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Label Free & Isobaric Quantitative Proteomics Training | LFQ, TMT/iTRAQ, Normalization & Batch Correction

NTHRYS >> Services >> Academic Services >> Training Programs >> Bioinformatics Training >> Proteomics, Structural Bioinformatics & Biophysical Modeling >> Label Free & Isobaric Quantitative Proteomics Training | LFQ, TMT/iTRAQ, Normalization & Batch Correction

Label Free & Isobaric Quantitative Proteomics — Hands-on

Design and execute robust quantitative proteomics studies using both label free and isobaric strategies. Learn how to plan channels and replicates, control inter batch variation, handle missingness, normalize and transform data, and apply sound statistics for differential protein abundance with publication ready outputs.

Label Free & Isobaric Quantitative Proteomics
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Session 1
Fee: Rs 12320
Quantitation Strategies & Study Design
  • Choosing label free vs isobaric designs
  • discovery vs targeted goals depth vs throughput budget and instrument time
  • Replicates, blocking and channel planning
  • biological vs technical replicates balanced groups pooled reference channels
  • Sources of variability in quantitation
  • sample prep and load LC MS drift batch and instrument effects
Session 2
Fee: Rs 16520
Label Free Quantitation Workflows
  • Intensity and spectral counting approaches
  • MS1 feature based LFQ spectral counts match between runs concepts
  • Feature detection and alignment
  • RT alignment peak integration handling shared peptides
  • Export formats and QC for LFQ data
  • protein groups tables CVs within groups missingness patterns
Session 3
Fee: Rs 20720
Isobaric (TMT/iTRAQ) Design & Analysis
  • TMT and iTRAQ chemistry and multiplexing
  • channel layout bridge channels reference designs
  • Ratio compression and interference handling
  • co isolation effects MS3 and SPS ideas filtering high interference PSMs
  • Reporter ion extraction and QC
  • reporter S/N missing channels channel balance checks
Session 4
Fee: Rs 26320
Normalization, Batch Correction & Statistics
  • Normalization strategies for protein intensities
  • global scaling median and quantile log transforms
  • Batch correction and missing value handling
  • combat like correction ideas missing not at random scenarios imputation strategies
  • Differential abundance and reporting
  • moderated t tests FDR controlled hit lists volcano plots and heatmaps


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