"Analysis Of Dda Data Works I Want To Briefly Give You A Sense Of Generally How You'Ll Analyze Your D Da Data Although If You'Re Staying For The MexicoíS On Summer School Later In The Week You'Ll Get This In A Lot More Detail The First Step In Identifying Your Peptides Or The First Step In The Analysis Is To Identify Your Peptides From Your Ms/Ms Spectra And This Is A Process Called Peptide Spectral Matching And There'S Really Three Ways That People Do This The First Way Is A Database Search And This Is Where You Compare Your Experimental Spectra To All Theoretical Spectra Predicted From A Database Of Possible Peptides Based On The Genomic Sequence So A Database Search Requires That You'Ve Also Have Some Genomic Reference Sequence For That Organism The Second Way Is Called A Spectral Library Search And This Is Where You Compare Your Experimental Vectra To A Library Of All Spectra That You'Ve Identified Previously Probably From Another Database Search And The Last Method Is De Novo And This Is Where You Look At The Fragment Spectra And Try To Piece Together What The Amino Acid Sequence Should Be And After Each Of These Different Options I'Ve Listed A Few Different Software Tools That Perform Each Of These Types Of Analysis Now For Any Of These Peptide Identification Methods We Need A Way To Assign Statistics That We'Ve Assigned The Right Peptide To Our Spectra And We Do This With Something Called The Target Decoy Approach And That Means That You Search For Real Peptides That You Expect Should Be In Your Sample But You Also Search For Shuffled Or Reversed Fake Peptide Sequences Which Should Not Be There And Those Are Your Decoys This Allows You To Determine How Often Your Search Finds The Wrong Answers Which Is Called Your False Discovery Rate Or Fdr And The Way This Works Is You Determine Distributions Of Your Target Decode Or Your Target Hits In Green And Your Decoy Hits In Red And That Allows You To Set A Score Threshold Above Which You'Ll Accept Any Peptide Id At A Known Proportion Of Decoy Hits Often We Use 1% Fdr After You'Ve Identified Your Peptides And Assign Statistics To Those Identifications You Probably Need To Infer Proteins So Although In Bottom-Up Proteomics Were Actually Looking At Peptides We Need Statistically Rigorous Ways To Determine What Proteins We Found And It'S Important To Note That You Must Compute Your Protein And Peptide Fdr Separately So A 1% Peptide Fdr Will Almost Always Correspond To A Higher Protein Fdr And There'S Many Different Programs That Will Do This For You A Couple Examples Are Protein Profit And Mayu And There'S Actually Many Different Tools Well The Final Step Is To Quantify Your Peptides And Proteins And I'Ll Talk About That More On The Next Slide But I Want To Make The Point That There'S Many Different Tools That We'Ll Do Each Of These Steps That Are Developed Academically Or Commercially One Really Great Tool Is Max Font Because It Will Do All Of These Steps For You It Puts Everything Together But I'Ve Also Given You A Citation For An Example Of A Different Route That I Published Earlier This Year"

0.0(0)
studied byStudied by 0 people
learnLearn
examPractice Test
spaced repetitionSpaced Repetition
heart puzzleMatch
flashcardsFlashcards
Card Sorting

1/14

encourage image

There's no tags or description

Looks like no tags are added yet.

Study Analytics
Name
Mastery
Learn
Test
Matching
Spaced

No study sessions yet.

15 Terms

1
New cards

Hybrid Mass Spectrometers

Instruments that contain multiple mass spectrometry units for proteomics and metabolomics.

2
New cards

Precursor Ion Scan

A method where the first quadrupole (Q1) selects a wide mass range of ions for detection without fragmentation.

3
New cards

Fragment Ion Scan

Also known as tandem MS/MS or MS2, where Q1 selects a subset of masses and Q2 induces fragmentation before detection.

4
New cards

Data Dependent Acquisition (DDA)

A method where the MS scan sequence depends on the data collected, leading to variability in scans across runs.

5
New cards

Data Independent Acquisition (DIA)

A method where the scan sequence is independent of the data, resulting in consistent scans across analyses.

6
New cards

Targeted Methods

Approaches used for hypothesis testing, focusing on specific proteins or peptides of interest.

7
New cards

Untargeted Methods

Approaches used for hypothesis generation, allowing for the discovery of unknown proteins or changes in biological conditions.

8
New cards

Targeted DDA

A method that uses an inclusion list to monitor specific peptides during data collection.

9
New cards

Untargeted DDA

A method that collects data based on the most abundant precursor ions detected at any moment, also known as the top strategy.

10
New cards

Selected Reaction Monitoring (SRM)

A targeted DIA method performed on a triple quadrupole mass spectrometer.

11
New cards

Parallel Reaction Monitoring (PRM)

A targeted DIA method performed on high-resolution instruments like Orbitrap or Q-Exactive.

12
New cards

SWATH

An untargeted DIA method that selects and fragments larger predefined mass ranges throughout the elution gradient.

13
New cards

Precursor MS Spectra

The initial mass spectra produced by allowing all peptides through Q1 unfragmented.

14
New cards

Fragment Ion Spectra

The mass spectra produced from the fragments of selected precursor ions after fragmentation in Q2.

15
New cards

Stochasticity of DDA

The variability in protein identification across repeated analyses of the same sample, leading to diminishing returns in unique identifications.