Update R docs and doc-site (#684)

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* Update api/r/cellxgene.census/README.md

Co-authored-by: Andrew Tolopko <atolopko-czi@users.noreply.github.com>

* Update api/r/cellxgene.census/README.md

Co-authored-by: Andrew Tolopko <atolopko-czi@users.noreply.github.com>

* Update api/r/cellxgene.census/README.md

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* Update docs/cellxgene_census_docsite_quick_start.md

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* Update installation instructions, and R version

---------

Co-authored-by: Andrew Tolopko <atolopko-czi@users.noreply.github.com>

api/r/cellxgene.census/DESCRIPTION

@@ -1,6 +1,6 @@
 Package: cellxgene.census
 Title: CZ CELLxGENE Discover Cell Census
-Version: 0.0.0.9000
+Version: 0.0.9.9
 Authors@R: 
     person("Chan Zuckerberg Initiative", email = "soma@chanzuckerberg.com",
            role = c("aut", "cre", "cph", "fnd"))

api/r/cellxgene.census/README.md

@@ -1,39 +1,90 @@
 
-# CZ CELLxGENE Discover Census
+# R package of CZ CELLxGENE Discover Census
 
 <!-- badges: start -->
 <!-- badges: end -->
 
+This is the documentation for the R package `cellxgene.census` which is part of CZ CELLxGENE Discover Census. For full details on Census data and capabilities please go to the [main Census site](https://chanzuckerberg.github.io/cellxgene-census/).  
 
-The `cellxgene.census` package provides an API to facilitate the use of the CZ CELLxGENE Discover Census. For more information about the API and the project visit the [chanzuckerberg/cellxgene-census GitHub repo](https://github.com/chanzuckerberg/cellxgene-census/).
+`cellxgene.census` provides an API to efficiently access the cloud-hosted Census single-cell data from R. In just a few seconds users can access any slice of Census data using cell or gene filters across hundreds of single-cell datasets. 
 
-**Status**: Pre-release, under rapid development. Expect API changes.
-
-Also see the [Python API](https://cellxgene-census.readthedocs.io/).
+Census data can be fetched in an iterative fashion for bigger-than-memory slices of data, or quickly exported to basic R structures, as well as `Seurat` or `SingleCellExperiment` objects for downstream analysis.
 
 ## Installation
 
-You can install the development version of `cellxgene.census` from [GitHub](https://github.com/) with:
+From an R session, first install `tiledb` from R-Universe, the latest release in CRAN is not yet available.
+
+If installing from Ubuntu, you may need to install the following libraries via `apt install`:  `libxml2-dev` `libssl-dev` `libcurl4-openssl-dev`.
+
+If installing from MacOS, you will need to install the [developer tools `Xcode`](https://apps.apple.com/us/app/xcode/id497799835?mt=12).
 
-``` r
-# install.packages("devtools")
-devtools::install_github("chanzuckerberg/cellxgene-census/api/r/cellxgene.census")
-print(cellxgene.census::open_soma())
+```r
+install.packages(
+  "tiledb",
+  version = "0.20.3", 
+  repos=c('https://tiledb-inc.r-universe.dev','https://cloud.r-project.org') 
+)
 ```
 
-(minimal apt dependencies: r-base cmake git)
+Then install `cellxgene.census` from R-Universe.
+
+```r
+install.packages(
+  "cellxgene.census",
+  repos=c('https://chanzuckerberg.r-universe.dev', 'https://cloud.r-project.org') 
+)
+```
+
+## Usage
+
+Check out the vignettes in the "Articles" section of the navigation bar on this site. We highly recommend the following vignettes as a starting point:
+
+* [Querying and fetching the single-cell data and cell/gene metadata](./articles/census_query_extract.html)
+* [Learning about the CZ CELLxGENE Discover Census](./articles/comp_bio_census_info.html)
+
+You can also check out out the [quick start guide](https://chanzuckerberg.github.io/cellxgene-census/cellxgene_census_docsite_quick_start.html) in the main Census site.
+
+
+### Example `Seurat` and `SingleCellExperiment` query
+
+The following creates a `Seurat` object on-demand with all sympathetic neurons in Census and filtering only for the genes `ENSG00000161798`, `ENSG00000188229`.
+
+```r
+library("cellxgene.census")
+library("Seurat")
+
+census <- open_soma()
+
+organism <- "Homo sapiens"
+gene_filter <- "feature_id %in% c('ENSG00000107317', 'ENSG00000106034')"
+cell_filter <-  "cell_type == 'sympathetic neuron'"
+cell_columns <- c("assay", "cell_type", "tissue", "tissue_general", "suspension_type", "disease")
+
+seurat_obj <- get_seurat(
+   census = census,
+   organism = organism,
+   var_value_filter = gene_filter,
+   obs_value_filter = cell_filter,
+   obs_column_names = cell_columns
+)
+```
 
-## Example
+And the following retrieves the same data as a `SingleCellExperiment` object.
 
-This is a basic example which shows you how to solve a common problem:
+```r
+library("SingleCellExperiment")
 
-``` r
-library(cellxgene.census)
-## basic example code
+sce_obj <- get_single_cell_experiment(
+   census = census,
+   organism = organism,
+   var_value_filter = gene_filter,
+   obs_value_filter = cell_filter,
+   obs_column_names = cell_columns
+)
 ```
 
 ## For More Help
 
-For more help, please file a issue on the repo, or contact us at <soma@chanzuckerberg.com>
+For more help, please go visit the [main Census site](https://chanzuckerberg.github.io/cellxgene-census/). 
 
-If you believe you have found a security issue, we would appreciate notification. Please send email to <security@chanzuckerberg.com>.
+If you believe you have found a security issue, we would appreciate notification. Please send an email to <security@chanzuckerberg.com>.