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Table 5 Quantification results of the sample 1:3 mix.

From: Precise protein quantification based on peptide quantification using iTRAQ™

Protein Id

Protein name

Quant

EE

Pro Quant™

Bias

        

2,9929

   

2,8491

  

Ratio

n

IQR

RMS

LSE

μ

σ

Ratio

n

pVal

EF

P00722

Beta-galactosidase BGAL_ECOLI

1.0072

100

0.1606

0.0287

1.0550

0.0323

0.1952

0.9862

100

0.3045

1.0268

P00698

Lysozyme C precursor LYSC_CHICK

1.0545

47

0.1971

0.0202

1.0891

0.0757

0.1392

1.0088

47

0.6644

1.0410

P02787

Serotransferrin precursor TRFE_HUMAN

1.0005

124

0.1832

0.0213

1.0363

0.0144

0.1973

1.0261

124

0.0536

1.0264

P02769

Serum albumin precursor ALBU_BOVIN

1.0305

64

0.1975

0.0331

1.0929

0.0624

0.2183

1.0329

64

0.0099

1.0245

P00711

Alpha-lactalbumin precursor LALBA_BOVIN

0.9618

8

0.1667

0.0083

0.9546

-0.0511

0.1022

1.0194

8

0.5019

1.0601

P02754

Beta-lactoglobulin precursor (LACB_BOVIN)

1.0366

54

0.1569

0.0099

1.0436

0.0331

0.1388

0.9839

54

0.4429

1.0434

  1. The quantification results of the sample 1:3 mix are shown that include all peptides of each identified protein. Listed are the Protein Id, the protein name, the protein ratio (ratio) with the experiment error (EE) and the bias estimate of Quant and ProQuant™, respectively. The number of MS/MS spectra is listed in column n. Furthermore, several quality factors calculated by Quant are shown: the least squares estimator (LSE), interquartile range (IQR), root-mean-square value (RMS), mean value (μ) and standard deviation (σ). μ and σ were calculated from the log-transformed data. The results of ProQuant™ are taken from the ProGroup™ output that yields a p-value (pVal) and an error factor (EF) as described previously [35]. The experiment error of Quant (bias of ProQuant™) indicates the overall protein mixing ratio. The protein ratio results are normalized by this factor.