diff --git a/DESCRIPTION b/DESCRIPTION
index a2deb87..f3e425e 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: CuratedAtlasQueryR
 Title: Queries the Human Cell Atlas
-Version: 0.3.1
+Version: 0.4.0
 Authors@R: c(
     person(
         "Stefano",
@@ -126,3 +126,4 @@ LazyDataCompression: xz
 URL: https://github.com/stemangiola/CuratedAtlasQueryR
 BugReports: https://github.com/stemangiola/CuratedAtlasQueryR/issues
 VignetteBuilder: knitr
+Roxygen: list(markdown = TRUE)
diff --git a/R/query.R b/R/query.R
index c79d8cb..129c86f 100644
--- a/R/query.R
+++ b/R/query.R
@@ -11,15 +11,19 @@ assay_map <- c(
 )
 
 REMOTE_URL <- "https://swift.rc.nectar.org.au/v1/AUTH_06d6e008e3e642da99d806ba3ea629c5/harmonised-human-atlas"
+COUNTS_VERSION <- "0.2"
 
-#' Given a data frame of HCA metadata, returns a SingleCellExperiment object
-#' corresponding to the samples in that data frame
+#' Gets a SingleCellExperiment from curated metadata
+#'
+#' Given a data frame of Curated Atlas metadata obtained from [get_metadata()],
+#' returns a [`SingleCellExperiment::SingleCellExperiment-class`] object corresponding to the samples in that
+#' data frame
 #'
 #' @param data A data frame containing, at minimum, a `.sample` column, which
 #'   corresponds to a single cell sample ID. This can be obtained from the
 #'   [get_metadata()] function.
-#' @param assays A character vector whose elements must be either "counts" and/or
-#'   "cpm", representing the corresponding assay(s) you want to request.
+#' @param assays A character vector whose elements must be either "counts"
+#'   and/or "cpm", representing the corresponding assay(s) you want to request.
 #' @param repository A character vector of length one. If provided, it should be
 #'   an HTTP URL pointing to the location where the single cell data is stored.
 #' @param cache_directory An optional character vector of length one. If
@@ -51,7 +55,7 @@ REMOTE_URL <- "https://swift.rc.nectar.org.au/v1/AUTH_06d6e008e3e642da99d806ba3e
 #'
 #' @export
 #'
-#'
+#' 
 get_SingleCellExperiment <- function(
     data,
     assays = c("counts", "cpm"),
@@ -79,9 +83,10 @@ get_SingleCellExperiment <- function(
     cli_alert_info("Realising metadata.")
     raw_data <- collect(data)
     inherits(raw_data, "tbl") |> assert_that()
-    has_name(raw_data, c(".cell", "file_id_db")) |> assert_that()
+    has_name(raw_data, c("_cell", "file_id_db")) |> assert_that()
 
-    cache_directory |> dir.create(showWarnings = FALSE)
+    versioned_cache_directory = file.path(cache_directory, COUNTS_VERSION)
+    versioned_cache_directory |> dir.create(showWarnings = FALSE, recursive = TRUE)
 
     subdirs <- assay_map[assays]
 
@@ -100,7 +105,7 @@ get_SingleCellExperiment <- function(
             as.character() |>
             sync_assay_files(
                 url = parsed_repo,
-                cache_dir = cache_directory,
+                cache_dir = versioned_cache_directory,
                 files = _,
                 subdirs = subdirs
             )
@@ -111,7 +116,7 @@ get_SingleCellExperiment <- function(
         imap(function(current_subdir, current_assay) {
             # Build up an SCE for each assay
             dir_prefix <- file.path(
-                cache_directory,
+                versioned_cache_directory,
                 current_subdir
             )
 
@@ -172,14 +177,14 @@ group_to_sce <- function(i, df, dir_prefix, features) {
     sce <- loadHDF5SummarizedExperiment(sce_path)
     # The cells we select here are those that are both available in the SCE
     # object, and requested for this particular file
-    cells <- colnames(sce) |> intersect(df$.cell)
+    cells <- colnames(sce) |> intersect(df$`_cell`)
     # We need to make the cell names globally unique, which we can guarantee
     # by adding a suffix that is derived from file_id_db, which is the grouping
     # variable
     new_cellnames <- paste0(cells, "_", i)
     new_coldata <- df |>
-        mutate(original_cell_id = .data$.cell, .cell = new_cellnames) |>
-        column_to_rownames(".cell") |>
+        mutate(original_cell_id = .data$`_cell`, `_cell` = new_cellnames) |>
+        column_to_rownames("_cell") |>
         as("DataFrame")
 
     features |>
@@ -333,10 +338,12 @@ get_seurat <- function(...) {
     get_SingleCellExperiment(...) |> as.Seurat(data = NULL)
 }
 
+#' Gets the Curated Atlas metadata as a data frame.
+#' 
 #' Downloads a parquet database of the Human Cell Atlas metadata to a local 
 #' cache, and then opens it as a data frame. It can then be filtered and 
 #' passed into [get_SingleCellExperiment()] 
-#' to obtain a [`SingleCellExperiment`](SingleCellExperiment::SingleCellExperiment-class)
+#' to obtain a [`SingleCellExperiment::SingleCellExperiment-class`]
 #'
 #' @param remote_url Optional character vector of length 1. An HTTP URL pointing
 #'   to the location of the parquet database.
@@ -364,10 +371,10 @@ get_seurat <- function(...) {
 #' @importFrom httr progress
 #' @importFrom cli cli_alert_info
 get_metadata <- function(
-    remote_url = "https://object-store.rc.nectar.org.au/v1/AUTH_06d6e008e3e642da99d806ba3ea629c5/metadata-sqlite/metadata.parquet",
+    remote_url = "https://object-store.rc.nectar.org.au/v1/AUTH_06d6e008e3e642da99d806ba3ea629c5/metadata/metadata.0.2.2.parquet",
     cache_directory = get_default_cache_dir()
 ) {
-    db_path <- file.path(cache_directory, "metadata.parquet")
+    db_path <- file.path(cache_directory, "metadata.0.2.2.parquet")
     sync_remote_file(
         remote_url,
         db_path,
diff --git a/man/get_SingleCellExperiment.Rd b/man/get_SingleCellExperiment.Rd
index 6bf9aac..8c5bc59 100644
--- a/man/get_SingleCellExperiment.Rd
+++ b/man/get_SingleCellExperiment.Rd
@@ -2,8 +2,7 @@
 % Please edit documentation in R/query.R
 \name{get_SingleCellExperiment}
 \alias{get_SingleCellExperiment}
-\title{Given a data frame of HCA metadata, returns a SingleCellExperiment object
-corresponding to the samples in that data frame}
+\title{Gets a SingleCellExperiment from curated metadata}
 \usage{
 get_SingleCellExperiment(
   data,
@@ -14,12 +13,12 @@ get_SingleCellExperiment(
 )
 }
 \arguments{
-\item{data}{A data frame containing, at minimum, a `.sample` column, which
+\item{data}{A data frame containing, at minimum, a \code{.sample} column, which
 corresponds to a single cell sample ID. This can be obtained from the
-[get_metadata()] function.}
+\code{\link[=get_metadata]{get_metadata()}} function.}
 
-\item{assays}{A character vector whose elements must be either "counts" and/or
-"cpm", representing the corresponding assay(s) you want to request.}
+\item{assays}{A character vector whose elements must be either "counts"
+and/or "cpm", representing the corresponding assay(s) you want to request.}
 
 \item{cache_directory}{An optional character vector of length one. If
 provided, it should indicate a local file path where any remotely accessed
@@ -33,11 +32,12 @@ the counts for. By default counts for all features will be returned.}
 }
 \value{
 A SingleCellExperiment object, with one assay for each value in the
-  assays argument
+assays argument
 }
 \description{
-Given a data frame of HCA metadata, returns a SingleCellExperiment object
-corresponding to the samples in that data frame
+Given a data frame of Curated Atlas metadata obtained from \code{\link[=get_metadata]{get_metadata()}},
+returns a \code{\link[SingleCellExperiment:SingleCellExperiment]{SingleCellExperiment::SingleCellExperiment}} object corresponding to the samples in that
+data frame
 }
 \examples{
 meta <- get_metadata() |> head(2)
diff --git a/man/get_metadata.Rd b/man/get_metadata.Rd
index f82560f..76dcf9d 100644
--- a/man/get_metadata.Rd
+++ b/man/get_metadata.Rd
@@ -2,14 +2,11 @@
 % Please edit documentation in R/query.R
 \name{get_metadata}
 \alias{get_metadata}
-\title{Downloads a parquet database of the Human Cell Atlas metadata to a local 
-cache, and then opens it as a data frame. It can then be filtered and 
-passed into [get_SingleCellExperiment()] 
-to obtain a [`SingleCellExperiment`](SingleCellExperiment::SingleCellExperiment-class)}
+\title{Gets the Curated Atlas metadata as a data frame.}
 \usage{
 get_metadata(
   remote_url =
-    "https://object-store.rc.nectar.org.au/v1/AUTH_06d6e008e3e642da99d806ba3ea629c5/metadata-sqlite/metadata.parquet",
+    "https://object-store.rc.nectar.org.au/v1/AUTH_06d6e008e3e642da99d806ba3ea629c5/metadata/metadata.0.2.2.parquet",
   cache_directory = get_default_cache_dir()
 )
 }
@@ -23,15 +20,15 @@ metadata.parquet}
 }
 \value{
 A lazy data.frame subclass containing the metadata. You can interact
-  with this object using most standard dplyr functions. For string matching,
-  it is recommended that you use `stringr::str_like` to filter character
-  columns, as `stringr::str_match` will not work.
+with this object using most standard dplyr functions. For string matching,
+it is recommended that you use \code{stringr::str_like} to filter character
+columns, as \code{stringr::str_match} will not work.
 }
 \description{
-Downloads a parquet database of the Human Cell Atlas metadata to a local 
-cache, and then opens it as a data frame. It can then be filtered and 
-passed into [get_SingleCellExperiment()] 
-to obtain a [`SingleCellExperiment`](SingleCellExperiment::SingleCellExperiment-class)
+Downloads a parquet database of the Human Cell Atlas metadata to a local
+cache, and then opens it as a data frame. It can then be filtered and
+passed into \code{\link[=get_SingleCellExperiment]{get_SingleCellExperiment()}}
+to obtain a \code{\link[SingleCellExperiment:SingleCellExperiment]{SingleCellExperiment::SingleCellExperiment}}
 }
 \examples{
 library(dplyr)
diff --git a/man/get_seurat.Rd b/man/get_seurat.Rd
index 2e2a491..fb5189b 100644
--- a/man/get_seurat.Rd
+++ b/man/get_seurat.Rd
@@ -11,11 +11,11 @@ get_seurat(...)
 \item{...}{
   Arguments passed on to \code{\link[=get_SingleCellExperiment]{get_SingleCellExperiment}}
   \describe{
-    \item{\code{data}}{A data frame containing, at minimum, a `.sample` column, which
+    \item{\code{data}}{A data frame containing, at minimum, a \code{.sample} column, which
 corresponds to a single cell sample ID. This can be obtained from the
-[get_metadata()] function.}
-    \item{\code{assays}}{A character vector whose elements must be either "counts" and/or
-"cpm", representing the corresponding assay(s) you want to request.}
+\code{\link[=get_metadata]{get_metadata()}} function.}
+    \item{\code{assays}}{A character vector whose elements must be either "counts"
+and/or "cpm", representing the corresponding assay(s) you want to request.}
     \item{\code{repository}}{A character vector of length one. If provided, it should be
 an HTTP URL pointing to the location where the single cell data is stored.}
     \item{\code{cache_directory}}{An optional character vector of length one. If
@@ -27,7 +27,7 @@ the counts for. By default counts for all features will be returned.}
 }
 \value{
 A Seurat object containing the same data as a call to
-  get_SingleCellExperiment.
+get_SingleCellExperiment.
 }
 \description{
 Given a data frame of HCA metadata, returns a Seurat object corresponding to
diff --git a/tests/testthat/test-query.R b/tests/testthat/test-query.R
index 92d491a..6ff3c02 100755
--- a/tests/testthat/test-query.R
+++ b/tests/testthat/test-query.R
@@ -2,7 +2,7 @@ library(CuratedAtlasQueryR)
 
 test_that("get_SingleCellExperiment() correctly handles duplicate cell IDs", {
     meta <- get_metadata() |>
-        dplyr::filter(.cell == "868417_1") |>
+        dplyr::filter(`_cell` == "868417_1") |>
         dplyr::collect()
     sce <- get_SingleCellExperiment(meta)
     # This query should return multiple cells, despite querying only 1 cell ID
diff --git a/vignettes/Introduction.Rmd b/vignettes/Introduction.Rmd
index feefda1..7991996 100644
--- a/vignettes/Introduction.Rmd
+++ b/vignettes/Introduction.Rmd
@@ -31,7 +31,7 @@ knitr::include_graphics(c(
   "../man/figures/svcf_logo.jpeg", 
   "../man/figures/czi_logo.png", 
   "../man/figures/bioconductor_logo.jpg",
-    "../man/figures/vca_logo.png"
+  "../man/figures/vca_logo.png"
 ))
 ```