getMappedRT: Get mapping of reference RT on experiment run.
In Roestlab/DIAlign: Dynamic Programming Based Alignment of MS2 Chromatograms

Description Usage Arguments Value Author(s) See Also Examples

This function aligns XICs of reference and experiment runs. Using alignment, it maps retention time from refernce run on experiment run.

getMappedRT(
  refRT,
  XICs.ref,
  XICs.eXp,
  globalFit,
  alignType,
  adaptiveRT,
  normalization,
  simMeasure,
  goFactor,
  geFactor,
  cosAngleThresh,
  OverlapAlignment,
  dotProdThresh,
  gapQuantile,
  kerLen,
  hardConstrain,
  samples4gradient,
  objType = "light"
)

`refRT`	Peak's retention-time in reference run.
`XICs.ref`	List of extracted ion chromatograms from reference run.
`XICs.eXp`	List of extracted ion chromatograms from experiment run.
`globalFit`	Linear or loess fit object between reference and experiment run.
`alignType`	Available alignment methods are "global", "local" and "hybrid".
`adaptiveRT`	(numeric) Similarity matrix is not penalized within adaptive RT.
`normalization`	(character) Must be selected from "mean", "l2".
`simMeasure`	(string) Must be selected from dotProduct, cosineAngle, crossCorrelation, cosine2Angle, dotProductMasked, euclideanDist, covariance and correlation.
`goFactor`	(numeric) Penalty for introducing first gap in alignment. This value is multiplied by base gap-penalty.
`geFactor`	(numeric) Penalty for introducing subsequent gaps in alignment. This value is multiplied by base gap-penalty.
`cosAngleThresh`	(numeric) In simType = dotProductMasked mode, angular similarity should be higher than cosAngleThresh otherwise similarity is forced to zero.
`OverlapAlignment`	(logical) An input for alignment with free end-gaps. False: Global alignment, True: overlap alignment.
`dotProdThresh`	(numeric) In simType = dotProductMasked mode, values in similarity matrix higher than dotProdThresh quantile are checked for angular similarity.
`gapQuantile`	(numeric) Must be between 0 and 1. This is used to calculate base gap-penalty from similarity distribution.
`kerLen`	(integer) In simType = crossCorrelation, length of the kernel used to sum similarity score. Must be an odd number.
`hardConstrain`	(logical) If FALSE; indices farther from noBeef distance are filled with distance from linear fit line.
`samples4gradient`	(numeric) This parameter modulates penalization of masked indices.
`objType`	(char) Must be selected from light, medium and heavy.

(numeric)

Shubham Gupta, shubh.gupta@mail.utoronto.ca

ORCID: 0000-0003-3500-8152

License: (c) Author (2019) + GPL-3 Date: 2019-12-13

alignChromatogramsCpp

data(XIC_QFNNTDIVLLEDFQK_3_DIAlignR, package="DIAlignR")
data(oswFiles_DIAlignR, package="DIAlignR")
run1 <- "hroest_K120809_Strep0%PlasmaBiolRepl2_R04_SW_filt"
run2 <- "hroest_K120809_Strep10%PlasmaBiolRepl2_R04_SW_filt"
XICs.ref <- XIC_QFNNTDIVLLEDFQK_3_DIAlignR[[run1]][["4618"]]
XICs.eXp <- XIC_QFNNTDIVLLEDFQK_3_DIAlignR[[run2]][["4618"]]
RUNS_RT <- getRTdf(oswFiles_DIAlignR, ref = "run1", eXp = "run2", maxFdrGlobal = 0.05)
globalFit <- loess(RT.eXp ~ RT.ref, data = RUNS_RT, span = 0.1, control=loess.control(surface="direct"))
adaptiveRT <- 77.82315 #3.5*globalFit$s
## Not run: 
getMappedRT(refRT = 5238.35, XICs.ref, XICs.eXp, globalFit, alignType = "hybrid",
 adaptiveRT = adaptiveRT, normalization = "mean",
  simMeasure = "dotProductMasked", goFactor = 0.125, geFactor = 40, cosAngleThresh = 0.3,
  OverlapAlignment = TRUE, dotProdThresh = 0.96, gapQuantile = 0.5, kerLen = 9L, hardConstrain = FALSE,
  samples4gradient = 100)

## End(Not run)