The Basics

+ What is the aim of the Alpha Trial?

We are working with a small group of Mass Spec experts to validate that Mass Dynamics works as expected. Once we know that the results are better than today's benchmark, we will start rolling out access to the masses.

We are looking for feedack and validation in the following areas:

  • Are the results better than what you have achieved with your existing workflow?
  • Were you pleased with the experience? Was it easy to use?
  • What features would you like to see next?
  • On completion of the workflow, what would you typically do next and what can we build to support this?
  • Was there anything that confused you?
  • Would you use Mass Dynamics again?

We thank you for your support in helping us through the Alpha Trial.

+ How do I get started with the Alpha Trial?

The Alpha Trial is a closed activity, therefore you will need get the ok from a Mass Dynamics team member. You will then need to sign up here which will secure your spot. On completion of the form, we will get you started by sending you an invitation to Slack (our communications tool of choice). It's here that we will setup your username and password, send you the Mass Dynamics URL and also answer any questions that you may have.

+ How long does the Alpha Trial go for?

The Alpha Trial will close at the end of April.

+ How much does it cost?

Use of the Alpha Trial is free. In exchange for the free results processing, we ask users to provide feedback via a survey at the end of the 2 month Alpha Trial

+ How long should I expect to receive my results?

While your results should be available to you within a few days, the Alpha Trial may uncover unexpected issues which may cause delays. We’ll keep you up to date on Slack.


Getting started

+ What data do I need to get started?

At Mass Dynamics, we've made it simple to get started. If you have raw or converted files that have been produced using a ThermoFisher Mass Spectrometer instrument, you're good to go.

For the Alpha Trial, we will require that you upload a FASTA file so that we understand the context of your experiment. If you don't have one, you can download one from the Uniprot website.

+ What types of experiments can I use Mass Dynamics for?

The Alpha Trial is limited to Data-Dependant Acquistion, Label-Free Quantitative (DDA LFQ) methods and we will be introducing additional methods in the future.

We recommend the first experiment that you run on Mass Dynamics is one that is:

  • a DDA LFQ experiment
  • Limited to 24 runs
  • Has been created using ThermoFisher mass spectrometers
  • Has been analysed previously (to ensure a more efficient and easier comparison)

+ Is it compatible with all Mass Spectrometry instruments’ raw data?

Mass Dynamics will be compatible with all instruments, and for the Alpha Trial we are focussing on ThermoFisher.

Workflow Mechanics

+ What does the Mass Dynamics workflow do?

Starting with the upload of your raw or converted MS files, Mass Dynamics automates the following steps in the Proteomics Data Analysis workflow:

  • Feature Detection
  • Deconvolution
  • Consensus Mapping
  • Cloning
  • Database Searches
  • Protein Inference
  • Extracted-Ion Chromatogram
  • Machine Learning

Mass Dynamics is made possible thanks to clever cloud computing, machine-learning algorithms and exceptional Proteomics expertise.

+ Why are there so few parameters needed?

We have intentionally built the Alpha Trial for simplicity as we want Mass Dynamics to be a tool for the masses. We have limited the number of parameters required, and can activate particular parameters on request.

+ How does Mass Dynamics handle Missing Values?

Historically, a drawback of the Data-Dependant Approach (DDA) has been the number of missing values (MV) that are generated. To address this challenge, Mass Dynamics has developed a more sensitive 'match between runs' workflow that now provides a reliable quality metric and filtering (1% FDR cut-off for matches). Missing values, are now more likely exactly that.

To facilitate calculation of P-Values, Mass Dynamics imputes missing values by drawing values from a normal distribution with mean equal to the mean of the measured intensity distribution minus 2.5 standard deviations of the measured intensity distribution, and a standard deviation that equals 0.3 times the standard deviations of the measured intensity distribution.

The workflow moves the distribution of imputed measures to lower values, mainly because our machine-learning process yields a low number of missing values, so the distribution of imputed values does not affect the distribution of real intensity measures. It has the benefit of not imputing at the same level of low abundant protein/peptides.

+ How does the workflow define the term "reliably identified"

It's defined as: peptide MS1 feature that has been detected in at least 50% of at least 1 condition in the experiment.

It's important to be transparent and explicit on this definition as it is an arbitrary cutoff that can be defined in different ways by different operators. While we aim to enable the setting of such a parameter in the future, the default is set to 50% in at least one group.

+ How many peptides are used for the protein quantification?

The workflow uses peptides that are deemed as “reliably identified" for quantitative purposes” in the experiment. See definition above.

+ What is the identification False Discover Rate (FDR) cut off?

The workflow identification FDR cutoff is 1% and is applied to peptide-spectrum match (PSM), peptide and protein identification tables.

The worflows' protein inference step is a work-in-progress for the Alpha Trial purposes and at this stage is considered conservative, and reporting much smaller numbers of proteins in comparison to state-of-the-art. A more comprehensive solution will be avaiable shortly. Should you wish to compare our workflow results to other solutions, we recommend comparing the number of identified peptides identied at this interim stage.

It's worth noting that we report an FDR on the MS1 feature detection. Thanks to our machine learning processes, our workflow reports a measure of “confidence” that a feature is actually a real MS1 feature. This is a great advantage over other feature detection techniques and “match between runs”, where there is no measure of accuracy of detection and matching.

+ Are the proteins filtered, e.g. the proteins identified only some but not all biological replicates in one group?

The workflow does not filter proteins based on the number of peptide identified, hence all proteins are reported. If a protein does not have any peptide that is defined as “reliably identified” it will not have a quantitative value in any of the experimental conditions. See definition above.

For example, a protein has 2 peptides identified but only one peptide is detected in more then 50% of samples in one group, our workflow calculates a protein quantitative value for all the samples where that peptide has been detected, while the other samples will be “missing values”. If none of the peptides are detected “reliably” then the workflow does not calculate the protein quantitative value. The identification information remains in the table and all of the quantitative information will be blank.

+ How are p-values calculated?

The p-values are calculated using ANOVA and the pairwise comparisons with Tukey’s post-hoc analysis, all p-values are corrected for multiple testing by “Benjamini-Hochberg” so they are in fact FDR values. This is a work-in-progress for Alpha Trial purposes and an implementation of “limma” and “SAM” tests will be available shortly.

+ What results files will Mass Dynamics create for me?

When Mass Dynamics has finished processing your files, you will be notifed. Once you log in, you will be given access to your results files that you can download. This includes:

  • A Quality Control (QC) report
  • Feature Tables
  • Peptide Intensity
  • Peptide Table
  • Protein Intensity
  • Protein Table
  • Features Identified
  • Features All
  • MS2

Everything else

+ Can I share the results with my peers or team leaders?

You sure can. And if you would like to use the results for any other purposes outside of the Alpha Trial, please get in contact with us so the results can be validated.

+ What will happen with my data during and after the Alpha Trial?

All results files that are produced by Mass Dynamics are owned by the submitter of the experiment (researcher). If the workflow’s results wish to be used for any other purposes outside of the Alpha Trial, please get in contact with MD so the results can be validated.

Ingested raw data and results files will only be stored for the duration of the Alpha Trial. It will then be deleted and not accessible by Mass Dymamics or the submitter of the experiment (researcher). Files can be downloaded and saved locally at any given during the Alpha Trial.


Getting in touch

+ Slack and MD

Slack is a platform that connects teams with apps, services, and resources they need to get work done. This will be the main channel that the MD team will communicate with you throughout the Alpha Trial.

If you don't yet have an account:

  • Sign up for one - it's free
  • Email the MD team on and let them know which email address you use for Slack
  • Wait to receive an email adding you to the Mass Dynamics Community Slack workspace
  • Follow the Slack instructions in the email