llsmvis
llsmvis is a collection of codes that we used to analyze the datasets acquired in the following study:
Yi, X., Miao, H., Lo, J.K.Y., Elsheikh, M., Lee, T.H., Jiang, C., Segelke, B.W., Overton, K.W., Bremer, P.T. and Laurence, T.A., 2022. A Tailored Approach To Study Legionella Infection Using Lattice Light Sheet Microscope (LLSM). bioRxiv. doi: https://doi.org/10.1101/2022.03.20.485032
Prerequisits: Python, Conda, Git, Jupyter notebook
Relevant datasets
The datasets are available on figshare (find it here).
Getting started
- Install Anaconda.
- Clone the repository.
git clone https://github.com/xiyuyi-at-LLNL/llsmvis.git - Configure the conda virtual environment.
conda env create -f mac_env.yml(tested for MacOS Majave 10.14.3)`
For LC users
-
Install anaconda: on LC: After login onto LC, go to the path of anaconda installers:
cd /collab/usr/gapps/python/$SYS_TYPE/conda install anaconda3: bash ./Anaconda3-2019.10-Linux-x86_64.sh Follow the prompted instructions to activate anaconda, and initialize conda.
reference: https://hpc.llnl.gov/software/development-environment-software/python
-
Create a virtual environment for llsmvis under folder llsmvis:
bash llsmvis-setup
Data processing for LC users (to deskew acquired datasetes)
To process all the raw ata after an imaging session with multiple stacks and various imaging conditions.
- activate the llsmv conda environment
conda activate llsmvis
- copy ./tools/getdsk into the data file folder and run it.
./getdsk
answer the prompted questions accordingly, and you'll find the results under folder 'results_dsk'
Note
This work was produced under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. Release number: LLNL-CODE-834237
Developers (update on 2022-05-06):
Yi, Xiyu; Miao, Haichao; Chenfanfu Jiang; Bremer, Peer-Timo; Laurence, Ted A.; Zhang Yuliang.