MaAsLin2: Microbiome Multivariate Association with Linear Models
tools public metagenomics bioconductor repeated-measures microbiome false-discovery-rate biobakery differential-abundance-analysis multiple-covariates r-tools
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#
false-discovery-rate
Here are 30 public repositories matching this topic...
Multiple hypothesis testing in Python
python statistics neuroscience data-visualization p-value reproducibility hypothesis-testing multiple-comparisons bonferroni sidak false-discovery-rate fdr permutation-algorithms fwer q-value random-field-theory two-group-model r-value
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- Python
Conformal Anomaly Detection & Change-Point Detection
outlier-detection uncertainty-quantification false-discovery-rate anomaly-detection martingale conformal-prediction change-point-detection exchangeability conformal-inference conformal-anomaly-detection conformal-martingale exchangeability-martingale
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- Python
Conditional calibration of conformal p-values for outlier detection.
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- Python
Benchmarking study of recent covariate-adjusted FDR methods
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- Jupyter Notebook
A workflow for metabolite identification and accurate profiling in multidimensional LC-IM-MS-DIA measurements. DOI: 10.5281/zenodo.
machine-learning metabolomics mass-spectrometry false-discovery-rate ion-mobility-spectrometry data-independent-acquisition
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Report various statistics stemming from a confusion matrix in a tidy fashion. 🎯
specificity tidy sensitivity kappa confusion-matrix rand fallout false-discovery-rate f1-score dice-coefficient precision-recall positive-predictive-value negative-predictive-value true-positive-rate true-negative-rate false-positive-rate false-negative-rate balanced-accuracy false-omission-rate peirce
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- R
Adjust p-values for multiple comparisons
matlab p-value octave statistical-tests octave-scripts matlab-functions octave-functions multiple-comparisons bonferroni sidak false-discovery-rate fdr
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- MATLAB
Knockoff-based analysis of GWAS summary statistics data
gwas genomics variable-selection false-discovery-rate fdr summary-statistics conditional-independence knockoffs
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- Julia
Variable Selection with Knockoffs
bioinformatics genomics lasso variable-selection feature-selection model-selection hypothesis-testing false-discovery-rate fdr conditional-independence conditional-independence-test knockoffs group-knockoffs multiple-knockoffs knockoff-filter
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- Julia
Large-scale Benchmarking of Microbial Multivariable Association Methods
benchmarking metagenomics repeated-measures microbiome false-discovery-rate differential-abundance-methods synthetic-dataset-generation biobakery differential-abundance-analysis multiple-covariates
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Reproducible experiments conducted in the paper 'Uncertainty Quantification in Anomaly Detection with Cross-Conformal p-Values'.
uncertainty-quantification uncertainty-estimation false-discovery-rate anomaly-detection benjamini-hochberg conformal-prediction conformal-inference conformal-anomaly-detection cross-conformal
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- Python
Sequential Hypothesis Testing
multiple-testing false-discovery-rate lord addis saffron sequential-testing lond alpha-investing online-fdr online-multiple-testing
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- Python
This repository includes the scripts to replicate the results of my paper entitled "A False Discovery Rate Approach to Optimal Volatility Forecasting Model Selection".
finance buckets econometrics false-discovery-rate model-confidence-set exchange-traded-funds volatility-modeling familywise-error-rate data-snooping-test
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- MATLAB
Large-scale Benchmarking of Microbial Multivariable Association Methods
benchmarking public metagenomics repeated-measures microbiome analyses benchmark-framework false-discovery-rate differential-abundance-analysis multiple-covariates
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A Python implementation of the "Controlling the False Discovery Rate via Knockoffs" paper from 2015, designed to provide tools for generating knockoff features and applying controlled variable selection techniques in high-dimensional data settings.
github gwas dimensionality-reduction gitkraken collaborate false-discovery-rate github-copilot knockoff knockoff-filter synthethic-data
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- Jupyter Notebook
The Julia package for estimating and testing a generalized linear mixed model with normal mixture random effects
statistics clustering gaussian-mixture-models hypothesis-testing false-discovery-rate sequential-tests generalized-linear-mixed-models
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- Julia
This project considers the use of p-value weighting to voxel-based lesion behavior mapping (VLSM) studies. Our methods are demonstrated on an aphasia study investigating which regions of the brain are associated with the severity of language impairment among stroke survivors.
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An empirical Bayes change point model for gene expression timecourse data.
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- Jupyter Notebook
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