Changes for page SGA2 SP3 UC002 KR3.2 - Slow Wave Analysis Pipeline
Last modified by robing on 2022/03/25 09:55
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... ... @@ -5,25 +5,21 @@ 5 5 = (% style="--darkreader-inline-color:inherit; color:inherit" %)Slow Wave Analysis Pipeline(%%) = 6 6 7 7 (% class="wikigeneratedid" id="HUseCaseSGA2-SP3-002:IntegratingmultiscaledataA0inareproducibleandadaptablepipeline" %) 8 -(% style="--darkreader-inline-color:inherit; color:inherit; font-size:24px" %)**Use Case SGA2-SP3-002 KR3.2: Integrating multi-scale data in a reproducible and adaptable pipeline**8 +(% style="--darkreader-inline-color:inherit; color:inherit; font-size:24px" %)**Use Case SGA2-SP3-002: Integrating multi-scale data in a reproducible and adaptable pipeline** 9 9 10 - RobinGutzen^^1^^,Giulia De Bonis^^2^^, ElenaPastorelli^^2^^,CristianoCapone^^2^^,10 +To be discussed Author orders, contributions,...: 11 11 12 - Chiara DeLuca^^2^^, Marco Celotto^^2^^, Michael Denker^^1^^,Sonja Grün^^1^^,12 +Experiments: ...? 13 13 14 - Pier StanislaoPaolucci^^2^^,AndrewDavison^^3^^14 +Implementation: Robin Gutzen^^1^^, Elena Pastorelli^^2^^, ... 15 15 16 - Experiments:FrancescoPavone^^4^^,Maria-VictoriaSanchez-Vives^^5^^16 +Lead: Michael Denker^^1^^, Sonja Grün^^1^^, Pier Stanislao Paolucci^^2^^, Andrew Davison? 17 17 18 18 ,,1) Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany,, 19 19 20 -,,2) INFN Sezione di Roma, Rome,Italy,,20 +,,2) Dipartimento di Fisica, Università di Cagliari and INFN Sezione di Roma, Italy,, 21 21 22 -,,3) Unité de Neurosciences, Information et Complexité, Neuroinformatics group, CNRS FRE 3693, Gif-sur-Yvette, France,, 23 - 24 -,,4) LENS, University of Florence, 50019 Florence, Italy,, 25 - 26 -,,5) Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain,, 22 + 27 27 ))) 28 28 ))) 29 29 ... ... @@ -54,20 +54,19 @@ 54 54 **Copy the collab drive to your personal drive space** 55 55 56 56 * Open the Drive from the left menu 57 -* Select the folders //pipeline// and //datasets,// 58 -and the notebook// run_snakemake_in_collab.ipynb// 53 +* Select the folders //pipeline// and //datasets// 59 59 * Select 'Copy', and then 'My Library' from the dropdown 'Other Libraries' 60 60 61 61 ))) 62 62 * **Start a Jupyter Hub instance ** 63 63 In another browser tab, open [[https:~~/~~/lab.ebrains.eu>>https://lab.ebrains.eu]] 64 - 59 + 65 65 * **Edit the config files** 66 -Each stage has a config file (//pipeline/<stage_name>/config.yaml//)tospecify which analysis/processing blocks to execute and which parameters to use. General and specific information about the blocks and parameters can found in the README and config files of each stage. The default values are set for an example dataset (ECoG, anesthetized mouse, [[IDIBAPS>>https://kg.ebrains.eu/search/?facet_type[0]=Dataset&q=sanchez-vives#Dataset/2ead029b-bba5-4611-b957-bb6feb631396]]]).61 +Each stage has a config file to specify which analysis/processing blocks to execute and which parameters to use. General and specific information about the blocks and parameters can found in the README and config files of each stage. The default values are set for an example dataset (ECoG, anesthetized mouse, [[IDIBAPS>>https://kg.ebrains.eu/search/?facet_type[0]=Dataset&q=sanchez-vives#Dataset/2ead029b-bba5-4611-b957-bb6feb631396]]]). 67 67 68 68 * **Run the notebook** 69 69 In the jupyter hub, navigate to //drive/My Libraries/My Library/pipeline/showcase_notebooks/run_snakemake_in_collab.ipynb//, or where you copied the //pipeline// folder to. 70 -Follow the notebook to install the required packages into your Python kernel, set the output path, and execute the pipeline with snakemake. 65 +* Follow the notebook to install the required packages into your Python kernel, set the output path, and execute the pipeline with snakemake. 71 71 72 72 * **Coming soon** 73 73 ** Use of KnowledgeGraph API ... ... @@ -81,26 +81,26 @@ 81 81 82 82 * ((( 83 83 **Build the Python environment** 84 -In the wavescalephant git repository, there is an environment file ([[pipeline/envs/wavescalephant_env.yml>>https://drive.ebrains.eu/ lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/envs/wavescalephant_env.yml]]) specifying the required packages and versions. To build the environment, we recommend using conda ([[how to get started with conda>>https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html]]).79 +In the wavescalephant git repository, there is an environment file ([[pipeline/envs/wavescalephant_env.yaml>>https://drive.ebrains.eu/f/efe2ecf0874d4402bb11/]]) specifying the required packages and versions. To build the environment, we recommend using conda ([[how to get started with conda>>https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html]]). 85 85 ##conda env create ~-~-file /envs/wavescalephant_env.yml## 86 86 87 87 ))) 88 88 * **Edit the settings** 89 -The settings file specifies the path to the output folder, where results are saved to. Open the template file //[[pipeline/settings_template.py>>https://drive.ebrains.eu/ lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/settings_template.py]]//, set the ##output_path## to the desired path, and save it as //pipeline/settings.py//.84 +The settings file specifies the path to the output folder, where results are saved to. Open the template file //[[pipeline/settings_template.py>>https://drive.ebrains.eu/f/b6dbd9f15e4f4d97af17/]]//, set the ##output_path## to the desired path, and save it as //pipeline/settings.py//. 90 90 91 91 * **Edit the config files** 92 92 Each stage has a config file to specify which analysis/processing blocks to execute and which parameters to use. Edit the config template files //pipeline/stageXX_<stage_name>/config_template.yaml// according to your dataset and analysis goal, and save them as //pipeline/stageXX_<stage_name>/config.yaml//. A detailed description of the available parameter settings and their meaning is commented in the template files, and a more general description of the working mechanism of each stage can be found in the respective README file //pipeline/stageXX_<stage_name>/README.md//. 93 93 //Links are view-only// 94 -** full pipeline:[[ README.md>>https://drive.ebrains.eu/ lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/README.md]],[[config.yaml>>https://drive.ebrains.eu/f/fd37c5dd8970444fa217/]]95 -** stage01_data_entry: [[README.md>>https://drive.ebrains.eu/ lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage01_data_entry/README.md]], [[config.yaml>>https://drive.ebrains.eu/lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage01_data_entry/config_template.yaml]]96 -** stage02_processing: [[README.md>>https://drive.ebrains.eu/ lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage02_processing/README.md]], [[config.yaml>>https://drive.ebrains.eu/lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage02_processing/config_template.yaml]]97 -** stage03_trigger_detection: [[README.md>>https://drive.ebrains.eu/ lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage03_trigger_detection/README.md]], [[config.yaml>>https://drive.ebrains.eu/lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage03_trigger_detection/config_template.yaml]]98 -** stage04_wavefront_detection: [[README.md>>https://drive.ebrains.eu/ lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage04_wavefront_detection/README.md]], [[config.yaml>>https://drive.ebrains.eu/lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage04_wavefront_detection/config_template.yaml]]99 -** stage05_wave_characterization: [[README.md>>https://drive.ebrains.eu/ lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage05_wave_characterization/README.md]], [[config.yaml>>https://drive.ebrains.eu/lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage05_wave_characterization/config_template.yaml]]89 +** full pipeline:[[ README.md>>https://drive.ebrains.eu/f/ec474df6919a4089832e/]], config.yaml 90 +** stage01_data_entry: [[README.md>>https://drive.ebrains.eu/f/b46ffe259b3a4a51a277/]], [[config.yaml>>https://drive.ebrains.eu/f/8de751f48d7d47edaec1/]] 91 +** stage02_processing: [[README.md>>https://drive.ebrains.eu/f/7f19d89913624425bf63/]], [[config.yaml>>https://drive.ebrains.eu/f/b1607671f6f2468aa43c/]] 92 +** stage03_trigger_detection: [[README.md>>https://drive.ebrains.eu/f/94d12860dde84bbab7b1/]], [[config.yaml>>https://drive.ebrains.eu/f/6dfb712d5fa24f4f9fcf/]] 93 +** stage04_wavefront_detection: [[README.md>>https://drive.ebrains.eu/d/9c53abd5eaf543b28615/]], [[config.yaml>>https://drive.ebrains.eu/f/9534e46c4fae41c78f17/]] 94 +** stage05_wave_characterization: [[README.md>>https://drive.ebrains.eu/f/4d79f3e314474c22a781/]], [[config.yaml>>https://drive.ebrains.eu/f/1689dda03be04251b85f/]] 100 100 101 101 * **Enter a dataset** 102 102 There are two test datasets in the collab drive (IDIBAPS and LENS) for which there are also corresponding config files and scripts in the data_entry stage. So, these datasets are ready to be used and analyzed. 103 -For adding new datasets see //[[pipeline/stage01_data_entry/README.md>>https://drive.ebrains.eu/f/b46ffe259b3a https://drive.ebrains.eu/lib/905d7321-a16b-4147-8cca-31d710d1f946/file/pipeline/stage01_data_entry/README.md4a51a277/]]//98 +For adding new datasets see //[[pipeline/stage01_data_entry/README.md>>https://drive.ebrains.eu/f/b46ffe259b3a4a51a277/]]// 104 104 105 105 * **Run the pipeline (-stages)** 106 106 To run the pipeline with snakemake ([intro to snakemake]()) activate the Python environment ##conda activate wavescalephant_env,## make sure you are in the working directory `pipeline/`, and call ##snakemake## to run the entire pipeline. ... ... @@ -112,8 +112,6 @@ 112 112 113 113 == References == 114 114 115 -* De Bonis, Giulia, et al. "Analysis pipeline for extracting features of cortical slow oscillations." //Frontiers in Systems Neuroscience// 13 (2019): 70. 116 -* Celotto, Marco, et al. "Analysis and Model of Cortical Slow Waves Acquired with Optical Techniques." //Methods and Protocols// 3.1 (2020): 14. 117 117 118 118 == License (to discuss) == 119 119