# Presentation: 323105

##  Novel Algorithms for the Quantification Confidence in Quantitative Proteomics with Stable Isotope Labeling*

**Chongle Pan**1,2; David L. Tabb1; Dale Pelletier1; W. Hayes McDonald1; Greg Hurst1; Nagiza F. Samatova1; Robert L. Hettich1;
**1**Oak Ridge National Laboratory, Oak Ridge, TN
**2** Genome Science and Technology, UT-ORNL
*** Research support provided by the U.S. Department of Energy, Office of Biological and Environmental Research.  **

## Uncertainty in the Measurements

**Mass spectrometric measurement of a protein**
**Mr = 23,564 Da**

**±10 Da  95% confidence**

**Relative quantification of a protein in quantitative proteomics**
**Abundance ratio = 1:1**
- 95% confidence interval = [2:1, 1:2]

**The principal aim**

## Experimental

**Metabolic labeling of***** Rhodopseudomonas palustris *****with***** *****the***** *****stable isotope ****15****N  **
**Standard mixtures of natural and ****15****N-labeled proteomes at the pre-determined mixing ratios **
**Shotgun proteomics analysis**
**MS instrument:**** linear ion trap  **(LTQ, Finnigan)
**2D-LC method:**** 24-hour MudPIT technique**5
**Protein identification**
**Database searching:**** DBDigger**6
**Identification filtering:**** DTASelect**7

- 5 Int. J. of Mass Spec. 2002. 219: p. 245-251.
- 6 Anal Chem, 2003. **75**: p. 6912-21
- 7 J. Proteome Res. 2002 1: p. 21-26.

## Benchmark Data

**Peptide I.D. filtering: 95% of true positive rate **
**Protein I.D. filtering: minimum of 2 peptides**

**Data quality**
**Reproducibility**

## Block Diagram

**SIC reconstruction**

**peak detection**

**peptide quantification**

**protein quantification**

- maximum likelihood estimation

- principal component analysis

- parallel paired covariance

**Block Diagram**

- selected ion chromatogram

- mass spectral data

- chromatographic peak

- peptide abundance ratio
- confidence score

- protein abundance ratio
- confidence interval

## Peak Detection

- covariance

- scan number

- scan number

- ion intensity

**Light isotopologue SIC****; **
**Heavy isotopologue**** ****SIC**

**S/N=3****; **
**S/N=13**

**S/N=42**

**Parallel paired covariance chromatogram (PPC)**

**Peak boundaries are defined as the local minima in the PPC, which include all MS/MS matching the peptide**

**Peak boundaries**

## Peptide Quantification

**Peptide abundance ratios can be estimated by**
**Peak height ratio**

- scan number

- ion intensity

- ion intensity

- scan number

## Peptide Quantification

- heavy isotopologue ion intensity

- light isotopologue ion intensity

**Peptide Quantification**

- ion intensity

- scan number

## Quantification Accuracy

**Quantification Accuracy**

**Peptide counts**

**log****2****(ratio)**

- Expected log2(ratio)

- Peak height ratio
- Peak area ratio
- PCA/linear regression

- 1:5

## Quantification Accuracy

- 5:1

- 10:1

- 1:10

- 1:1

**log****2****(ratio)**

**Peptide counts**

**Peptide counts**

**log****2****(ratio)**

**log****2****(ratio)**

**Quantification Accuracy**

- 1:1

- 5:1

- 1:5

- 1:10

- 10:1

## Quantification Confidence

**log****2****(ratio)**

**log****2****(PCA-SNR)**

**peptide counts**

- 5:1

**2D histogram of**
**peptide log****2****(ratio) & log****2****(PCA-SNR)**

## Quantification Confidence

**Quantification Confidence**

**log****2****(ratio)**

**log****2****(PCA-SNR)**

- 5:1

**Bin the peptides by their log****2****(PCA-SNR) value**
**Bias: the deviation of the average estimated log****2****(ratio)**
**from the expected log****2****(ratio)**
**Bias increases as**
**PCA-SNR decreases below a threshold**

## Quantification Confidence

**Quantification Confidence**

**log****2****(ratio)**

**log****2****(PCA-SNR)**

- 5:1

**Bin the peptides by their log****2****(PCA-SNR) value**
**Variance: the variability of the estimated log****2****(ratio) **
**Variance increases as**
**PCA-SNR decreases**

## Quantification Confidence

- 1:5

- log2(ratio)

- log2(S/N)

- Comet-like two-dimensional distribution
- As log2(SNR) decreases,
- the spread of log2(ratio) estimates increases
- the average of log2(ratio) estimates regresses to zero

**log****2****(ratio)**

**log****2****(PCA-SNR)**

**log****2****(ratio)**

**log****2****(ratio)**

**log****2****(PCA-SNR)**

- 1:1

- 1:10

- 10:1

- 1:1

- 5:1

## Quantification Confidence

**log****2****(PCA-SNR)**

**| mean { log****2****(ratio) } |**

- 5:1&1:5

- 10:1&1:10

- 1:1

**log****2****(PCA-SNR)**

**standard deviation **
**{ log****2****(ratio) }**

- 1:1
- 5:1&1:5
- 10:1&1:10

**The quantification bias and variance for peptides are linear functions of PCA-SNR  **

## Protein Quantification

**Protein Quantification**

**log****2****(ratio)**

**log****2****(PCA-SNR)**

- mean

**Maximum likelihood point estimate of a protein’s abundance ratio is the ratio that best explains its measured peptides’ estimated log****2****(ratio) at the calculated log****2****(PCA-SNR)**

- 2 sd

- measured
- peptides

**A series of theoretical probability distributions of peptide abundance ratio estimates at each PCA-SNR level**

## Quantification Accuracy

**Quantification Accuracy**

**RelEx filtering:**
**> 0.7 correlation at 1**
**> 0.4 correlation at 10**
**> 3 signal-to-noise**
**> 2 peptides**

**log****2****(ratio)**

**protein counts**

**MSE: Mean Square Error**

**PRATIO filtering:**
**> 2 PCA-SNR**
**> 2 peptides**
**< 4 95% confidence interval width for log****2****(ratio) **

## Quantification Accuracy

- 5:1

- 1:10

- RelEx: red; PRATIO: blue

**Quantification Accuracy**

- log2(ratio)

- log2(ratio)

- log2(ratio)

- 1:1

- 1:1

- 5:1

- 1:5

- 1:10

- 10:1

- protein counts

- protein counts

## Confidence Interval Estimation

**log****2****(ratio)**

**1:5**

**Display of the point estimates (****+****) and the 95% confidence interval estimates ( ****-----------**** ) for protein abundance ratios**** **

**Protein **

## Confidence Interval Estimation

- Point estimates and confidence interval estimates of protein abundance ratios

**log****2****(ratio)**

**log****2****(ratio)**

**log****2****(ratio)**

**1:1**

**1:5**

**5:1**

**10:1**

**1:1**

**1:10**

## Conclusions

- Three novel algorithms
- Parallel paired covariance for peak detection
- Principal component analysis for peptide quantification
- Maximum likelihood estimation for protein quantification
**Improved Protein Quantification Accuracy**
**Rigorous Confidence Interval Estimation**

**The fully automated program with graphic user interface is freely available for testing by contacting C. Pan (email: panc@ornl.gov)**