Add content to Marker Finding Vignette

vignettes/Marker_Finding.Rmd

@@ -49,11 +49,39 @@ bib <- c(
 )
 ```
 
-# Basics
+# Introduction
 
-## Install `DeconvoBuddies`
+## What are Marker Genes?
+
+### How can we select marker genes?
+
+## The MeanRatio Method
+
+## Goals of this Vignette
+
+We will be demonstrating how to use `DeconvoBuddies` tools when finding cell 
+type marker genes in single cell RNA-seq data via the MeanRatio method.
 
-`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:
+1.  Install and load required packages
+2.  Download DLPFC snRNA-seq data
+3.  Find MeanRatio marker genes with `DeconvoBuddies::get_mean_ratio()`
+4.  Find 1vALL marker genes with `DeconvoBuddies::findMarkers_1vALL()`
+5.  Compare marker gene selection
+6.  Visualize marker genes expression with `DeconcoBuddies::plot_gene_express()`
+and related functions
+
+# 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)) {
@@ -66,37 +94,44 @@ BiocManager::install("DeconvoBuddies")
 BiocManager::valid()
 ```
 
-## Required knowledge
-
-`r Biocpkg("DeconvoBuddies")` is based on many other packages and in particular in those that have implemented the infrastructure needed for dealing with RNA-seq data (EDIT!). That is, packages like `r Biocpkg("SummarizedExperiment")` (EDIT!).
+## Load Other Packages
 
-If you are asking yourself the question "Where do I start using Bioconductor?" you might be interested in [this blog post](http://lcolladotor.github.io/2014/10/16/startbioc/#.VkOKbq6rRuU).
-
-## Asking for help
-
-As package developers, we try to explain clearly how to use our packages and in which order to use the functions. But `R` and `Bioconductor` have a steep learning curve so it is critical to learn where to ask for help. The blog post quoted above mentions some but we would like to highlight the [Bioconductor support site](https://support.bioconductor.org/) as the main resource for getting help: remember to use the `DeconvoBuddies` tag and check [the older posts](https://support.bioconductor.org/tag/DeconvoBuddies/). Other alternatives are available such as creating GitHub issues and tweeting. However, please note that if you want to receive help you should adhere to the [posting guidelines](http://www.bioconductor.org/help/support/posting-guide/). It is particularly critical that you provide a small reproducible example and your session information so package developers can track down the source of the error.
-
-## Citing `DeconvoBuddies`
-
-We hope that `r Biocpkg("DeconvoBuddies")` will be useful for your research. Please use the following information to cite the package and the overall approach. Thank you!
-
-```{r "citation"}
-## Citation info
-citation("DeconvoBuddies")
+```{r "load_packages", message=FALSE, warning=FALSE}
+library("spatialLIBD")
+library("DeconvoBuddies")
+library("SummarizedExperiment")
+library("SingleCellExperiment")
+library("dplyr")
+library("tidyr")
+library("tibble")
+library("ggplot2")
 ```
 
-# Quick start to using `DeconvoBuddies`
+# 2. Download DLPFC snRNA-seq data.
+```{r "load snRNA-seq"}
+## Use spatialLIBD to fetch the snRNA-seq dataset
+sce_path_zip <- fetch_deconvo_data("sce")
 
-```{r "start", message=FALSE}
-library("DeconvoBuddies")
-```
+## unzip and load the data
+sce_path <- unzip(sce_path_zip, exdir = tempdir())
+sce <- HDF5Array::loadHDF5SummarizedExperiment(
+    file.path(tempdir(), "sce_DLPFC_annotated")
+)
 
-Edit this as you see fit =)
+# lobstr::obj_size(sce)
+# 172.28 MB
 
-Here is an example of you can cite your package inside the vignette:
+## exclude Ambiguous cell type
+sce <- sce[, sce$cellType_broad_hc != "Ambiguous"]
+sce$cellType_broad_hc <- droplevels(sce$cellType_broad_hc)
 
-* `r Biocpkg("DeconvoBuddies")` `r Citep(bib[["DeconvoBuddies"]])`
+dim(sce)
+## Check the broad cell type distribution
+table(sce$cellType_broad_hc)
 
+## We're going to subset to the first 5k genes to save memory
+sce <- sce[seq_len(5000), ]
+```
 
 
 # Reproducibility