
"To do" list for R/qtl
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This file is intended to contain a list of many of the additions and
revisions that are planned for the R/qtl package.  

If you any additions or revisions to suggest, please send an email to
Karl Broman, <kbroman@biostat.wisc.edu>.
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SHORT TERM:

o pull all of the genoprob and imputation information out of 
  the qtl objects and replace it with indices to the information
  in the cross object.  (This stuff takes up too much space!)

o For the stepwiseqtl function:
   - should be able to save all models with plod within some value
     of the best model 
   - QTL x covariate interactions in countterms
   - it'd be nice to be able to have all models that are one term
     away from the optimal model (maybe this could be a separate
     function) 
   - it'd be nice to be able to easily make a plot of the final model
     plus information about all models that are one term away

o In plot.geno, allow use of xlim and ylim; also do this in
  plot.scanoneperm and plot.scantwoperm.

o read.cross is slow loading when there are *lots* of phenotypes

o make various functions work appropriately with class "special"
  (eg, plot and summary)

o Add an explanation regarding the coding in the coefficient 
  estimates in fitqtl().  Add text to the help file for
  summary.fitqtl(). 

o FAQ: - constructing covariate matrices

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MEDIUM-SHORT TERM:

o revise read.cross with format="mm" to deal with ril by selfing
  and/or sib mating

o Batch permutations: study relationship between time and size of
  batches.  Perhaps do batches not all at once but in pieces.

o get scanone and scantwo to work with a single marker on a
  chromosome. 

o Fix convergence problems in scanone with method="ehk", especially
  in the case of covariates and interactions. 

o cM coordinates in scantwo plot for multiple chromosomes: Fix
  plot.scantwo for the case that incl.markers=TRUE, so that positions
  are not equally spaced, but are according to the genetic map.  (This
  is working if just one chromosome is plotted, but should be made to
  work generally.)

o Plotting scanone results for *many* phenotypes as an image plot.
  (Perhaps threshold the really high LODs and eliminate curves that
  fail to meet a given threshold.)

o plots of segregation ratios at markers

o lodint/bayesint as option to summary.scanone.

o conditional LOD scores from scantwo output.

o scanqtl: if formula symmetric w/ respect to two QTL that are on the 
  same chromosome, only scan the triangle (rather than the square)

o write tools for converting the output from scanqtl() to the format
  for scanone() or scantwo(), according to whether it's a 1-d or
  2-d search, or print a warning otherwise.

o pairprob at markers + putative QTL?  For linked loci in scanqtl by
  HK/EM. 

o Allow plot.geno (or other cases in which subset.cross is used to
  pull out individuals) to refer to individual IDs.

o findpeaks() function, for finding multiple maxima on a chromosome
  in scanone results.

o incorporate revised code from Steffen Moeller.

o Tabbing in "allpheno" from summary.scanone output looks odd...maybe
  use spaces? [Gary reported this, but I've not been able to reproduce
  this problem.] 

o X chromosome in cim().

o Include Bjarke's code on eHK for scantwo.

o Go through all of the various plot functions and make sure that
  the x- and y-axis labels are created with axis() rather than
  text() and segments().  This way, the size of the labels can be
  modified with par(cex.axis)

o Turn the tutorial into a Sweave vingette, to conform to the
  Bioconductor requirements?

o Revise plot.rf so that it can have different color schemes, as in
  plot.scantwo.  Allow a zscale.

o Simpler methods to get at interesting bits in the est.rf results.

o Revise read.cross so that if all genotypes are 
  AA and BB, the thing is called DH by default.  Maybe add an 
  argument to read.cross so that one may specify the cross type?

o Finish off the work to get coefficient estimates by imputation in
  fitqtl for the X chromosome in BC and F2. 

o Revise c.cross so that you can combine crosses even if there are
  different numbers of chromosomes

o Ensure consistency in use of chromosome numbers vs names/IDs when
  plotting results of genome scans, subsetting crosses, and so forth
  (sometimes #'s taken as indices and sometimes as names).

o Documentation on RI lines.

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MEDIUM TERM:

o covariates with 2part model in scanone

o Analysis of censored phenotypes.

o Analysis of residuals.

o read.cross for "qtx" sometimes doesn't seem to take the
  genotype pattern appropriately; read in a backcross as if it
  were an F2. 

o An NA in the mapmaker data file caused an error in read.cross;
  the line became too long.  Maybe this is true whenever an item
  doesn't match what is expected.

o Speed up read.cross.mm; deliver meaningful errors if map/genotypes
  don't match, and if too many genotypes in a row.

o scanone() with model="2part" gives NAs as LOD scores if there
  is complete penetrance (one of the p's goes to 1).  This doesn't
  happen with model="binary".

  The problem is that if everyone with a certain genotype survives,
  then you have great segregation distortion if you look at only
  the dead individuals, and so you can't estimate both means.

o In MIM: allow return of SEs of effects.  Write coef.mim, resid.mim,
  and dev.mim to pull out the est'd coefficients, the residuals, and
  the "deviance" (2 * ln likelihood).

o Incorporate the DIRECT algorithm stuff from Hao

o scanone with additive alleles at QTL

o Pull out results for an interval from scanone.

o Modify the map expansion for RI lines for the X chromosome.
  [really need to add additional functions for mapping, as
   the marginal genotype distribution is 2:1 rather than 1:1]
  --the transition matrix is not symmetric 
  Pr(BB|AA) = 2r/(1+4r) and Pr(AA|BB) = 4r/(1+4r)

o Ability to get at the individual contributions to the LOD score? 

o Incorporate code from Brian Yandell, Fei Zou and Amy Jin on
  semi-parametric QTL mapping methods.

o Add appropriate functions to analyze advanced intercrosses (AILs). 

o Analysis of binary traits by imputation

o Include widgets for getting more easy access to the data.

o Allow phenotypes on multiple individuals (esp for recombinant inbred
  lines). 

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LONG TERM:

o HMM stuff for BCn data.

o "embarassing parallel" processing for permutation tests (Rmpi, snow)

o Imprinting/parent-of-origin effects.

o Treating a covariate as a random effect.

o Multiple phenotypes (esp. regarding pleiotropy).

o Model search for MIM etc...forward and stepwise selection.

o Function to plot, for a specified q1, LOD{q2|q1} vs q2 (using the
  output from scantwo).

o Take the fit of the null model outside of the C code for
  the imputation method in scanone and scantwo, so that it
  only has to be done once (rather than for each chr or chr pair).

o Starting values for EM for the two-part model (and more generally).
  Allow the option of an automatic selection of multiple starting
  points. 

o Generalized linear models in scanone and scantwo.

o Analysis functions such as scanone and scantwo might assign an
  attribute to their output which identifies the input data and/or
  function call.

o Re-write the C code for EM underneath scanone and scantwo so that it
  is not so tedious.

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end of TODO.txt
