DDARawData
(Package: MSstats) :
Example dataset from a label-free DDA, a controlled spike-in experiment.
This is a data set obtained from a published study (Mueller, et. al, 2007). A controlled spike-in experiment, where 6 proteins, (horse myoglobin, bovine carbonic anhydrase, horse Cytochrome C, chicken lysozyme, yeast alcohol dehydrogenase, rabbit aldolase A) were spiked into a complex background in known concentrations in a latin square design. The experiment contained 6 mixtures, and each mixture was analyzed in label-free LC-MS mode with 3 technical replicates (resulting in the total of 18 runs). Each protein was represented by 7-21 peptides, and each peptide was represented by 1-5 transition.
DDARawData.Skyline
(Package: MSstats) :
Example dataset from a label-free DDA, a controlled spike-in experiment, processed by Skyline.
This is a data set obtained from a published study (Mueller, et. al, 2007). A controlled spike-in experiment, where 6 proteins, (horse myoglobin, bovine carbonic anhydrase, horse Cytochrome C, chicken lysozyme, yeast alcohol dehydrogenase, rabbit aldolase A) were spiked into a complex background in known concentrations in a latin square design. The experiment contained 6 mixtures, and each mixture was analyzed in label-free LC-MS mode with 3 technical replicates (resulting in the total of 18 runs). Each protein was represented by 7-21 peptides, and each peptide was represented by 1-5 transition. Skyline is used for processing.
DIARawData
(Package: MSstats) :
Example dataset from a label-free DIA, a group comparison study of S.Pyogenes.
This example dataset was obtained from a group comparison study of S. Pyogenes. Two conditions, S. Pyogenes with 0% and 10% of human plasma added (denoted Strep 0% and Strep 10%), were profiled in two replicates, in the label-free mode, with a SWATH-MS-enabled AB SCIEX TripleTOF 5600 System. The identification and quantification of spectral peaks was assisted by a spectral library, and was performed using OpenSWATH software (http: //proteomics.ethz.ch/openswath.html). For reasons of space, the example dataset only contains two proteins from this study. Protein FabG shows strong evidence of differential abundance, while protein Probable RNA helicase exp9 only shows moderate evidence of dif- ferential abundance between conditions.
MSstats-package
(Package: MSstats) :
Tools for protein significance analysis in DDA,SRM and DIA proteomic experiments for label-free workflows or workflows with stable isotope labeled reference
A set of tools for protein significance analysis in SRM, DDA and DIA experiments.
SRMRawData
(Package: MSstats) :
Example dataset from a SRM experiment with stable isotope labeled reference of a time course yeast study
This is a partial data set obtained from a published study (Picotti, et. al, 2009). The experiment targeted 45 proteins in the glycolysis/gluconeogenesis/TCA cycle/glyoxylate cycle network, which spans the range of protein abundance from less than 128 to 10E6 copies per cell. Three biological replicates were analyzed at ten time points (T1-T10), while yeasts transited through exponential growth in a glucose-rich medium (T1-T4), diauxic shift (T5-T6), post-diauxic phase (T7-T9), and stationary phase (T10). Prior to trypsinization, the samples were mixed with an equal amount of proteins from the same N15-labeled yeast sample, which was used as a reference. Each sample was profiled in a single mass spectrometry run, where each protein was represented by up to two peptides and each peptide by up to three transitions. The goal of this study is to detect significantly change in protein abundance across time points. Transcriptional activity under the same experimental conditions has been previously investigated by (DeRisi et. al., 1997). Genes coding for 29 of the proteins are differentially expressed between conditions similar to those represented by T7 and T1 and could be treated as external sources to validate the proteomics analysis. In this exampled data set, two of the targeted proteins are selected and validated with gene expression study: Protein IDHC (gene name IDP2) is differentially expressed in time point 1 and time point 7, whereas, Protein PMG2 (gene name GPM2) is not. The protein names are based on Swiss Prot Name.
SpikeInDataLinear
(Package: MSstats) :
Example dataset from an MRM spike-in experiment with a linear behavior
This dataset is part of the CPTAC 7, study 3 (Addona et al., 2009). It corresponds to the spike-in data for peptide AGLCQTFVYGGCR at site 86. This particular data was chosen because it illustrates well a linear response for a spiked in experiment. The data is composed of 4 replicates at 10 different concentrations (including a blank sample with concentration 0).
SpikeInDataNonLinear
(Package: MSstats) :
Example dataset from an MRM spike-in experiment with a nonlinear behavior
This dataset is part of the CPTAC 7, study 3 (Addona et al., 2009). It corresponds to the spike-in data for peptide ESDTSYVSLK at site 19. This particular data was chosen because of the concentration threshold that is present at low concentrations that warrant the use of a nonlinear method. The data is composed of 4 replicates at 10 different concentrations (including a blank sample with concentration 0).
dataProcess
(Package: MSstats) :
Data pre-processing and quality control of MS runs of raw data
Data pre-processing and quality control of MS runs of the original raw data into quantitative data for model fitting and group comparison. Log transformation is automatically applied and additional variables are created in columns for model fitting and group comparison process. Three options of data pre-processing and quality control of MS runs in dataProcess are (1) Transformation: logarithm transformation with base 2 or 10; (2) Normalization: to remove systematic bias between MS runs.
To illustrate the quantitative data after data-preprocessing and quality control of MS runs, dataProcessPlots takes the quantitative data from function (dataProcess) as input and automatically generate three types of figures in pdf files as output : (1) profile plot (specify "ProfilePlot" in option type), to identify the potential sources of variation for each protein; (2) quality control plot (specify "QCPlot" in option type), to evaluate the systematic bias between MS runs; (3) mean plot for conditions (specify "ConditionPlot" in option type), to illustrate mean and variability of each condition per protein.
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