IOCBIO Kinetics: An open-source software solution for analysis of data traces

Biological measurements frequently involve measuring parameters as a function of time, space, or frequency. Later, during the analysis phase of the study, the researcher splits the recorded data trace into smaller sections, analyzes each section separately by finding a mean or fitting against a specified function, and uses the analysis results in the study. Here, we present the software that allows to analyze these data traces in a manner that ensures repeatability of the analysis and simplifies the application of FAIR (findability, accessibility, interoperability, and reusability) principles in such studies. At the same time, it simplifies the routine data analysis pipeline and gives access to a fast overview of the analysis results. For that, the software supports reading the raw data, processing the data as specified in the protocol, and storing all intermediate results in the laboratory database. The software can be extended by study- or hardware-specific modules to provide the required data import and analysis facilities. To simplify the development of the data entry web interfaces, that can be used to enter data describing the experiments, we released a web framework with an example implementation of such a site. The software is covered by open-source license and is available through several online channels. Author summary In biological and other types of experiments, we frequently record changes of some parameters in time or space. It is common to analyze the data by splitting the recording into smaller sections and relating it to some changes induced by the researchers. The steps involved in the analysis are: splitting of the data, fitting them to some function, relating the fit result to the change in the environment, and normalization. These steps are frequently done through several software packages, spreedsheets, and manual copy and paste between the programs. The software presented in this work allows to make all these analysis steps in one database in a manner that is easy, can be reproduced by others, and clearly tracks the history of all the analysis steps. In addition, it allows to link the experimental data with the description of the experiment, making it simple to perform tasks such as normalization of the recorded values, relating experimental recordings to the sample or animal, as well as extracting data from the laboratory database for publishing. The software is written to be easily extendable by user-defined modules to fit the analysis pipelines and is expected to improve the data analysis practices in research.