fork/cellxgene
1
0
Fork 0
mirror of https://github.com/chanzuckerberg/cellxgene.git synced 2026-09-20 03:18:12 +08:00
Code Issues Packages Projects Releases Wiki Activity

Add calculate_qc_metrics to `prepare (#697)

Browse Source 
* Calculate QC metrics

* Add QC metrics to prepare section of readme

* Add pointer to scanpy qc metrics function

* Don't explicitly pass qc flag as arg

* Add explicit toggle for run-qc/skip-qc

* Move qc metrics calculation to separate step/function
This commit is contained in:
Sidney Bell
2019-04-09 08:56:07 -07:00
committed by GitHub
parent 7275d9d4dc
commit 34e5a91dc6
2 changed files with 16 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
README.md
View File

@@ -70,7 +70,7 @@ To prepare from an existing `.h5ad` file use
cellxgene prepare dataset.h5ad --output=dataset-processed.h5ad
```
This will load the input data, perform PCA and nearest neighbor calculations, compute `umap` and `tsne` layouts and `louvain` cluster assignments, and save the results in a new file called `dataset-processed.h5ad` that can be loaded using `cellxgene launch`. Data can be loaded from several formats, including `.h5ad` `.loom` and a `10-Genomics-formatted` `mtx` directory. Several options are available, including running one of the preprocessing `recipes` included with `scanpy`, which include steps like cell filtering and gene selection. To learn more about the `recipes` please see the `scanpy` [documentation](https://scanpy.readthedocs.io/en/latest/api/index.html#recipes).
This will load the input data, calculate QC metrics, perform PCA and nearest neighbor calculations, compute `umap` and `tsne` layouts and `louvain` cluster assignments, and save the results in a new file called `dataset-processed.h5ad` that can be loaded using `cellxgene launch`. Data can be loaded from several formats, including `.h5ad` `.loom` and a `10-Genomics-formatted` `mtx` directory. Several options are available, including running one of the preprocessing `recipes` included with `scanpy`, which include steps like cell filtering and gene selection. To learn more about the `recipes` please see the `scanpy` [documentation](https://scanpy.readthedocs.io/en/latest/api/index.html#recipes).
Depending on the options chosen, `prepare` can take a long time to run (a few minutes for datasets with 10-100k cells, up to an hour or more for datasets with >100k cells). If you want `prepare` to run faster we recommend using the `sparse` option and only computing the layout for `umap`, using a call like this

16
server/cli/prepare.py
View File

@@ -30,6 +30,10 @@ from scipy.sparse.csc import csc_matrix
@click.option("--overwrite", default=False, is_flag=True, help="Allow file overwriting.", show_default=True)
@click.option("--set-obs-names", default="", help="Named field to set as index for obs.", metavar="<name>")
@click.option("--set-var-names", default="", help="Named field to set as index for var.", metavar="<name>")
@click.option(
"--run-qc/--skip-qc", default=True, is_flag=True,
help="Whether to calculate QC metrics (saved to adata.obs and adata.var). \
See scanpy.pp.calculate_qc_metrics for details.", show_default=True)
@click.option(
"--make-obs-names-unique", default=True, is_flag=True, help="Ensure obs index is unique.", show_default=True
)
@@ -46,6 +50,7 @@ def prepare(
overwrite,
set_obs_names,
set_var_names,
run_qc,
make_obs_names_unique,
make_var_names_unique,
):
@@ -115,7 +120,11 @@ def prepare(
click.echo("Warning: obs index is not unique")
if not adata._var.index.is_unique:
click.echo("Warning: var index is not unique")
return adata
def calculate_qc_metrics(adata):
if run_qc:
sc.pp.calculate_qc_metrics(adata, inplace=True)
return adata
def make_sparse(adata):
@@ -171,7 +180,12 @@ def prepare(
sc.pl.tsne(adata, color="louvain", palette=palette, save="_louvain")
def show_step(item):
if run_qc:
qc_name = "Calculating QC metrics"
else:
qc_name = "Skipping QC"
names = {
"calculate_qc_metrics": qc_name,
"make_sparse": "Ensuring sparsity",
"run_recipe": f'Running preprocessing recipe "{recipe}"',
"run_pca": "Running PCA",
@@ -182,7 +196,7 @@ def prepare(
if item is not None:
return names[item.__name__]
steps = [make_sparse, run_recipe, run_pca, run_neighbors, run_louvain, run_layout]
steps = [calculate_qc_metrics, make_sparse, run_recipe, run_pca, run_neighbors, run_louvain, run_layout]
click.echo(f"[cellxgene] Loading data from {data}, please wait...")
adata = load_data(data)