Very minor changes to elaborate in a few places

This commit is contained in:
Sidney Bell
2018-08-07 07:42:45 -07:00
parent 16d7fac88e
commit 12c52a55f7
+40 -40
View File
@@ -21,84 +21,84 @@ Started in the context of the Human Cell Atlas Consortium, cellxgene hopes to bo
- OS: OSX, Windows, Linux - OS: OSX, Windows, Linux
- python 3.6 - python 3.6
- npm - npm
- Google Chrome - Google Chrome
**Clone project** **Clone project**
git clone https://github.com/chanzuckerberg/cellxgene.git git clone https://github.com/chanzuckerberg/cellxgene.git
**Install client**
**Install client**
cd cellxgene cd cellxgene
./bin/build-client ./bin/build-client
**To use with virtual env for python** **To use with virtual env for python**
(optional, but recommended) (optional, but recommended)
ENV_NAME=cellxgene
python3 -m venv ${ENV_NAME}
source ${ENV_NAME}/bin/activate
**Install server** ENV_NAME=cellxgene
python3 -m venv ${ENV_NAME}
python3 setup.py install source ${ENV_NAME}/bin/activate
**Install server**
python3 setup.py install
**Run (with demo data)**
**Run (with demo data)**
cellxgene --title PBMC3K scanpy example-dataset/ cellxgene --title PBMC3K scanpy example-dataset/
*In google chrome, navigate to the viewer via the web address printed in your console. *In google chrome, navigate to the viewer via the web address printed in your console.
E.g.,* `Running on http://0.0.0.0:5005/` E.g.,* `Running on http://0.0.0.0:5005/`
**Help** **Help**
cellxgene --help cellxgene --help
_For help with the scanpy engine_ _For help with the scanpy engine_
cellxgene scanpy --help cellxgene scanpy --help
## Using your own data ## Using your own data
### Scanpy ### Scanpy
To prepare you data you will need to format your data into AnnData format using scanpy and calculate PCA and nearest neighbors and save in h5ad format. To prepare your data you will need to format your data into AnnData format using scanpy and calculate PCA and nearest neighbors and save in h5ad format.
1. [Load data into scanpy](https://scanpy.readthedocs.io/en/latest/api/index.html#exporting) 1. [Load data into scanpy](https://scanpy.readthedocs.io/en/latest/api/index.html#reading)
- Ensure that `obs`'s index is the cell names - Ensure that `obs`'s index is the cell names: `print(data.obs_names)` should show your cell indices. If it shows gene names, you may need to just call `data.transpose()`.
2. Calculate PCA 2. Calculate PCA
sc.pp.pca(data) sc.pp.pca(data) ## sc is scanpy.api
3. Calculate nearest neighbors (depending on layout algorithm) 3. Calculate nearest neighbors (depending on layout algorithm)
``` ```
# For umap layout algorithm # For umap layout algorithm, you need to use the "umap" method for neighbors
sc.pp.neighbors(data, method="umap", metric="euclidean", use_rep="X_pca") sc.pp.neighbors(data, method="umap", metric="euclidean", use_rep="X_pca")
# For tsne layout algorithm # For tsne layout algorithm, you can use either "umap" or "gauss"; we recommend "gauss"
sc.pp.neighbors(data, method="gauss", metric="euclidean", use_rep="X_pca") sc.pp.neighbors(data, method="gauss", metric="euclidean", use_rep="X_pca")
``` ```
4. Save file 4. Save file
``` ```
# cellxgene requires file to be named data.h5ad # cellxgene requires file to be named data.h5ad
data.write("data.h5ad") data.write("data.h5ad")
``` ```
5. Create config file (optional) 5. Create config file (optional)
If you do not have a config file, the schema (metadata names, types, and categorical/continuous) will be inferred from the observations in the data file. Config file is required to be named 'data_schema.json' and located in the same directory as data file. If you do not have a config file, the schema (metadata names, types, and categorical/continuous) will be inferred from the observations in the data file. Config file is required to be named 'data_schema.json' and located in the same directory as data file.
- The config file is a JSON format file with information on the metadata associated with the cells. The key is the column name in obs. The value is an object - The config file is a JSON format file with information on the metadata associated with the cells. The key is the column name in obs. The value is an object
``` ```
type: string, int, or float (what type the values are), type: string, int, or float (what type the values are),
variabletype: categorical or continuous (categorical values are displayed as checkboxes, continuous values are displayed as a histogram) variabletype: categorical or continuous (categorical values are displayed as checkboxes, continuous values are displayed as a histogram)
displayname: (what the heading should be displayed as) displayname: (what the heading should be displayed as)
include: True/False (whether to display values on web interface) include: True/False (whether to display values on web interface)
```
``` ```
```
Example Example
{ {
"CellName": { "CellName": {