lung, and Blood Institute
Grant: HHSN268201800003I, HHSN268201800004I, HHSN268201800005I, HHSN268201800006I, HHSN268201800007I
National Institute on Aging
Grant: K01-HL127159
NHLBI NIH HHS
Grant: HHSN268201800007I
NHLBI NIH HHS
Grant: HHSN268201800005I
NIGMS NIH HHS
Grant: R01 GM129512
NHLBI NIH HHS
Grant: HHSN268201800003I
NHLBI NIH HHS
Grant: HHSN268201800004I
NHLBI NIH HHS
Grant: HHSN268201800006I
NHLBI NIH HHS
Grant: K01 HL127159
NHLBI NIH HHS
Grant: R01 HL155417
National Institutes of Health
Grant: 6R01HL155417-02
Statistical Methods for Large Scale Microbiome Studies of Cardiovascular Disease Risk
National Institutes of Health
Grant: 5R01GM129512-04
Joint Analysis of Microbiome and Other Genomic Data Types
National Institutes of Health
Grant: 5K01HL127159-03
A Novel Gut Microbial-Dependent Nutrient Metabolite and Atherosclerosis
The Hope Foundation
FWCI
2.39
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Additional file 1 of Powerful and robust non-parametric association testing for microbiome data via a zero-inflated quantile approach (ZINQ)
Additional file 1 of Powerful and robust non-parametric association testing for microbiome data via a zero-inflated quantile approach (ZINQ)
Additional file 2 of A comprehensive evaluation of microbial differential abundance analysis methods: current status and potential solutions
Additional file 2 of A comprehensive evaluation of microbial differential abundance analysis methods: current status and potential solutions
Additional file 1 of A robust and transformation-free joint model with matching and regularization for metagenomic trajectory and disease onset
Additional file 1 of A robust and transformation-free joint model with matching and regularization for metagenomic trajectory and disease onset
Additional file 1 of Accommodating multiple potential normalizations in microbiome associations studies
Additional file 1 of Accommodating multiple potential normalizations in microbiome associations studies
Additional file 1 of MIDASim: a fast and simple simulator for realistic microbiome data
Additional file 1 of MIDASim: a fast and simple simulator for realistic microbiome data
Additional file 1 of A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies
Additional file 1 of A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies
Additional file 2 of A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies
Additional file 2 of A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies
Additional file 3 of A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies
Additional file 3 of A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies
Additional file 4 of A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies
Additional file 4 of A realistic benchmark for differential abundance testing and confounder adjustment in human microbiome studies
Additional file 2 of A robust and transformation-free joint model with matching and regularization for metagenomic trajectory and disease onset
Additional file 2 of A robust and transformation-free joint model with matching and regularization for metagenomic trajectory and disease onset