Welcome to the latest release notes for CODI Apps and Batch Analysis! For questions about the new software release, please contact our Customer Success team on https://help.codi.bio/ or any software team member directly via ONI-Club slack channel. You can find more information about the new features in the how-to guide on the CODI-help center.

PRODUCT OVERVIEW

Software Product: CODI
Software Update: Apps and Batch Analysis
Release Date: June 2023

NEW FEATURES

CODI Apps and Batch Analysis

We always envisioned CODI to be the tool that unlocks super-resolution microscopy for researchers all around the globe. With this big release, we’re setting the foundation to bring you all kinds of powerful App workflows in the form of Apps, that will allow you to focus on your research questions, and not worry about the data analysis software. We’re also delivering a new function to analyze multiple datasets at once, so that you can spend more time doing research and minimize any tedious manual data analysis.

Introducing CODI Apps 

Now, with the new CODI Apps infrastructure, CODI offers not just one, but multiple analysis workflows designed to address your biological questions and experimental needs. Each App offers a complete analysis workflow developed to help quantify single- molecule microscopy data. In addition to these exciting updates, we are also bringing one of our most requested features, batch analysis, to the newest version of CODI. With these new updates, you can now create, collaborate, save, and run end-to-end batch analysis workflows all in the cloud! 

Some examples of the new App workflows available you will have with this release are:

1. Clustering: Quantify statistical and morphological properties of your dSTORM or DNA-PAINT data.
2. Clustering & Counting: Explore subpopulations and quantify statistical and morphological properties of your dSTORM or DNA-PAINT data
   
3. EV Profiling: Quickly identify subpopulations with single EV precision with a customized Clustering workflow.

This is just the start. This release enables us to rapidly introduce new applications to support all aspects of your super- resolution workflows on CODI and sets us up for delivering some really exciting things to come in the near future.

For this first release, we have worked with internal teams as well as Alpha and Beta testers to configure CODI Apps to include default parameter settings to guide users through basic single- molecule analysis. We recommend starting with these default settings first, then tweaking the parameters to fit each dataset. Once you have optimized your workflow, you can simply save and reuse it on other dataset individually or using the new Batch Analysis tool to be consistent across datasets pertaining to the same experiment. 

What’s new:

1. CODI Apps:  Analysis Apps offer a complete analysis workflow for a variety of super- resolution experiment types with cloud- based storage and processing.  
   
2. Settings: We provide essential settings for each App, but also allow for user-defined settings that can be saved and re-run on future datasets individually or as part of a batch analysis.
   
3. Results: Experiments are about results, but you often need to tweak your analysis parameters before coming to conclusions. CODI Apps keeps track of your parameter changes and their effect on your results, so you can feel free to explore different analysis pipelines on the same dataset view at once. 
   
4. Fast-forward: Select an App and settings, and simply hit play to run an entire analysis workflow on any dataset automatically (see Running analysis tools section). 
   
5. Batch Analysis: Add statistical power to your experiments quickly by analyzing multiple datasets within the same collaboration with the same settings. Simply select multiple datasets within a collaboration, apply an analysis App and settings to initiate batch analysis. Follow the progress of batch processing and download your results when it’s done.
   

Known Limitations

1. Large Number of Datasets: If you are working with a very large collaboration containing hundreds of datasets, the results view may take some time to display the list of single and batch analysis results.
   
2. Delay when Starting Batch Analysis: When you trigger a batch analysis, it may take a few seconds between starting each analysis in the batch, but they will eventually all be started. So the more datasets you analyze in a batch, the longer it will take for all results to appear in the results view of the collaboration. Similarly, the batch download screen does not update automatically and must be refreshed to display the correct status of whether a result is still running or has completed.
   
3. Batch Analysis Limited to Datasets in a Collaboration: A batch analysis can only be run on datasets in the same collaboration, but you can apply the same analysis settings to datasets in different collaborations.
   
4. Multi-channel Dataset Limitation: If you try to run an analysis App on a multi-channel dataset that has no data in one of the channels, the analysis will fail.