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gchure committed May 25, 2018
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#`mscl_survival`
# `mscl_survival` #

This repository contains all Python code, Jupyter Notebooks, small data files, and the full text for the publication "Connecting the dots between mechanosensitive channel abundance, osmotic shock, and survival at single-cell resolution." We encourage the scientific community to fork this repository and open constructive issues that will improve and/or correct any writing in this work. The general architecture of the repository is described below.

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This repository contains all processing, analysis, and figure code used in this work. Within `code`, there five subfolders separated by document type.

1. **`analysis`**
Contains Python scripts (`.py`) that conduct the major analysis described in the work. This includes all Markov chain Monte Carlo analyses.
1. **`analysis`**: Contains Python scripts (`.py`) that conduct the major analysis described in the work. This includes all Markov chain Monte Carlo analyses.

2. **`figs`**
Contains Python scripts (`.py`) used to generate the main text and supplementary information figures.
3. **`notebooks`**
Contains a Jupyter notebook that walks through the image analysis pipeline.
4. **`processing`**
Contains all experimental processing. Each folder within `processing` is separated by date, strain, and shock rate. Each folder contains a Python script `.py` that performs all image processing and saves a `.csv` for that experimental run.
5. **`stan`**
All `stan` models which were used in the MCMC.
2. **`figs`**: Contains Python scripts (`.py`) used to generate the main text and supplementary information figures.
3. **`notebooks`**: Contains a Jupyter notebook that walks through the image analysis pipeline.
4. **`processing`**: Contains all experimental processing. Each folder within `processing` is separated by date, strain, and shock rate. Each folder contains a Python script `.py` that performs all image processing and saves a `.csv` for that experimental run.
5. **`stan`**: All `.stan` models which were used in the MCMC.

## `data/csv` ##

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This is a Python module which contains all invariant functions used for processing, analysis, and plotting. It is structured as a typical Python module that can be imported. There are several components to this module, described below.

1. **`image.py`**
Contains functions related to the loading, manipulation, and processing of the raw microscopy images and parsing the `.xml` files produced through manual identification of survivors and fatalities.
1. **`image.py`**: Contains functions related to the loading, manipulation, and processing of the raw microscopy images and parsing the `.xml` files produced through manual identification of survivors and fatalities.

2. **`mcmc.py`**
A set of functions that manipulate the output from `pystan` sampling.
2. **`mcmc.py`**: A set of functions that manipulate the output from `pystan` sampling.

3.**`plotting.py`**
Functions for generating standard plots and setting the plotting style.
3.**`plotting.py`**: Functions for generating standard plots and setting the plotting style.

5.**`stats.py`**
A set of functions that compute numerous frequently used statistics.
5.**`stats.py`**: A set of functions that compute numerous frequently used statistics.


## Contact ##
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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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