computeCopynumber           package:crlmm           R Documentation

_C_o_m_p_u_t_e_s _c_o_p_y _n_u_m_b_e_r

_D_e_s_c_r_i_p_t_i_o_n:

     A function that transforms the quantile-normalized fluorescence
     intensities of the polymorphic and nonpolymorphic probes to a copy
     number scale.

_U_s_a_g_e:

     computeCopynumber(chrom, A, B, calls, conf, NP, plate, MIN.OBS=1, 
     envir, P, DF.PRIOR = 50, CONF.THR = 0.99, bias.adj=FALSE,
     priorProb, gender=NULL, SNR, SNRmin, seed=123, cdfName="genomewidesnp6",
     verbose=TRUE, ...)

_A_r_g_u_m_e_n_t_s:

   chrom: Chromosome (an integer).  Use 23 for X and 24 for Y.

       A: The A allele intensities from 'snprma'

       B: The B allele intensities from 'snprma'

   calls: The genotype calls from 'crlmm'

    conf: The genotype confidence scores from 'crlmm'

      NP: The quantile normalized intensities of the nonpolymorphic
          probes

   plate: The bach variable.  Should be the same length as the number
          of columns in A

 MIN.OBS: Integer: The minimum number of observations in a genotype
          cluster for which a SNP is deemed complete.

   envir: An environment to save intermediate objects

       P: Mainly for debugging a particular plate/batch.

DF.PRIOR: The degrees of freedom for the prior.  Higher numbers will
          shrink the variance and correlation more.

CONF.THR: A threshold for the genotype confidence scores. Genotypes
          with scores below the threshold are ignored when computing
          SNP-specific  within-genotype estimates of location and
          scale.

bias.adj: Logical: whether to adjust the location and scale parameters
          to account for biases due to common copy number variants. 
          This is a SNP-specific adjustment.  Parameters for background
          and slope must have already been estimated and available from
          the environment variable.

priorProb: Numerical vector of length 4.  The prior probability of each
          copy number state (0, 1, 2, 3, and 4). The default is a
          uniform prior.  Ignored if bias.adj=FALSE

  gender: Gender of subjects. If not specified, we predict the gender
          from the X chromosome.

     SNR: Signal to noise ratio from crlmm.

  SNRmin: The minimum value for the SNR - we suggest 5. Samples with
          SNR below SNRmin are excluded.

    seed: Seed used for random samples

 cdfName: Annotation package 

 verbose: Logical: verbose output

     ...: Currently ignored

_D_e_t_a_i_l_s:

     Parameters for copy number are estimated using a linear model
     based on the diallelic genotype calls.  No training data is used
     to estimate model parameters. Therefore, this function requires at
     least 10 samples to estimate copy number.  For small sample sizes
     (e.g., 10 - 30 samples), this function will impute model
     parameters for a large number of loci and the precision of the
     estimates will be reduced.

     Key assumption:

     - we assume that the median copy number at any given locus is two
     for each batch.  This assumption may not be appropriate for many
     datasets (e.g., a cancer dataset without normals processed in the
     same batch).

     The developmental version of this package available from
     Bioconductor has many improvements to this function.

_V_a_l_u_e:

     All objects created by this function are stored in the environment
     passed to this function.  In addition, each of the elements are
     specific to the chromosome(s) specified by the argument 'chrom'.
     For instance the element 'A' is the matrix of quantile-normalized
     intensities for the A-allele on chromosome(s) 'chrom'.  The
     element of this environment are as follows

       A: Matrix of quantile-normalized intensities for the A-allele

       B: Matrix of quantile-normalized intensities for the A-allele

      CA: Copy number estimate for the A-allele (x 100)

      CB: Copy number estimate for the B-allele (x 100)

   calls: CRLMM genotype calls (AA=1, AB=2, BB=3)

   chrom: Integer(s) indicating the chromosome(s)

    cnvs: Names of the nonpolymorphic probes.  These are the rownames
          of 'NP' and 'CT'.

    conf: CRLMM confidence scores for the genotypes:
          'round(-1000*log2(1-p))'

    corr: Correlation of the A and B alleles for genotypes AB

corrA.BB: Correlation of A and B alleles for genotypes BB

corrB.AA: Correlation of A and B alleles for genotypes AA

      CT: Copy number estimates for nonpolymorphic probe.  See 'cnvs'
          for the rownames.

  CT.sds: Standard deviation estimates for 'CT'

 npflags: Flags for the nonpolymorphic probes.

      Ns: The number of observations for each genotype/plate

     nuA: Background/cross-hyb for the A allele (plate- and
          locus-specific)

     nuB: Background/cross-hyb for the B allele (plate- and
          locus-specific)

     nuT: Background for the nonpolymorphic probes (plate- and
          locus-specific)

    phiA: Slope for the A allele (plate- and locus-specific)

    phiB: Slope for the B allele (plate- and locus-specific)

    phiT: Slope for the nonpolymorphic probes (plate- and
          locus-specific)

   plate: Factor indicating batch (same length as number of cel files)

   sig2A: Variance estimate for the A-allele signal (plate- and
          locus-specific)

   sig2B: Variance estimate for the B-allele signal (plate- and
          locus-specific)

   sig2T: Variance estimate for the nonpolymorphic signal (plate- and
          locus-specific)

snpflags: Flags for polymorphic probes

    snps: Rownames for 'A', 'B', 'CA', 'CB', ...

     sns: Sample names - the column names for 'A', 'B', ...

   steps: Steps completed. For internal use.

   tau2A: Variance estimate for the B-allele background/cross-hyb
          (plate- and locus-specific)

   tau2B: Variance estimate for the B-allele background/cross-hyb
          (plate- and locus-specific)

_A_u_t_h_o_r(_s):

     Rob Scharpf

_R_e_f_e_r_e_n_c_e_s:

     Nothing yet.

