Description Usage Arguments Details Value Examples
View source: R/normalization.R
Normalizes each replicate of an experiment based on linear regression of calculated Tm (corrects for remaining systematic error).
1 | normalize_to_tm(expt, res)
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expt |
An MSThermExperiment object |
res |
An MSThermResultSet object |
An assumption can be made in most TPP experiments using a single organism that the Tm of most proteins should not be changing. However, global shifts have been observed between replicates, presumably due to technical variance, which complicate data interpretation. This method attempts to remove this source of error by doing a bootstrap renormalization of the quantification values based on pairwise linear regression between calculated Tms of each replicate. A reference set of Tms is calculated based on all replicates, and each replicate is normalized to this based on the calculated slope and intercept of the input data.
An MsThermExperiment object with re-normalized data slots
1 2 3 4 5 6 7 | control <- system.file("extdata", "demo_project/control.tsv", package="mstherm")
annots <- system.file("extdata", "demo_project/annots.tsv", package="mstherm")
expt <- MSThermExperiment(control, annotations=annots)
expt <- normalize_to_std(expt, "cRAP_ALBU_BOVIN", plot=FALSE)
res <- model_experiment(expt, smooth=TRUE, bootstrap=FALSE, np=2)
expt <- normalize_to_tm(expt, res)
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