1 / 38

PREMIER Biosoft

PREMIER Biosoft. Accelerating Research in Life Sciences. A High Throughput Lipid Characterization Tool using MS Data. Major Features. Database containing 40,298 lipid structures.

bobg
Télécharger la présentation

PREMIER Biosoft

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. PREMIERBiosoft Accelerating Research in Life Sciences

  2. A High Throughput Lipid Characterization Tool using MS Data

  3. Major Features • Database containing 40,298 lipid structures. • 5211 set masses (transitions) of PIS/NLS experiments for fatty acid chains, and head groups of lipid species from different classes and sub-classes. • Identify target lipids based on exact mass database search, and the target headgroup, or fatty acid chain corresponding to the set masses of the PIS/NLS experiments. • Isotope peak correction to facilitate accurate quantitation of lipids.

  4. Major Features • Align lipids across biological samples based on short name e.g., PC(28:2); name without double bond positions e.g., PC(18:1/18:1) instead of PC(18:1(9Z)/18:1(9Z)). • Calculate normalized response of analytes w.r.t. the response of the internal standards that belong to the same class/subclass. • Heatmap, Concentration X Composition reports of lipid classes, and fatty acid chains. • Additional lipid ontology based filters, e.g., only even/odd numbers of double bonds, and carbon (C) atoms in the fatty acid chains of target lipids.

  5. Create a New Project 1. File > New > Project 2. Enter a project name 3. Click Create

  6. Import Data from Native as well as Standard Data Files 1. File > Open > Peaklist Data > Waters Data File > QqQ (.raw)

  7. Shortcut for Importing “Waters” Data 1. Select Waters > QqQ (.raw) 2. Select the file(s) 3. Click Open

  8. Enter PIS/NLS Target Masses for Each Function Within a File 2. To average MS2 level data select “Specify Range” option 3. Click OK 1. Click “All Scans of All Profiles” to select all the scans in one go

  9. Enter PIS/NLS Target Masses for Each Function Within a File 1. Click Load Scan

  10. Enter PIS/NLS Target Masses for Each Function Within a File

  11. Model Experiment Design for Targeted Lipid Identification 2. Analyze > Lipid Quantitation > Model Experiment Design 1. Select Lipid Quantitation Node

  12. Model Experiment Design for Targeted Lipid Identification 1. Select “Only Average Profiles” for experiment design 2. Click OK

  13. Model Experiment Design 1. Specify experiment name 2. Specify sample name 4. Select the corresponding Events/Functions 3. Select the samples 6. Click to transfer all the information into selected profiles table 5. Polarity and Target Mass and Scan Type information is read automatically from the file

  14. Model Experiment Design Information transferred to selected profiles table 2. Click OK 1. Click “Map Target Mass Database” option to map the target masses with SimLipid's target fragment database

  15. Target Mass Mapping – Review the Mapped Fragments 1. Select this view to show only the Events /files with unique target masses within a specified tolerance range 2. Select target mass

  16. Target Mass Mapping – Review the Mapped Fragments Search results obtained for Target Mass = 253.2168 Click OK Information selected for this target mass is applied to all other instances of this target mass available in the “Show All” view.

  17. Specify Peak Correction Parameters and Click “OK” to Perform Search 1. Select to enable Peak Correction 3. Click OK 2. Click Peak Correction Technique

  18. Specify Peak Correction Parameters and Click “OK” to Perform Search 1. Click OK to perform search

  19. Data Pre-processing

  20. Check Search Status and Load Results HTP search status- Pending

  21. Check Search Status and Load Results HTP search status- Completed

  22. Check Search Status and Load Results Load HTP Results

  23. Check Search Status and Load Results

  24. Result View of PIS/NLS_253.2168_Pos 0 Notice the hierarchy of experiment, sample and and replicates

  25. Result View at PISNLS_184.1_Pos Note that lipids from PC and SM classes are only reported

  26. Mark Internal Standard 1. Select a lipid to be marked as internal standard 2. Select Mark/Unmark/Edit Internal Standard button 4. Click Mark 3. Specify the amount of Internal Standard Please Note: Multiple internal standards can be marked for a lipid class

  27. Align Scans in a Sample Analyze > Lipid Quantitation > Align Scans in Sample Select the experiment name from the dropdown list Select the PIS/NLS/Full Scan nodes to be aligned for a sample

  28. Align Scans in a Sample

  29. Scans Aligned at Sample Level Note here lipid PC(44:0) identified in both scans with Target Mass = 283.3 (Neg mode) and Target Mass = 184.07 (Pos mode) gets aligned, you can SUM or Average the intensities from the aligned scans

  30. Align Samples in an Experiment Use shortcut button to align samples Analyze > Lipid Quantitation > Align Samples 1. Select the Experiment Name 2. Select the Samples to be aligned 3. Select the Alignment Options 4. Click OK

  31. Align Samples in an Experiment

  32. Generate Comp. x Conc. Report 2. Select the fragment type and lipid abundanceoption for generating Comp. X Conc. report 3. Select “Heat Map” to generate heatmap 1. Click on “Comp. X Conc. Report” button 4. Select file type 5. Click OK

  33. Generate Comp. x Conc. Report

  34. Generate Comp. x Conc. Report Output

  35. Lipids Aligned at Sample Level Lipids aligned from both the samples, Serum 10 and Serum 33

  36. Quantitation at Experiment Level 2. Select Total Abundance 1. Click Quantitation 3. Click OK

  37. Quantified Lipids at Experiment Level

More Related