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Spatial normalization of reverse phase protein array data.

Kaushik P, Molinelli EJ, Miller ML, Wang W, Korkut A, Liu W, Ju Z, Lu Y, Mills G, Sander C - PLoS ONE (2014)

Bottom Line: This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide.Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case.It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis.

View Article: PubMed Central - PubMed

Affiliation: Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.

ABSTRACT
Reverse phase protein arrays (RPPA) are an efficient, high-throughput, cost-effective method for the quantification of specific proteins in complex biological samples. The quality of RPPA data may be affected by various sources of error. One of these, spatial variation, is caused by uneven exposure of different parts of an RPPA slide to the reagents used in protein detection. We present a method for the determination and correction of systematic spatial variation in RPPA slides using positive control spots printed on each slide. The method uses a simple bi-linear interpolation technique to obtain a surface representing the spatial variation occurring across the dimensions of a slide. This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide. The adoption of the method results in increased agreement between technical and biological replicates of various tumor and cell-line derived samples. Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case. The method is implemented in the R statistical programing language. It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis. The method is made available, along with suggestions for implementation, at http://bitbucket.org/rppa_preprocess/rppa_preprocess/src.

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Related in: MedlinePlus

In the experimental design we use for the analysis of the samples in sets A and B, lysate is spotted in 96 arrays consisting of 22 samples, two positive controls and one buffer spot each.Each of the samples and the positive controls is printed in five 1∶2 serial dilutions each.
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pone-0097213-g002: In the experimental design we use for the analysis of the samples in sets A and B, lysate is spotted in 96 arrays consisting of 22 samples, two positive controls and one buffer spot each.Each of the samples and the positive controls is printed in five 1∶2 serial dilutions each.

Mentions: Homogenized cell pellets consisting of cellular proteins are derived from cells grown in-vitro or from tissue samples in-vivo. Samples are lysed and the protein extract obtained is diluted based on the design of each experiment. In the slides comprising the data sets in this study, each sample undergoes a ½ serial dilution four times, leading to a total of 5 concentrations per sample. These initial serial dilutions are performed manually. Diluted samples are then robotically spotted onto the surface of slides coated with nitrocellulose. In our experimental design, each sample and positive control is printed in five dilutions. The slides are laid out as grids of 132×44 spots, comprised of 48 subgrids containing 121 spots each. Thus, each subgrid accommodates 22 samples and 2 positive control samples, in 5 dilutions each. A subgrid is also printed with a single buffer spot that serves as a negative or background control. Each slide thus accommodates 1056 serially diluted samples and 96 positive control samples (with 5 dilutions per sample), and an additional 48 negative control spots (Fig. 2). The positive control spots, are printed at fixed intervals across the length and breadth of each slide, and are technical replicates of each other, obtained from a single batch of standard mixed cell lysate [18]. Since the controls are designed to contain sufficient amount of each of the proteins in the antibody panel for reliable detection, similar levels of the concerned protein should also be detected in experimental samples when the appropriate dilution of antibody is used. The negative control spots consist of buffer containing no protein and are hence informative of the level of background signal generated.


Spatial normalization of reverse phase protein array data.

Kaushik P, Molinelli EJ, Miller ML, Wang W, Korkut A, Liu W, Ju Z, Lu Y, Mills G, Sander C - PLoS ONE (2014)

In the experimental design we use for the analysis of the samples in sets A and B, lysate is spotted in 96 arrays consisting of 22 samples, two positive controls and one buffer spot each.Each of the samples and the positive controls is printed in five 1∶2 serial dilutions each.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4264691&req=5

pone-0097213-g002: In the experimental design we use for the analysis of the samples in sets A and B, lysate is spotted in 96 arrays consisting of 22 samples, two positive controls and one buffer spot each.Each of the samples and the positive controls is printed in five 1∶2 serial dilutions each.
Mentions: Homogenized cell pellets consisting of cellular proteins are derived from cells grown in-vitro or from tissue samples in-vivo. Samples are lysed and the protein extract obtained is diluted based on the design of each experiment. In the slides comprising the data sets in this study, each sample undergoes a ½ serial dilution four times, leading to a total of 5 concentrations per sample. These initial serial dilutions are performed manually. Diluted samples are then robotically spotted onto the surface of slides coated with nitrocellulose. In our experimental design, each sample and positive control is printed in five dilutions. The slides are laid out as grids of 132×44 spots, comprised of 48 subgrids containing 121 spots each. Thus, each subgrid accommodates 22 samples and 2 positive control samples, in 5 dilutions each. A subgrid is also printed with a single buffer spot that serves as a negative or background control. Each slide thus accommodates 1056 serially diluted samples and 96 positive control samples (with 5 dilutions per sample), and an additional 48 negative control spots (Fig. 2). The positive control spots, are printed at fixed intervals across the length and breadth of each slide, and are technical replicates of each other, obtained from a single batch of standard mixed cell lysate [18]. Since the controls are designed to contain sufficient amount of each of the proteins in the antibody panel for reliable detection, similar levels of the concerned protein should also be detected in experimental samples when the appropriate dilution of antibody is used. The negative control spots consist of buffer containing no protein and are hence informative of the level of background signal generated.

Bottom Line: This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide.Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case.It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis.

View Article: PubMed Central - PubMed

Affiliation: Computational Biology Center, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.

ABSTRACT
Reverse phase protein arrays (RPPA) are an efficient, high-throughput, cost-effective method for the quantification of specific proteins in complex biological samples. The quality of RPPA data may be affected by various sources of error. One of these, spatial variation, is caused by uneven exposure of different parts of an RPPA slide to the reagents used in protein detection. We present a method for the determination and correction of systematic spatial variation in RPPA slides using positive control spots printed on each slide. The method uses a simple bi-linear interpolation technique to obtain a surface representing the spatial variation occurring across the dimensions of a slide. This surface is used to calculate correction factors that can normalize the relative protein concentrations of the samples on each slide. The adoption of the method results in increased agreement between technical and biological replicates of various tumor and cell-line derived samples. Further, in data from a study of the melanoma cell-line SKMEL-133, several slides that had previously been rejected because they had a coefficient of variation (CV) greater than 15%, are rescued by reduction of CV below this threshold in each case. The method is implemented in the R statistical programing language. It is compatible with MicroVigene and SuperCurve, packages commonly used in RPPA data analysis. The method is made available, along with suggestions for implementation, at http://bitbucket.org/rppa_preprocess/rppa_preprocess/src.

Show MeSH
Related in: MedlinePlus