What Inputs Does TraceBase Take

TraceBase takes 3 kinds of input data:

  • Raw Mass Spectrometry Peak Data
    • RAW files from the Mass Spec Instrument
    • mzXML files
  • Corrected Mass Spectrometry Peak Data
    • We refer to these inputs as peak annotation files
    • Used initially to extract experimental metadata
    • Included in the final submission with associated raw data
  • Experimental Metadata
    • All experimental metadata (e.g. sample details, compounds, protocols, etc) is entered into a single Excel file
    • We refer to this input file as the Study Doc

The experimental metadata includes some nomenclature-controlled metadata to make sure all data is inter-comparable and reliably searchable across studies. See How TraceBase Handles Data for more information on how TraceBase treats both input and output data.

Raw Mass Spectrometry Peak Data

TraceBase currently supports 2 forms or raw Mass Spec files"

  • RAW files produced by a Mass Spec instrument
  • mzXML files containing a portion of the RAW data that are typically used in peak correction

TraceBase archives each of these file types to make them searchable in order to find unanalyzed peak data for future studies (as opposed to the curated corrected data that TraceBase provides calculated values for, like FCirc Rates).

A collection of either form of raw file is too large and impractical to provide via upload on the web, so study submissions are delivered for loading using a shared drive, as described on the Upload Submit page.

The mzXML files are parsed by TraceBase to extract:

  • Polarity
  • Scan Range

Corrected Mass Spectrometry Peak Data

TraceBase supports the output from 3 popular tools for natural abundance correction:

Therefore, a typical workflow to put data in TraceBase could start with:

  1. Create mzXML files from the Mass Spec instrument's RAW files using conversion tools like
    • ProteoWizard's MSConvert
    • OpenMS FileConverter
    • custom scripts
  2. Select peaks from a set of mzXML files using peak-picking tools like
  3. Create a peak annotation file using one of the natural abundance correction tools mentioned above

Tracebase can take any of the 3 peak annotation file types (AccuCor, IsoCor, or Iso-AutoCor) in any one of 3 formats:

  • Microsoft Excel Spreadsheet
  • Corrected data sheet only in one of 2 plain text formats (e.g. using NotePad or TextEdit):
    • CSV (comma separated values)
    • TSV (tab separated values)

Peak annotation files are included in 2 steps during the upload process:

  • They are used on the Upload Start page to stub out a Study Doc template to get a jump start on experimental metadata entry.
  • They are included in the final submission, organized into folders on a shared drive with their associated raw files.

^ The GitHub version of IsoCor is called isocorr13C15N. These two terms are used interchangeably on TraceBase.

Experimental Metadata

To empower the user and engender a sense of ownership and control over your data, all experimental metadata (even the nomenclature-controlled metadata that subject to curator oversight), is localized in a single Excel document that you build during the submission process.

TraceBase is designed to match an LCMS sample name to a biological sample. In a submission, the sample names and the compounds are extracted and processed from the peak annotation files. It's not possible to extract all other metadata automatically, thus much of this data entry is manual, but the data is organized around how researchers tend to store this kind of data.

Some researchers keep a single list of Animal IDs for all experiments. This works well for TraceBase, because each Animal ID is unique. Other researchers keep a list of animal IDs for each experiment (aka "Study"). In this example, the study should have a unique identifier and that should be combined with the animal identifier (e.g. study001_mouse001). This also works well for TraceBase.

If the Animal ID or Sample ID is not unique, upload is more difficult but still achievable. Feel free to enter what you have and TraceBase curators can help make your data compatible.

Note that these labeling schemes can be applied to your general organization of data outside of tracebase: * For a new experiment, create a new identifier counting up from study001 * A related follow up experiment may have an extension, e.g. study001b, study001c * Any text could be used in place of "study" * Within each experiment, count animal identifiers study001_m01, study001_m02... * When labeling sample files, provide full animal identifier, tissue, and sometimes time collected: * E.g. study001_m01_quad, study001_m01_tailserum_000, study001_m01_tailserum_120 * When working with samples in the lab, it is not feasible to label every tube with the full identifier, but shorthand can be used for intermediate tubes if everything is from the same study: * E.g. for tissue extraction from study001, label working tubes Q_1, Q_2.... Label final tubes 001_m1_Q * Data and any other information related to your experiments can be organized in folders labeled for each study study001_my first infusion, study001b_fixing my first infusion