adds 'duplicate cells' notebooks #448
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| "\n", | ||
| "* There are superset datasets containing data from multiple datasets.\n", | ||
| "> *For example [Tabula Sapiens](https://cellxgene.cziscience.com/collections/e5f58829-1a66-40b5-a624-9046778e74f5) has one dataset with all of its cells and separate datasets with cells divided by high-level lineage (i.e. immune, epithelial, stromal, endothelial)*\n", | ||
| "* There are datasets with meta-analysis of pre-existing datasets.\n", |
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| "* There are datasets with meta-analysis of pre-existing datasets.\n", | |
| "* A dataset may provide a meta-analysis of a pre-existing datasets.\n", |
| } | ||
| ], | ||
| "source": [ | ||
| "adata" |
| "outputs": [], | ||
| "source": [ | ||
| "with cellxgene_census.open_soma() as census:\n", | ||
| " nk_cells_unique = census[\"census_data\"][\"homo_sapiens\"].obs.read(\n", |
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why not nk_cells_primary instead of introducing a new term (unique)? (for adata below, too)
| " )\n", | ||
| "\n", | ||
| " # get iterator for X\n", | ||
| " iterator = query.X(\"raw\").tables()\n", |
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alternately, you could retrieve the obs data, concat it, and show the count, as done for the other examples. This we de-emphasize the "out-of-core" purpose. Or retrieve the obs data and show the is_primary_data values for a single chunk are all True.
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I would like to still emphasize the out-of-core aspect of this, the reason being "repetition is our ally" for communicating to the user how to perform out-of-core and exclude primary cells
Co-authored-by: Andrew Tolopko <[email protected]>
Co-authored-by: Andrew Tolopko <[email protected]>
Co-authored-by: Andrew Tolopko <[email protected]>
Co-authored-by: Andrew Tolopko <[email protected]>
Co-authored-by: Andrew Tolopko <[email protected]>
Co-authored-by: Andrew Tolopko <[email protected]>
| "\n", | ||
| "## An example: duplicate cells in the Tabula Muris Senis data\n", | ||
| "\n", | ||
| "Let's take a look at an example from the Census using the Tabula Muris Senis data. Some datasets contain non-primary cell data.\n", |
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this introduces a new term: "non-primary cell data". Is this the same as "duplicated cell data"? If the same, I suggest sticking with the defined term ("duplicate"), or defining primary/non-primary in the intro.
| "\n", | ||
| "Let's take a look at an example from the Census using the Tabula Muris Senis data. Some datasets contain non-primary cell data.\n", | ||
| "\n", | ||
| "We can obtain cell metadata for the **main** Tabula Muris Senis dataset: \"All - A single-cell transcriptomic atlas characterizes ageing tissues in the mouse - 10x\", which contains only primary cell data\n", |
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same issue here - the term "primary" is used. If these are helpful, maybe we just need to add them to the definition above (i.e., what is a "primary" or "non-primary" cell?)
| "1. This dataset only contains cells from liver.\n", | ||
| "2. All cells are labelled as `False` for `is_primary_data`. **This is because the cells are marked as duplicate cells of the main Tabula Muris Senis dataset.**\n", | ||
| "\n", | ||
| "## Filtering out duplicates cells\n", |
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typo (extra 's'): suggest: "duplicate cells"
Adds notebook to increase visibility to the cell metadata variable
is_primary_data