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QSQTLSCAN procedure

Performs a genome-wide scan for QTL effects (Simple and Composite Interval Mapping) in single-environment trials (M.P. Boer, M. Malosetti, S.J. Welham & J.T.N.M. Thissen).


PRINT = string tokens What to print (summary, progress, model, components, effects, means, stratumvariances, monitoring, vcovariance, deviance, Waldtests, missingvalues, covariancemodels); default summ
PLOT = string token Whether to plot the profile along the genome (profile); default prof
POPULATIONTYPE = string token Type of population (BC1, DH1, F2, RIL, BCxSy, CP); must be set
ALPHALEVEL = scalar Defines a genome-wide significance level to calculate the threshold; default 0.05
COFACTORS = variate Index numbers of loci to be used as cofactors for the genetic background
COFWINDOW = scalar Specifies a window for cofactor exclusion from the model; default 106 which means that all cofactors on the same chromosomes are excluded
THRMETHOD = string token Which method to use to calculate the threshold for QTL detection (bonferroni, liji, given); default liji
THRESHOLD = scalar Threshold value for test statistic when THRMETHOD=given
DISTANCE = scalar Distance between loci when THRMETHOD=bonferroni; default 4
FIXED = formula Formula with extra fixed terms
UNITFACTOR = factor Saves the units factor required to define the random model when UNITERROR is to be used
STATISTICTYPE = string token Which test statistic to plot and save using the STATISTICS parameter (wald, minlog10p); default minl
COLOURS = scalar, variate or text Colours to use for the chromosomes; default * uses the colours of pens 1, 2 up to the number of chromosomes
TITLE = text General title for plot
YTITLE = text Title for the y-axis; default uses the identifier of the STATISTICS variate or pointer
XTITLE = text Title for the x-axis; default 'Chromosomes'
MVINCLUDE = string tokens Whether to include units with missing values in the explanatory factors and variates and/or the y-variates (explanatory, yvariate); default expl, yvar
MAXCYCLE = scalar Limit on the number of iterations; default 100
WORKSPACE = scalar Number of blocks of internal memory to be set up for use by the REML algorithm; default 100


TRAIT = variates Quantitative trait to be analysed; must be set
GENOTYPES = factors Genotype factor; must be set
UNITERROR = variates Uncertainty on trait means (derived from individual unit or plot error) to be included in QTL analysis; default * i.e. omitted
ADDITIVEPREDICTORS = pointers Additive genetic predictors; must be set
ADD2PREDICTORS = pointers Second (paternal) set of additive genetic predictors
DOMINANCEPREDICTORS = pointers Dominance genetic predictors
CHROMOSOMES = factors Chromosomes corresponding to the genetic predictors; must be set
POSITIONS = variates Positions on the chromosomes corresponding to the genetic predictors; must be set
IDLOCI = texts Labels for the loci
IDMGENOTYPES = texts Labels for the genotypes corresponding to the genetic predictors
IDEFFECTS = texts Labels for the effects along the y-axis, in the frame below the profile plot
IDPARENTS = texts Labels to use to identify the parents
QSTATISTICS = variates Saves test statistics for QTL effects along the genome
QEFFECTS = pointers Saves QTL effects along the genome (additive effects,and, if specified, also second additive and dominance effects)
QSE = pointers Saves standard errors of the QTL effects
OUTFILENAME = texts Name of the Genstat workbook file (*.gwb) to be created
DFILENAME = texts Name of the graphs file for the plots


QSQTLSCAN performs a genome-wide QTL scan in single-environment trials. It uses single observation per genotype as phenotypic data. The response variable must be specified by the TRAIT parameter, and the genotypes by the GENOTYPES parameter. The POPULATIONTYPE option must be set to specify the population type.

Molecular information must be provided in the form of additive genetic predictors stored in variates and supplied, in a pointer, by the ADDITIVEPREDICTORS parameter. Non-additive effects can be included in the model by using the DOMINANCEPREDICTORS parameter to specify dominance genetic predictors (e.g. in a F2 population); again they are stored in variates and supplied in a pointer. In the case of segregating F1 populations (outbreeders) two sets of additive genetic predictors must be specified: the maternal ones by the ADDITIVEPREDICTORS parameter, and the paternal ones by the ADD2PREDICTORS parameter. The corresponding map information for the genetic predictors must be given by the CHROMOSOMES and POSITIONS parameters. The labels for the loci can be supplied by the IDLOCI parameter, and the labels for the genotypes in the marker data can be supplied by the IDMGENOTYPES parameter. If IDMGENOTYPES is set, the match between the genotypes in the phenotypic and in the marker data will be checked.

The QTL detection model assumes genotypes as random and QTLs as fixed effects. Extra fixed effects can be specified using the FIXED option. The QTL search can be performed without cofactors (Simple Interval Mapping) or with cofactors that control for genetic background effects (Composite Interval Mapping). For Composite Interval Mapping, the COFACTORS option must specify a variate containing the index numbers of the loci designated as cofactors. The COFWINDOW option defines a window around a tested position within which cofactors are temporarily excluded from the model.

The MVINCLUDE, MAXCYCLE and WORKSPACE options operate in the same way as these options of the REML directive. The UNITERROR parameter allows uncertainty on the trait means (derived from individual unit or plot error) to be specified to include in the random model; by default this is omitted. The UNITFACTOR option allows the factor that is needed to define the unit-error term to be saved (this would be needed, for example, to save information later about the term using VKEEP).

The method to define the threshold value is defined by the THRMETHOD option and uses a genome-wide error rate defined by the option ALPHALEVEL (default 0.05). If THRMETHOD=given, a user-defined threshold value must be specified using the THRESHOLD option. If THRMETHOD=bonferroni, an effective number of tests is calculated using the value specified by the DISTANCE option as the step size (default 4). Alternatively the liji setting uses the method described by Li & Ji (2005). See procedure QTHRESHOLD for details.

The PRINT option specifies the output to be displayed. The summary setting prints the information about the QTLs retained in the model, and the progress setting shows how the scan is progressing. The other settings correspond to those in the PRINT option of the REML directive.

By default QSQTLSCAN plots the test statistic associated with the effects of the genetic predictors against their position on the chromosomes, but you can set option PLOT=* to suppress this. The STATISTICTYPE option specifies what to plot along the y-axis of the upper plot, either the test statistic or the associated probability value (on a -log10 scale), and also defines what is saved in the variates specified by the QSTATISTICS parameter. The IDEFFECTS parameter can be used to label the effects, and the IDPARENTS parameter can supply labels to identify the parents.

The corresponding effects of each genetic predictor and their standard errors can be saved by the QEFFECTS and QSE parameters, respectively. These are saved in pointers that contain a single variate if only the ADDITIVEPREDICTORS parameter is specified, or two or three variates if the DOMINANCEPREDICTORS and/or ADD2PREDICTORS parameters are also specified. The TITLE, YTITLE and XTITLE options can specify the general title of the graph, the title of the y-axis and the title of the x-axis, respectively. The colours to use for the chromosomes in the upper graph are specified by the COLOURS option using either a text of colour names or a variate of RGB values (see the PEN directive for details). If COLOURS is not set, the default is to use the default colours of the pens 1, 2, onwards, up to the number of chromosomes. By default, the plot is sent to the screen. However, you can supply a file for the plot, using the DFILENAME parameter. You can discover the types of graphics file that are supported by running the command.

The OUTFILENAME parameter can be used to write the QSTATISTICS, QEFFECTS and QSE structures to a Genstat work book file in a sheet named STATISTICS. This parameter should not contain an extension as the extension is defined automatically given as .gwb.




QSQTLSCAN fits the following mixed models repeatedly along the genome:

1)       yi = μ + ΣfF xif cf + xi αlj + Gi

if only ADDITIVEPREDICTORS are specified

2)       yi = μ + ΣfF ( xifadd cfadd + xifdom cfdom ) + ( xiadd αadd + xidom αdom ) + Gi

if DOMINANCEPREDICTORS are also specified

3)       yi = μ + ΣlL ( xifadd cladd + xifadd2 cladd2 + xifdom cldom )

+ ( xiadd αadd + xiadd2 αadd2 + xidom αdom ) + Gi

if both ADD2PREDICTORS and DOMINANCEPREDICTORS are specified (for population type CP)

where yi is the trait value of individual i, F is a set of cofactors (if cofactors are included in the model), and xifadd and xiadd are the additive genetic predictors of genotype i at the cofactor positions and at the tested position, respectively. The associated effects are denoted by ciadd and αadd for cofactors and tested position respectively. In model 2 and 3, xifdom and xidom are dominance genetic predictors of genotype i at the cofactor positions and at the tested position, respectively, with associated effects cfdom, and αdom. In model 3, xifadd and xiadd are the additive genetic predictors for the maternal genotype, for cofactors and tested position, respectively, and xifadd2 and xiadd2 are the equivalent additive genetic predictors for the paternal genotype. Finally xifdom and xidom are the dominance genetic predictors for the cofactors and tested position, respectively. The associated effects are given by cfadd, cfadd2 and cfdom for cofactors, and αadd, αadd2 and αdom for tested positions. Genetic predictors are genotypic covariables that reflect the genotypic composition of a genotype at a specific chromosome location (Lynch & Walsh 1998). The residual unexplained genetic and environmental effects are modelled by the Gi term, which is assumed to follow a Normal distribution with mean 0 and variance σ2.

The procedure uses the REML directive iteratively to fit the model at each chromosome position, storing the Wald statistic for hypothesis testing. The resulting Wald statistic or the associated probability value (on a -log10 scale) can be plotted to produce the well-known profile plots used for interpretation.

Action with RESTRICT

Restrictions are not allowed.


Lynch, M. & Walsh, B. (1998). Genetics and Analysis of Quantitative Traits. Sinauer Associates, Sunderland, MA.

See also


Commands for: Statistical genetics and QTL estimation.


SPLOAD    [PRINT=*] '%GENDIR%/Examples/F2maize_traits.gsh'
&         '%GENDIR%/Examples/F2maizemarkers.GWB'; SHEET='LOCI'
&         '%GENDIR%/Examples/F2maizemarkers.GWB'; SHEET='ADDPREDICTORS'
&         '%GENDIR%/Examples/F2maizemarkers.GWB'; SHEET='DOMPREDICTORS'
" create single environment "
SUBSET    [E.EQ.6] G,yld
POINTER   [MODIFY=yes; NVALUES=idlocus] addpred
POINTER   [MODIFY=yes; NVALUES=idlocus] dompred
          STATISTICTYPE=minlog; THRESHOLD=thres; TITLE='yld Wald 2 d.f.']\ 
          TRAIT=yld; GENOTYPES=G; CHROMOSOMES=mkchr;\ 
          POSITIONS=mkpos; IDLOCI=idlocus;\ 
          QSTATISTICS=minlog10p; QEFFECTS=qeff2; QSE=qse2;\ 
Updated on June 19, 2019

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