| bi.npmle | Bivariate NPMLE |
| expit | Expit function |
| ldd | Latent dependency detection |
| logit | Logit function |
| maxtest | Max test for detecting simultaneous signals |
| neb.predict | Nonparametric empirical Bayes classifier without annotations; prediction |
| neb.train | Nonparametric empirical Bayes classifier without annotations; training |
| nebula.bin.predict | Nonparametric empirical Bayes classifier using latent annotations: binary indicators; prediction |
| nebula.bin.train | Nonparametric empirical Bayes classifier using latent annotations: binary indicators; training |
| nebula.chisq.bin.predict | Nonparametric empirical Bayes classifier using latent annotations: chi-square test statistics and binary indicators; prediction |
| nebula.chisq.bin.train | Nonparametric empirical Bayes classifier using latent annotations: chi-square test statistics and binary indicators; training |
| nebula.chisq.predict | Nonparametric empirical Bayes classifier using latent annotations: chi-square test statistics; prediction |
| nebula.chisq.train | Nonparametric empirical Bayes classifier using latent annotations: chi-square test statistics; training |
| nebula.predict | Nonparametric empirical Bayes classifier using latent annotations: wrapper function; predict |
| nebula.train | Nonparametric empirical Bayes classifier using latent annotations: wrapper function; training |
| nfsdr | Nonparametric false simultaneous discovery rate control |
| nfsdr2 | Nonparametric false simultaneous discovery rate control, two thresholds |
| nfsdr2_all | Nonparametric false simultaneous discovery rate control, two thresholds - report all thresholds |
| prs.predict | Polygenic risk score; prediction |
| prs.predict.cv | Polygenic risk score; prediction for classifier trained with CV |
| prs.train | Polygenic risk score (given only allele frequencies); training |
| prs.train.cv | Polygenic risk score (given only allele frequencies); training with CV |
| tri.npmle | Trivariate NPMLE |
| uni.npmle | Univariate NPMLE |