Z test update

.Rbuildignore

@@ -5,3 +5,6 @@
 ^.*\.gitignore
 ^LICENSE\.md$
 ^.git*$
+^_pkgdown\.yml$
+^docs$
+^pkgdown$

.github/workflows/pkgdown.yaml

@@ -2,7 +2,7 @@
 # Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
 on:
   push:
-    branches: [main, master]
+    branches: main
   pull_request:
   release:
     types: [published]

.gitignore

@@ -5,3 +5,4 @@
 doc
 Meta
 inst/doc
+docs

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: leapR
 Title: Layered enrichment analysis of pathways R
-Version: 0.99.7
+Version: 0.99.8
 Authors@R: c(
     person("Sara", "Gosline", email = "sara.gosline@pnnl.gov", role = c('aut',"cre"), comment = c(ORCID = "0000-0002-6534-4774")),
     person("Jason", "McDermott", email = "jason.mcdermott@pnnl.gov", role = "aut"),

README.md

@@ -5,14 +5,11 @@ Layered Enrichment Analysis of Pathways in R (leapR) a tool that carries out sta
 ## Install
 leapR is available through Bioconductor repository here
 
-```{r install}
-
+```
 if (!require("BiocManager", quietly = TRUE))
     install.packages("BiocManager")
 BiocManager::install(version = "3.21")
-
 BiocManager::install('BiocStyle')
-
 BiocManager::install('leapR')
 ```
 

_pkgdown.yml

@@ -0,0 +1,4 @@
+url: https://pnnl-github.io/leapR
+template:
+  bootstrap: 5
+

catalog-info.yaml

@@ -0,0 +1,28 @@
+apiVersion: backstage.io/v1alpha1
+kind: Component
+metadata:
+  name: leap-r
+  title: Leap R
+  description: Layered Enrichment Analysis of Pathways in R (leapR) a tool that carries out statistical enrichment analysis on single- or multi-omics data.
+  annotations:
+    # Conditional host-specific annotations rendered to avoid empty-string values that fail catalog validation.
+    github.com/project-slug: pnnl/leapR
+  links:
+    - title: Leap R Repository
+      url: https://github.com/pnnl/leapR
+    - title: Leap R Publication
+      url: https://pubs.acs.org/doi/full/10.1021/acs.jproteome.0c00963
+  tags:
+    - R
+spec:
+  type: api
+  owner: user:default/sara.gosline_pnnl.gov # Sara Gosline project lead
+  visibility: private # to expose this item in the catalog to others at PNNL, change the visibility to 'public'
+  # system: 
+  lifecycle: production
+
+  # TODO: does leap-r depend on another resource or component?
+  # dependsOn:
+
+  # TODO: does another resource depend on leap-r? 
+  # dependencyOf:

vignettes/order-enrichment.Rmd

@@ -0,0 +1,127 @@
+---
+title: "leapR Order Enrichment Tests"
+output:
+  BiocStyle::html_document:
+    toc: true
+    toc_depth: 2
+vignette: |
+  %\VignetteIndexEntry{leapR}   
+  %\VignetteEngine{knitr::rmarkdown} 
+  %\VignetteEncoding{UTF-8}
+---
+
+```{r knitr, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>",
+  cache = FALSE
+)
+```
+
+
+# Load libraries needed
+
+```{r libraries, message=FALSE, warning = FALSE}
+# load the core libraries
+library(leapR)
+library(gplots)
+library(rmarkdown)
+# plotting helpers used in this vignette
+library(ggplot2)
+library(dplyr)
+library(tibble)
+library(stringr)
+```
+
+
+# Load our test proteomics dataset
+```{r load data}
+url <- "https://api.figshare.com/v2/file/download/56536217"
+pdata <- download.file(url, method = "libcurl", destfile = "protData.rda")
+#  as.matrix()
+load("protData.rda")
+
+p <- file.remove("protData.rda")
+
+data(shortlist)
+data(longlist)
+
+## columns that we want to use for results
+
+cols_to_display <- c("ingroup_n", "outgroup_n", "background_n", 
+                     "pvalue", "BH_pvalue")
+```
+
+# Compare enrichment methods
+We want to evaluate how various samples compare in enrichmnet
+
+```{r compare}
+
+i = 8
+data("ncipid")
+
+cor.res <- do.call(rbind,lapply(1:length(shortlist), function (i) {
+  protdata.enrichment.ks <- leapR::leapR(
+    geneset = ncipid, "enrichment_in_order",
+    eset = pset,
+    minsize = 5,
+    assay_name = "proteomics",
+    primary_columns = shortlist[i]
+  )
+
+  colnames(protdata.enrichment.ks) <- paste('ks',colnames(protdata.enrichment.ks),sep='.')
+
+
+  protdata.enrichment.cs <- leapR::leapR(
+    geneset = ncipid, "enrichment_in_order",
+    method = 'chisq',
+    eset = pset,  minsize = 5,
+    assay_name = "proteomics",
+    primary_columns = shortlist[i]
+  )
+  colnames(protdata.enrichment.cs) <- paste('chisq',colnames(protdata.enrichment.cs),sep='.')
+
+  protdata.enrichment.zt <- leapR::leapR(
+    geneset = ncipid, "enrichment_in_order",
+    eset = pset,  minsize = 5,
+    method = 'ztest',
+    assay_name = "proteomics",
+    primary_columns = shortlist[i]
+  )
+
+  colnames(protdata.enrichment.zt) <- paste('ztest',colnames(protdata.enrichment.zt),sep='.')
+
+  paths <- rownames(protdata.enrichment.ks)
+  allvals <- cbind(protdata.enrichment.cs[paths,], 
+                   protdata.enrichment.ks[paths,], 
+                   protdata.enrichment.zt[paths,])
+
+  kz <- cor(allvals$ks.BH_pvalue, allvals$ztest.BH_pvalue, use = 'p')
+
+  kc <- cor(allvals$ks.BH_pvalue, allvals$chisq.BH_pvalue, use = 'p')
+
+  cz <- cor(allvals$chisq.BH_pvalue, allvals$ztest.BH_pvalue, use = 'p')
+
+    kz <- cor(allvals$ks.pvalue, allvals$ztest.pvalue, use = 'p')
+
+  kc <- cor(allvals$ks.pvalue, allvals$chisq.pvalue, use = 'p')
+
+  cz <- cor(allvals$chisq.pvalue, allvals$ztest.pvalue, use = 'p')
+
+  return(c(kz = kc, kc=kc, cz = cz))
+}))
+
+```
+
+We can compare the corrected p-values
+
+```{r compare pvals}
+library(ggplot2)
+
+cor.res |> as.data.frame() |>
+  tidyr::pivot_longer(c(1:3),names_to='test_comparison',values_to='p cor') |>
+  ggplot(aes(x=test_comparison, y= `p cor`)) + geom_jitter()
+
+
+
+```