Start an updated vignette with DLPFC data

vignettes/Deconvolution_Benchmark_DLPFC.Rmd

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+---
+title: "Deconvolution_Benchmark_DLPFC"
+author: 
+  - name: Louise Huuki-Myers
+    affiliation:
+    - &libd Lieber Institute for Brain Development, Johns Hopkins Medical Campus
+    email: [email protected]
+output: 
+  BiocStyle::html_document:
+    self_contained: yes
+    toc: true
+    toc_float: true
+    toc_depth: 2
+    code_folding: show
+date: "`r doc_date()`"
+package: "`r pkg_ver('DeconvoBuddies')`"
+vignette: >
+  %\VignetteIndexEntry{Deconvolution_Benchmark_DLPFC}
+  %\VignetteEngine{knitr::rmarkdown}
+  %\VignetteEncoding{UTF-8}  
+---
+
+```{r setup, include = FALSE}
+knitr::opts_chunk$set(
+    collapse = TRUE,
+    comment = "#>",
+    crop = NULL ## Related to https://stat.ethz.ch/pipermail/bioc-devel/2020-April/016656.html
+)
+```
+
+
+```{r vignetteSetup, echo=FALSE, message=FALSE, warning = FALSE}
+## Track time spent on making the vignette
+startTime <- Sys.time()
+
+## Bib setup
+library("RefManageR")
+
+## Write bibliography information
+bib <- c(
+    R = citation(),
+    BiocStyle = citation("BiocStyle")[1],
+    knitr = citation("knitr")[1],
+    RefManageR = citation("RefManageR")[1],
+    rmarkdown = citation("rmarkdown")[1],
+    sessioninfo = citation("sessioninfo")[1],
+    testthat = citation("testthat")[1],
+    DeconvoBuddies = citation("DeconvoBuddies")[1]
+)
+```
+
+#Introduction
+
+## What is Deconvolution?
+
+**Inferring the composition of different cell types in a bulk RNA-seq data**
+
+`Bisque` is an R package for preforming reference based deconvolution [github.com/cozygene/bisque](https://github.com/cozygene/bisque).
+
+## Goals of this Vignette 
+
+We will be demonstrating how to use `DeconvoBuddies` tools when applying 
+deconvolution with the `Bisque` package.
+
+1. Install and load required packages 
+2. Download DLPFC RNA-seq data, and reference snRNA-seq data
+3. Find marker genes with `DeconvoBuddies` tools
+4. Run deconvolution with `BisqueRNA`
+5. Explore deconvolution output and create compostion plots with `DeconvoBuddies` tools
+6. Check proportion against RNAScope estimated proportions
+
+# Basics
+
+# 1. Install and load required packages
+
+`R` is an open-source statistical environment which can be easily modified to enhance its functionality via packages. `r Biocpkg("DeconvoBuddies")` is a `R` package available via the [Bioconductor](http://bioconductor.org) repository for packages. `R` can be installed on any operating system from [CRAN](https://cran.r-project.org/) after which you can install `r Biocpkg("DeconvoBuddies")` by using the following commands in your `R` session:
+
+## Install `DeconvoBuddies`
+
+```{r "install", eval = FALSE}
+if (!requireNamespace("BiocManager", quietly = TRUE)) {
+      install.packages("BiocManager")
+  }
+
+BiocManager::install("DeconvoBuddies")
+
+## Check that you have a valid Bioconductor installation
+BiocManager::valid()
+```
+
+## Load Other Packages
+
+```{r "load_packages", message=FALSE, warning=FALSE}
+## install Bisque from cran
+# install.packages("BisqueRNA")
+
+library("spatialLIBD")
+library("DeconvoBuddies")
+library("SummarizedExperiment")
+library("SingleCellExperiment")
+library("BisqueRNA")
+library("dplyr")
+library("tidyr")
+library("tibble")
+```
+
+# 2. Download DLPFC RNA-seq data, and reference snRNA-seq data. 
+
+## Bulk RNA-seq data
+
+Access the 110 sample Human DLPFC bulk RNA-seq dataset for LIBD. These samples  
+are from 19 tissue blocks, and 10 neurotypical adult donors. Samples were sequenced
+with two different `library_types` (polyA and RiboZeroGold), and three different 
+`RNA_extraction` (Cyto, Total, Nuc), post quality control n=110 samples. 
+
+```{r "load rse_gene"}
+## use fetch deconvon data to load rse_gene
+rse_gene <- fetch_deconvo_data("rse_gene")
+rse_gene
+
+## bulk RNA seq samples were sequenced with different library types, and RNA extractions
+table(rse_gene$library_type, rse_gene$library_prep)
+```
+
+## Refernce snRNA-seq data
+
+This data is paired with a single nucleus RNA-seq data set from `spatialLIBD`. 
+This dataset can be accessed with `spatialLIBD::fetch_data()`.
+
+```{r "load snRNA-seq"}
+## Use spatialLIBD to fetch the snRNA-seq dataset
+sce_path_zip <- spatialLIBD::fetch_data("spatialDLPFC_snRNAseq")
+
+# sce_path <- unzip(sce_path_zip, exdir = tempdir())
+# 
+# sce <- HDF5Array::loadHDF5SummarizedExperiment(
+#     file.path(tempdir(), "sce_DLPFC_annotated")
+# )
+```
+
+
+# 3. Find marker genes with `DeconvoBuddies` tools
+# 4. Run deconvolution with `BisqueRNA`
+# 5. Explore deconvolution output and create compostion plots with `DeconvoBuddies` tools
+# 6. Check proportion against RNAScope estimated proportions
+
+
+# Reproducibility
+
+The `r Biocpkg("DeconvoBuddies")` package `r Citep(bib[["DeconvoBuddies"]])` was made possible thanks to:
+
+* R `r Citep(bib[["R"]])`
+* `r Biocpkg("BiocStyle")` `r Citep(bib[["BiocStyle"]])`
+* `r CRANpkg("knitr")` `r Citep(bib[["knitr"]])`
+* `r CRANpkg("RefManageR")` `r Citep(bib[["RefManageR"]])`
+* `r CRANpkg("rmarkdown")` `r Citep(bib[["rmarkdown"]])`
+* `r CRANpkg("sessioninfo")` `r Citep(bib[["sessioninfo"]])`
+* `r CRANpkg("testthat")` `r Citep(bib[["testthat"]])`
+
+This package was developed using `r BiocStyle::Biocpkg("biocthis")`.
+
+
+Code for creating the vignette
+
+```{r createVignette, eval=FALSE}
+## Create the vignette
+library("rmarkdown")
+system.time(render("Deconvolution_Benchmark_DLPFC.Rmd", "BiocStyle::html_document"))
+
+## Extract the R code
+library("knitr")
+knit("Deconvolution_Benchmark_DLPFC.Rmd", tangle = TRUE)
+```
+
+Date the vignette was generated.
+
+```{r reproduce1, echo=FALSE}
+## Date the vignette was generated
+Sys.time()
+```
+
+Wallclock time spent generating the vignette.
+
+```{r reproduce2, echo=FALSE}
+## Processing time in seconds
+totalTime <- diff(c(startTime, Sys.time()))
+round(totalTime, digits = 3)
+```
+
+`R` session information.
+
+```{r reproduce3, echo=FALSE}
+## Session info
+library("sessioninfo")
+options(width = 120)
+session_info()
+```
+
+
+
+# Bibliography
+
+This vignette was generated using `r Biocpkg("BiocStyle")` `r Citep(bib[["BiocStyle"]])`
+with `r CRANpkg("knitr")` `r Citep(bib[["knitr"]])` and `r CRANpkg("rmarkdown")` `r Citep(bib[["rmarkdown"]])` running behind the scenes.
+
+Citations made with `r CRANpkg("RefManageR")` `r Citep(bib[["RefManageR"]])`.
+
+```{r vignetteBiblio, results = "asis", echo = FALSE, warning = FALSE, message = FALSE}
+## Print bibliography
+PrintBibliography(bib, .opts = list(hyperlink = "to.doc", style = "html"))
+```