Sir,
For some personal reasons I can't share Skyline document, zip folder or screenshots with you.
So I am sending herewith the complete workflow I have followed, hope it will help you to trace anything missed by me.
Thank you and regards.
Part 1. Making Spectral library from DDA raw data
Skyline → blank document → Save .sky (Skyline documents)
File → Import → peptide search → Spectral library → Build → Cut off 0.95 → DDA → DDA workflow → raw files → Next → Modifications Carbamidomethyl (C) fixed; Oxidation (M) variable → Next → Precursor charges (2-7) → Count 3 peaks → Centroided → Mass accuracy 20 PPM → Include all matching scans
Part 2. Making Spectral library from DIA raw data
Skyline → blank document → Save .sky (Skyline documents)
File → Import → peptide search → Spectral library → Build → Cut off 0.95 → DIA → DIA workflow → raw files → Next
Configure transition settings
Precursor 2-7, Ion charges 1-6, Ion types y,b,p
Product ions fom ion 1 to last ion
m/z 350 - 2000
Include DIA precursor window for exclusion
Ion match tolerance 0.05 m/z
Pick 6 product ions - 3 min. product ions
Configure Full scan Settings
MS 1 filtering
Isotope Peaks included count centroided
Peak 3
Mass accuracy
At MS level 20 ppm
At MS/MS level 20 ppm
RT Filtering
Use only scans with in 5 minute of MS/MS IDS
Isolation scheme
Prespecified Isolation windows
Select any .raw file
Deconvolution None
Name to isolation Scheme
Import FASTA
missed cleavages #2
Decoy generation Reverse sequence
Decoys per target 1
Instrument Q extractive
MS Amanda
MS1 - MS2 - tolerances 0.05 Da
Fragment ions b,y → .blib file
Part 3. To do screening of spectral library file against experimental raw data files
Peptide settings
Digestion tab → Enzyme (Trypsin semi or only Trypsin), # 2 missed cleavages, Background proteome Human Fasta
Prediction
Filter
Library Build → Add .blib respective file, Pick peptides matching, Library and filter, peak peptides by picked intensity
Modifications
Quantifications → Regression Linear, Normalization Equalize medians, Regression weighing, 1/x, MS level 2
Transition settings
Prediction
Filter → Precursor 2-7, Ions 1-6, From ion 3 to last ion
Libray → 0.05 m/z ion match tolerance, 6 product ions and 3 minimum product ions
Instrument
Full scan → Count, Centroided 3 peaks, MS1 20 PPM, MS/MS 20 PPM Include all matching scans
Ion mobility
Settings → Integrate all → view → Spectral libraries → select → add all → matching peptides to current document settings → filter peptides → add all
Refine → add decoys → reverse sequence → save skyline document
Import → results → many files →
Refine → reintegrate → peak scoring model → 2 peptides per protein → 3 minimum transitions per precursor
Add → mprophet → train model
Refine → advanced → 3 minimum peptides per protein, 3 minimum transitions per precursor
Part 4. Exporting result files
Export → report → peptide ratio results → detection Q value less than 0.01
column headings → peptide, protein, replicate, precursor m/z, precursor charge, product m/z, product charge, fragment ion, retention time, area, background and peak rank |