2008
DOI: 10.1186/1471-2105-9-316
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PatternLab for proteomics: a tool for differential shotgun proteomics

Abstract: Background: A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu et al. demonstrated a method to perform semirelative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Mo… Show more

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Cited by 133 publications
(130 citation statements)
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“…Statistical comparison between nanoLC-MS/MS detected proteins in different conditions was carried out with the PatternLab program (42). Data were normalized by the total number of spectral counts per replicate and analyzed using the ACFold method with a p value below 0.01 and a minimum fold of 2.…”
Section: Bacteria Andmentioning
confidence: 99%
“…Statistical comparison between nanoLC-MS/MS detected proteins in different conditions was carried out with the PatternLab program (42). Data were normalized by the total number of spectral counts per replicate and analyzed using the ACFold method with a p value below 0.01 and a minimum fold of 2.…”
Section: Bacteria Andmentioning
confidence: 99%
“…Significant variations were assessed using Patternlab software (37), as previously described (12). Supplemental Table S3 reports log 2 (fold change) and p values obtained with the T-fold statistical method adapted for high throughput hypothesis tests (37). A BH-FDR statistical test was calculated to evaluate the global false discovery rate for each comparison.…”
Section: Nanolc-ms/ms Analysis-nanolc-ms/msmentioning
confidence: 99%
“…Proteins identified by at least two fully tryptic unique peptides, each with a false positive rate of less than 5%, were considered to be present in the sample. Differential protein expression analysis was performed using the ACfold algorithm as implemented in the PatternLab software suite (37). Spectral counts were normalized using the Row Sigma method of PatternLab (37).…”
Section: Preparation Of Membrane Fractions and Purification Of Biotinmentioning
confidence: 99%
“…Differential protein expression analysis was performed using the ACfold algorithm as implemented in the PatternLab software suite (37). Spectral counts were normalized using the Row Sigma method of PatternLab (37). Proteins were considered differentially expressed if they met the following criteria: 1) a -fold change cutoff of 2.5, 2) an estimated -fold change false discovery rate of less than 0.1, and 3) an ACtest p value of less than 0.01.…”
Section: Preparation Of Membrane Fractions and Purification Of Biotinmentioning
confidence: 99%
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