Althy volunteer samples were matched according to gender and age, and

Althy volunteer samples were matched according to gender and age, and labeled with either Cy3 or Cy5. Also, an internal standard, labeled with Cy2, was used for normalization. The experimental setup can be found in Table 2. After electrophoresis and scanning of the gels, the gel images were loaded in DeCyder 2D 7.0 software and an extensive matching, re-matching and landmarking was conducted. In total, up to 2513 spots were detected on the gels. Although all protein spots from a 2D-DIGE experiment can be of interest, we chose to work with spots present in at least 11 out of 12 gels, as these spots are able to give a Epigenetics better estimation (moreStatistical analysisIn the BVA module of the Decyder 2D 7.0 software, the standard abundance (SA) for each spot was reported as the ratio of the spotvolume of Cy3 (or Cy5) to the volume of the Cy2 standard. Standardized log abundance (SLA) values were used to quantify the differential expression. Only protein spots appearing in at least 11 out of 12 gels were used for statistical Epigenetic Reader Domain analysis. After exporting the raw data of the proteins of interest, further statistical processing of the spot characteristics was performed in Excel and R. Spotwise standard deviations (SD), arithmetic mean (m) and coefficient of variation (CV) values of the SA values were calculated for eachVariation in PBMC ProteomeTable 2. Experimental setup of total variation experiment: The samples on one gel are matched according to age and gender.Cy3 Gel 1 Gel 2 Gel 3 Gel 4 Gel 5 Gel 6 HV 1 HV 2 HV 3 HV 12 HV 7 HVCy5 HV 21 HV 15 HV 13 HV 5 HV 11 HVCy2 pool pool pool pool pool pool Gel 7 Gel 8 Gel 9 Gel 10 Gel 11 GelCy3 HV 22 HV 10 HV 6 HV 14 HV 19 HVCy5 HV 20 HV 18 HV 24 HV 23 HV 8 HVCy2 pool pool pool pool pool poolHV = healthy volunteer. doi:10.1371/journal.pone.0061933.tsamples, more volume ratios, better statistical relevance) of the variance in this experiment. Furthermore, we assume that the biological and technical concepts discussed, can be extended to all spots on the gel. The highly reproducible protein spots used for the estimation of total variation are shown in Figure 1. After extraction of the raw data, we calculated the CV of 382 spots using the Vnormg values. These normalized values represent the standard log abundance (SLA) values, which gives the ratio of Cy3/Cy2 or Cy5/Cy2. As shown in Figure 1C, the Gaussian distribution of the SLA values confirms regular data. After making a pair wise comparison of the spots in the DeCyder software usingt-test statistics combined with FDR correction, none of the spots turned out to be a false positive differential protein. To have an idea about the spotwise variation of the selected proteins in this cell fraction, the coefficient of variation for every spot was calculated, using the standard abundance values. The CV of these spots ranged from 12,99 to 148,45 , with a mean value of 28 , as can be seen in Figure 2. Consequently, the interindividual variation in these mononuclear blood cells varies about 28 . Up to 75 of the spots do not exceed the CV value of 40 , which shows that most of the protein abundances are quite stable in 24 healthy individuals. Proteins exceeding the threshold of CV = 50 , are highly variable proteins, and cannot be used in differential biomarker discovery procedures, because their interindividual variation limits the detection of true biologically significant differences. Only 13 of all the protein spots used, turned out to be highly variable proteins.Althy volunteer samples were matched according to gender and age, and labeled with either Cy3 or Cy5. Also, an internal standard, labeled with Cy2, was used for normalization. The experimental setup can be found in Table 2. After electrophoresis and scanning of the gels, the gel images were loaded in DeCyder 2D 7.0 software and an extensive matching, re-matching and landmarking was conducted. In total, up to 2513 spots were detected on the gels. Although all protein spots from a 2D-DIGE experiment can be of interest, we chose to work with spots present in at least 11 out of 12 gels, as these spots are able to give a better estimation (moreStatistical analysisIn the BVA module of the Decyder 2D 7.0 software, the standard abundance (SA) for each spot was reported as the ratio of the spotvolume of Cy3 (or Cy5) to the volume of the Cy2 standard. Standardized log abundance (SLA) values were used to quantify the differential expression. Only protein spots appearing in at least 11 out of 12 gels were used for statistical analysis. After exporting the raw data of the proteins of interest, further statistical processing of the spot characteristics was performed in Excel and R. Spotwise standard deviations (SD), arithmetic mean (m) and coefficient of variation (CV) values of the SA values were calculated for eachVariation in PBMC ProteomeTable 2. Experimental setup of total variation experiment: The samples on one gel are matched according to age and gender.Cy3 Gel 1 Gel 2 Gel 3 Gel 4 Gel 5 Gel 6 HV 1 HV 2 HV 3 HV 12 HV 7 HVCy5 HV 21 HV 15 HV 13 HV 5 HV 11 HVCy2 pool pool pool pool pool pool Gel 7 Gel 8 Gel 9 Gel 10 Gel 11 GelCy3 HV 22 HV 10 HV 6 HV 14 HV 19 HVCy5 HV 20 HV 18 HV 24 HV 23 HV 8 HVCy2 pool pool pool pool pool poolHV = healthy volunteer. doi:10.1371/journal.pone.0061933.tsamples, more volume ratios, better statistical relevance) of the variance in this experiment. Furthermore, we assume that the biological and technical concepts discussed, can be extended to all spots on the gel. The highly reproducible protein spots used for the estimation of total variation are shown in Figure 1. After extraction of the raw data, we calculated the CV of 382 spots using the Vnormg values. These normalized values represent the standard log abundance (SLA) values, which gives the ratio of Cy3/Cy2 or Cy5/Cy2. As shown in Figure 1C, the Gaussian distribution of the SLA values confirms regular data. After making a pair wise comparison of the spots in the DeCyder software usingt-test statistics combined with FDR correction, none of the spots turned out to be a false positive differential protein. To have an idea about the spotwise variation of the selected proteins in this cell fraction, the coefficient of variation for every spot was calculated, using the standard abundance values. The CV of these spots ranged from 12,99 to 148,45 , with a mean value of 28 , as can be seen in Figure 2. Consequently, the interindividual variation in these mononuclear blood cells varies about 28 . Up to 75 of the spots do not exceed the CV value of 40 , which shows that most of the protein abundances are quite stable in 24 healthy individuals. Proteins exceeding the threshold of CV = 50 , are highly variable proteins, and cannot be used in differential biomarker discovery procedures, because their interindividual variation limits the detection of true biologically significant differences. Only 13 of all the protein spots used, turned out to be highly variable proteins.

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