Related Experiment Video
Updated: Aug 18, 2025
07:56
Genome Editing in Mammalian Cell Lines using CRISPR-Cas
Published on: April 11, 2019
21.9K
Contemporaneous sample data tracking for the generation of genome edited cell lines
Anne L Plant1, Michael W Halter2, Jeffrey R Stinson2
1Materials Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD, 20899, USA. anne.plant@nist.gov.
Scientific Reports
|December 9, 2022
Summary
Researchers developed a flexible spreadsheet-based method for real-time capture of detailed laboratory actions in biomedical research. This approach enhances data organization and interoperability for gene-edited pluripotent stem cell (PSC) line development.
Area of Science:
- Biomedical research
- Stem cell biology
- Bioinformatics
Background:
- Biomedical research generates extensive data, posing challenges for detailed record-keeping and analysis.
- Current experimental workflows often lack integrated systems for real-time data capture and organization.
Purpose of the Study:
- To present an adaptable, spreadsheet-based approach for capturing detailed experimental actions.
- To facilitate real-time data logging compatible with experimentalist workflows.
- To improve data organization and interoperability in gene editing research.
Main Methods:
- Utilized commercial spreadsheet software for ease of adaptation by researchers.
- Designed the system for real-time capture of laboratory actions in gene editing workflows.
- Implemented a sample- and file-naming convention for automated folder creation.
- Enabled data export in open standard formats (XML, CSV) for repository integration.
Main Results:
- Demonstrated a practical method for capturing detailed experimental steps in gene editing.
- Showcased automated organization of documentation and data via a file-naming convention.
- Facilitated real-time data logging and simple querying by experimentalists.
- Enabled export of collated data for interoperability with data repositories.
Conclusions:
- The spreadsheet-based approach offers a flexible and intuitive solution for detailed experimental data capture.
- This method enhances local data organization and facilitates integration with larger data management systems.
- The approach is generalizable to various experimental applications beyond pluripotent stem cell line development.
