Fall Workshop on DIA and Getting More Biology

Remember to Bring!

All participants must show a negative Covid test result AND proof of vaccination. Masking required except when eating or drinking. Be prepared, read more on Health & Safety page.

All participants must bring a laptop with them for use during the workshop. We recommend you bring a PC laptop and have credentials to load software (some company laptops have security protocols preventing this).

Registration and Breaks

Monday, November 7
7:30 - 9:00 am Registration, Kon Tiki Ballroom

  • Badge pickup
  • Have your proof of vaccination AND proof of negative COVID test result easily accessible and available to show.
  • Enhanced continental breakfast with breakfast sandwiches will be served, so arrive early!

9:00 am Fall Workshop begins, Kon Tiki Ballroom

10:00 - 10:30 am  Coffee Break

12:00 - 1:00 pm  ASMS hosted lunch provided to attendees, Beachside North

3:00 - 3:30 pm  Coffee Break

5:00 pm  Fall Workshop instruction ends for the day

5:00 - 6:00 pm  Reception, Kon Tiki Ballroom

Tuesday, November 8

7:30 - 9:00 am  Enhanced continental breakfast with breakfast sandwiches will be served

9:00 am  Fall Workshop instruction begins, Kon Tiki Ballroom

10:00 - 10:30 am  Coffee Break

12:00 - 1:00 pm  ASMS hosted lunch provided to attendees, Beachside North

3:00 - 3:30 pm  Coffee Break

5:00 pm  Workshop concludes

Detailed Program of Instruction

Monday, November 7

9:00 am - 12:00 pm, DIA-MS Introduction

The goal of this session is to introduce the workshop participate to differences in DIA-MS data acquisition and data analysis while setting up comparison of peptide- verses spectrum-centric data analysis of DIA-MS generated data.

Introduction to DIA Concepts, Drive for Reproducible Large Scale Datasets and Comparison of Different Data Acquisition Methods for Q-Orbitrap, Q-TOF, IMS-TOF, etc. Brian Searle (The Ohio State University), 30 minutes

Peptide-Centric Approaches for Data Analysis (e.g. Open-SWATH, Skyline, EncyclopeDIA, Spectronaut), Lilian Heil (University of Washington), 30 minutes

Coffee Break

Spectrum-Centric Approaches for Data Analysis (e.g. Pular-X, DIA-Umpire), Alexey Nesvizhskii (University of Michigan), 30 minutes

SKYLINE Tools and Applications Including Quantification, Brendan MacLean (University of Washington), 30 minutes

Small Group Discussion: Current Challenges and Issues in DIA-MS, Specifically around Robustness and Scalability. (Hannes Roste, Michael MacCoss and Niveda Sundararaman will lead discussion), 30 minutes

1:00 - 5:00 pm, Digging into the Nitty Gritty of Software and Analytics around DIA-MS

The goal of this session is for workshop participates to examine DIA-MS data sets using the two primary approaches and to understand the underlying assumptions and limitations of peptide- and spectrum-centric data analysis approaches and how new emerging methods may address some of these challenges. This session is comprised of two parts: The first part is a hands-on tutorial using pre-generated data sets followed by small group discussion. The second part is on new and emerging approaches for analyzing the same data set, followed by discussion.

Hands-On SKYLINE Tutorial, Brendan MacLean (University of Washington), 30 minutes

Hands-On Tutorials Using Thermo Fisher Orbitrap and Bruker timsTOF Instruments on the Same Real Data.

  • Effect of Missingness and Linearity of Quantitation: Expolresis on Same Data Analyzed by DIA-NN and EncyclopeDIA, Michael MacCoss, Deanna Plubell and Aaron Maurais (University of Washington), 45 minutes
  • Effect on Library Size and Type: timsTOF Data Using TIMS-DIA-NN, discussion on different approaches on library and filtering and look at linearity on CV% and timsTOF data, Qin Fu, Niveda Sundararaman and Alek Binek (Cedars-Sinai Medical Center), 45 minutes

Coffee Break, 30 minutes

New and Emerging Approaches. In this session, each new approach will outline the novelty and the pros and cons compared to peptide- and spectrum- centric approaches based on showing the data generated on the same model data set as above.

New Approach: DeepSearch, Gautam Saxena (DeepDIA), 20 minutes

New Approach: AI, Robin Park (Scripps), 20 minutes

Update on New Approaches with a Focus on Unmet Needs, Hannes Rost (University of Toronto), 20 minutes

Panel Discussion: Current Challenges in Data Acquisition and Data Handling. The focus is on establishing the issues around misintergpreting specta and establishing what should be the gold standard. Brian Searle, Michael MacCoss, Niveda Sundararaman, 30 minutes

Reception, 1 hour 

Tuesday, November 8

9:00 am - 12:00 pm, Establishing Reproducible DIA-MS Research

The goal of this session is to provide real-life examples focusing on quality control, reproducibility of data and highlighting lessons learned sets.

  • Sample Preparation and Automation, Qin Fu (Cedars-Sinai Medical Center), 20 minutes
  • Setting Up Systems Suitability, Process Control and QC for Sample Preparation, Deanna Plubell (University of Washington), 20 minutes
  • Full System Automation with Tracking and Automated Data Reports, Sarah Parker (Cedars-Sinai Medical Center), 20 minutes
  • What Is Wrong with This Data? Michael MacCoss (University of Washington), 20 minutes

Small Group Discussion, 40 minutes
Discuss the challenges and potential solutions based on a series of targeted questions. Questions will include:

  • What are criteria for quantification if based on a single peptide, and then extract those criteria to if you have to quantify 20,000 peptides?
  • Is identification equal to quantification? Is quantification equal to precision on different instruments?
  • What is the strategy for using DIA-MS on PTMs that can be isolated in different DIA-windows (e.g., mono-, di- versus tri-methylation)? What is the strategy for using DIA-MA on PTMs that cannot be isolated in different DIA-MA windows (e.g., citrullination, deamidation, etc.)?

Discussion and brainstorming by the full group, 30 minutes

1:00 - 5:00 pm, Pushing DIA-MS into Large Scale Reproducible Science 

The goal of this session is to provide real-life examples of the lectures, focusing on real questions and reproducibility of data and highlight the lessons learned.

Case Study 1: 350 CSF Samples from Different Disease Categories. Challenge: Sample Numbers and Individual Variation. Michael MacCoss (University of Washington), 40 minutes

Case Study 2: 1,000 IPSC Derived Motor Neurons for Answer ALS. Challenge to overcome are samples arriving over time. DIA-MS carried out on 6600 triple tof. Jennifer Van Eyk and Niveda Sundararaman (Cedars-Sinai Medical Center), 40 minutes

Case Study 3: Single Cell (Aorta). Challenge: Scaling down the input and scaling up data acquisition and analysis. Sarah Parker (Cedars-Sinai Medical Center), 40 minutes

Panel Discussion: Will summarize needs and next steps in DIA-MS applications. Moderated by Qin Fu and Lilian Heil, 60 minutes

Summary and Conclusion, 30 minutes