paramsDIAlignR: Parameters for the alignment functions

View source: R/utils.R

paramsDIAlignRR Documentation

Parameters for the alignment functions

Description

Retention alignment requires OpenSWATH/pyProphet extracted features and chromatograms. This function provides a suite of parameters used for selecting features and manipulating chromatograms. Chromatogram alignment can be performed via reference based or progressively via rooted or unrooted tree. This function provides sensible parameters for these tasks.

Usage

paramsDIAlignR()

Value

A list of parameters:

runType

(string) must be one of the strings "DIA_Proteomics", "DIA_IPF", "DIA_Metabolomics".

chromFile

(string) must either be "mzML" or "sqMass".

maxFdrQuery

(numeric) a numeric value between 0 and 1. It is used to filter peptides from osw file which have SCORE_MS2.QVALUE less than itself.

maxIPFFdrQuery

(numeric) A numeric value between 0 and 1. It is used to filter features from osw file which have SCORE_IPF.QVALUE less than itself. (For PTM IPF use)

maxPeptideFdr

(numeric) a numeric value between 0 and 1. It is used to filter peptides from osw file which have SCORE_PEPTIDE.QVALUE less than itself.

analyteFDR

(numeric) the upper limit of feature FDR to be it considered for building tree.

treeDist

(string) the method used to build distance matrix. Must be either "rsquared", "count" or "RSE".

treeAgg

(string) the method used for agglomeration while performing hierarchical clustering. Must be either "single", "average" or "complete".

alignToRoot

(logical) if TRUE, align leaves to the root in hierarchical clustering, else use already save aligned vectors.

prefix

(string) name to be used to define merged runs.

context

(string) used in pyprophet peptide. Must be either "run-specific", "experiment-wide", or "global".

unalignedFDR

(numeric) must be between 0 and maxFdrQuery. Features below unalignedFDR are considered for quantification even without the RT alignment.

alignedFDR1

(numeric) must be between unalignedFDR and alignedFDR2. Features below alignedFDR1 and aligned to the reference are considered for quantification.

alignedFDR2

(numeric) must be between alignedFDR1 and maxFdrQuery. Features below alignedFDR2 and within certain distance from the aligned time are considered for quantification after the alignment.

criterion

(integer) strategy to select peak if found overlapping peaks. 1:intensity, 2: RT overlap, 3: mscore, 4: edge distance

level

(string) apply maxPeptideFDR on Protein as well if specified as "Protein". Default: "Peptide".

integrationType

(string) method to ompute the area of a peak contained in XICs. Must be from "intensity_sum", "trapezoid", "simpson".

baseSubtraction

logical TRUE: remove background from peak signal using estimated noise levels.

baselineType

(string) method to estimate the background of a peak contained in XICs. Must be from "none", "base_to_base", "vertical_division_min", "vertical_division_max".

fitEMG

(logical) enable/disable exponentially modified gaussian peak model fitting.

recalIntensity

(logical) recalculate intensity for all analytes.

fillMissing

(logical) calculate intensity for ananlytes for which features are not found.

XICfilter

(string) must be either sgolay, boxcar, gaussian, loess or none.

polyOrd

(integer) order of the polynomial to be fit in the kernel.

kernelLen

(integer) number of data-points to consider in the kernel.

globalAlignment

(string) must be either "loess" or "linear".

globalAlignmentFdr

(numeric) a numeric value between 0 and 1. Features should have m-score lower than this value for participation in LOESS fit.

globalAlignmentSpan

(numeric) spanvalue for LOESS fit. For targeted proteomics 0.1 could be used.

RSEdistFactor

(numeric) defines how much distance in the unit of rse remains a noBeef zone.

normalization

(string) must be selected from "mean", "l2".

simMeasure

(string) must be selected from dotProduct, cosineAngle, crossCorrelation, cosine2Angle, dotProductMasked, euclideanDist, covariance and correlation.

alignType

(numeric) available alignment methods are "global", "local" and "hybrid".

goFactor

(numeric) penalty for introducing first gap in alignment. This value is multiplied by base gap-penalty. Should be between 10-1000.

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) modulates penalization of masked indices.

fillMethod

(string) must be either "spline", "sgolay" or "linear".

splineMethod

(string) must be either "fmm" or "natural".

mergeTime

(string) must be either "ref", "avg", "refStart" or "refEnd".

keepFlanks

(logical) TRUE: Flanking chromatogram is not removed.

fraction

(integer) indicates which fraction to align.

fractionNum

(integer) Number of fractions to divide the alignment.

lossy

(logical) if TRUE, time and intensity are lossy-compressed in generated sqMass file.

useIdentifying

(logical) Set TRUE to use identifying transitions in alignment. (DEFAULT: FALSE)

Author(s)

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

ORCID: 0000-0003-3500-8152

License: (c) Author (2020) + GPL-3 Date: 2020-07-11

See Also

checkParams, alignTargetedRuns

Examples

params <- paramsDIAlignR()

shubham1637/DIAlignR documentation built on March 29, 2023, 8:45 p.m.