In the research lab of a mid-size research firm, data is being collected directly at the bench. This collection is either in paper notebooks or in spreadsheets because experimental endpoints evolve very quickly in this organization, and the freedom granted by a spreadsheet allows them to perform research at a fast and flexible pace.
As the Snthesis software captures the scientist’s spreadsheets the system automatically validates that the input meets the requirements for that experiment and confirms that assay data can be connected to sample preparation data. Any data quality issues the system identifies are corrected directly by scientists. The platform then consolidated these individual spreadsheets into a single master record of sample and assay data. This aggregated master record is downloaded and used by scientists directly to perform basic analysis on their local machines.
Importantly, all data required for the experiment at hand is validated. Any one-off metadata data is also captured and preserved in case there is a future need to add additional data points to a particular experimental workflow. Everything is captured and made available, often eliminating additional future work on that experiment.
Sometimes a single sample is used in multiple assays, or may be shipped to external partners for more specialized experiments. In those cases, the sample teams upload their data directly to the system as “standalone” data. Later, as results are produced, the scientists upload them independently. The Snthesis platform automatically makes the connection and links the sample data with the results data, eliminating the need to manually merge spreadsheets from collaborators.
As assays evolve, the team easily adjusts the metadata and linking requirements using tools built into the platform, enabling versioned tracking of data requirements. The system always validates and confirms data quality against the latest parameters as it’s collected. Older data can be automatically up-converted to the newest version, from renaming columns to populating missing values from new fields. The aggregated data (old and new) is always in sync and mirrors the latest set of data requirements.
The analysis can only be as good as the data that flows into it. Snthesis Bio provides oversight and validation to ensure that the data feeding your analysis is clean, connected and complete.
In the research lab of a mid-size research firm, data is being collected directly at the bench. This collection is either in paper notebooks or in spreadsheets because experimental endpoints evolve very quickly in this organization, and the freedom granted by a spreadsheet allows them to perform research at a fast and flexible pace.
As the Snthesis software captures the scientist’s spreadsheets the system automatically validates that the input meets the requirements for that experiment and confirms that assay data can be connected to sample preparation data. Any data quality issues the system identifies are corrected directly by scientists. The platform then consolidated these individual spreadsheets into a single master record of sample and assay data. This aggregated master record is downloaded and used by scientists directly to perform basic analysis on their local machines.
Importantly, all data required for the experiment at hand is validated. Any one-off metadata data is also captured and preserved in case there is a future need to add additional data points to a particular experimental workflow. Everything is captured and made available, often eliminating additional future work on that experiment.
Sometimes a single sample is used in multiple assays, or may be shipped to external partners for more specialized experiments. In those cases, the sample teams upload their data directly to the system as “standalone” data. Later, as results are produced, the scientists upload them independently. The Snthesis platform automatically makes the connection and links the sample data with the results data, eliminating the need to manually merge spreadsheets from collaborators.
As assays evolve, the team easily adjusts the metadata and linking requirements using tools built into the platform, enabling versioned tracking of data requirements. The system always validates and confirms data quality against the latest parameters as it’s collected. Older data can be automatically up-converted to the newest version, from renaming columns to populating missing values from new fields. The aggregated data (old and new) is always in sync and mirrors the latest set of data requirements.
The analysis can only be as good as the data that flows into it. Snthesis Bio provides oversight and validation to ensure that the data feeding your analysis is clean, connected and complete.
