# stLearn - A downstream analysis toolkit for Spatial Transcriptomic data (v0.1.8)
stLearn is designed to comprehensively analyse Spatial Transcriptomics (ST) data to investigate complex biological processes within an undissociated tissue. ST is emerging as the “next generation” of single-cell RNA sequencing because it adds spatial and morphological context to the transcriptional profile of cells in an intact tissue section. However, existing ST analysis methods typically use the captured spatial and/or morphological data as a visualisation tool rather than as informative features for model development. We have developed an analysis method that exploits all three data types: Spatial distance, tissue Morphology, and gene Expression measurements (SME) from ST data. This combinatorial approach allows us to more accurately model underlying tissue biology, and allows researchers to address key questions in three major research areas: cell type identification, cell trajectory reconstruction, and the study of cell-cell interactions within an undissociated tissue sample.
<p align=”center”> <img src=”https://i.imgur.com/yfXlCYO.png” alt=”” width=”386” height=”261” /> </p>
## Detailed tutorials:
For installation and implementation of stLearn functionalities, see the dedicated documentation page at: https://stlearn.readthedocs.io/en/latest/
A collection of Jupyter notebooks are available in this repository in the tutorial folder
## Brief installation instructions are below:
### For Linux/MacOS users
#### Step 1:
Prepare conda environment for stlearn
` conda create -n stlearn python=3.8 `
` conda activate stlearn `
#### Step 2:
` conda config --add channels conda-forge `
` conda install jupyterlab louvain ipywidgets`
#### Step 3:
` pip install stlearn`
### For Windows users
#### Step 1:
Prepare conda environment for stlearn
` conda create -n stlearn python=3.8 `
` conda activate stlearn `
#### Step 2:
` conda install jupyterlab ipywidgets`
#### Step 4 (For Windows user):
Access to:
Download 2 files: python_igraph‑0.7.1.post6‑cp37‑cp37m‑win_amd64.whl and louvain‑0.6.1‑cp37‑cp37m‑win_amd64.whl
You have to change to downloaded files directory and install it:
` pip install python_igraph‑0.7.1.post6‑cp37‑cp37m‑win_amd64.whl `
` pip install louvain‑0.6.1‑cp37‑cp37m‑win_amd64.whl `
#### Step 4:
` pip install stlearn`
### Popular bugs when install
DLL load failed while importing utilsextension: The specified module could not be found.
You need to uninstall package tables and install it again
` pip uninstall tables `
` pip install tables `
History
0.1.9 (2020-05-25)
0.1.8 (2020-05-21)
0.1.7 (2020-03-20)
0.1.6 (2020-01-31)
0.1.5 (2020-01-31)
0.1.4 (2020-01-30)
0.1.3 (2020-01-30)
0.1.2 (2020-01-30)
0.1.1 (2020-01-30)
0.1.0 (2020-01-30)
First release on PyPI.
2 maintainers
Metadata
2 maintainers
Release files for stlearn 0.1.9
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| stlearn-0.1.9.tar.gz | 19.4 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| stlearn-0.1.9-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 19.5 MB
Release files / stlearn-0.1.9.tar.gz
| Download URL | stlearn-0.1.9.tar.gz |
|---|---|
| Size | 19.4 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
1320a6616c95ec66af8ce9d4530c543ff9020e02273bd7532dfe6a4158ee3d65
|
|
BLAKE2b-256 checksum How to use checksums |
95e571770fe65f23cb857112d1ba5da7e6fcf70f58404864dbb34afc73204cfa
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0.post20200518 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.2
|
Release files / stlearn-0.1.9-py2.py3-none-any.whl
| Download URL | stlearn-0.1.9-py2.py3-none-any.whl |
|---|---|
| Size | 99.6 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
f23e14ded3a483f85e430a1f86c2fca8a5c3126f6b2d03ac0d84c307673f11a1
|
|
BLAKE2b-256 checksum How to use checksums |
f8e30f529f0717dc4667348c808e6f72625a68facd0ef84862141583677a6968
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/46.4.0.post20200518 requests-toolbelt/0.9.1 tqdm/4.46.0 CPython/3.8.2
|
