crlmmIllumina             package:crlmm             R Documentation

_G_e_n_o_t_y_p_e _I_l_l_u_m_i_n_a _I_n_f_i_n_i_u_m _I_I _B_e_a_d_C_h_i_p _d_a_t_a _w_i_t_h _C_R_L_M_M

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

     This implementation of the CRLMM is especially designed for data
     from Illumina Infinium II BeadChips.

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

     crlmmIllumina(RG, XY, stripNorm=TRUE, useTarget=TRUE,
           row.names=TRUE, col.names=TRUE,
           probs=c(1/3, 1/3, 1/3), DF=6, SNRMin=5,
           gender=NULL, seed=1, save.it=FALSE, load.it=FALSE,
           intensityFile, mixtureSampleSize=10^5,
           eps=0.1, verbose=TRUE, cdfName, sns, recallMin=10,
           recallRegMin=1000, returnParams=FALSE, badSNP=0.7)

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

      RG: 'NChannelSet' containing R and G bead intensities

      XY: 'NChannelSet' containing X and Y bead intensities

stripNorm: 'logical'.  Should the data be strip-level normalized?

useTarget: 'logical' (only used when 'stripNorm=TRUE'). Should the
          reference HapMap intensities be used in strip-level
          normalization?

row.names: 'logical'. Use rownames - SNP names?

col.names: 'logical'. Use colnames - Sample names?

   probs: 'numeric' vector with priors for AA, AB and BB.

      DF: 'integer' with number of degrees of freedom to use with
          t-distribution.

  SNRMin: 'numeric' scalar defining the minimum SNR used to filter out
          samples.

  gender: 'integer' vector, with same length as 'filenames', defining
          sex. (1 - male; 2 - female)

    seed: 'integer' scalar for random number generator (used to sample
          'mixtureSampleSize' SNPs for mixture model.

 save.it: 'logical'. Save preprocessed data?

 load.it: 'logical'. Load preprocessed data to speed up analysis?

intensityFile: 'character' with filename of preprocessed data to be
          saved/loaded.

mixtureSampleSize: 'integer'. The number of SNP's to be used when
          fitting the mixture model.

     eps: Minimum change for mixture model.

 verbose: 'logical'.

 cdfName: 'character' defining the chip annotation (manifest) to use
          ('human370v1c', human550v3b', 'human650v3a', 'human1mv1c',
          'human370quadv3c', 'human610quadv1b', 'human660quadv1a'
          'human1mduov3b')

     sns: 'character' vector with sample names to be used.

recallMin: 'integer'. Minimum number of samples for recalibration.

recallRegMin: 'integer'. Minimum number of SNP's for regression.

returnParams: 'logical'. Return recalibrated parameters.

  badSNP: 'numeric'. Threshold to flag as bad SNP (affects batchQC)

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

     Note: The user should specify either the 'RG' or 'XY' intensities,
     not both.  Alternatively if 'crlmmIllumina' has been run already
     with 'save.it=TRUE', the preprocessed data can be loaded from file
     by specifying 'load.it=TRUE' and 'intensityFile' ('RG' or 'XY' are
     not needed in this case).

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

     A 'SnpSet' object which contains 

   calls: Genotype calls (1 - AA, 2 - AB, 3 - BB)

callProbability: confidence scores 'round(-1000*log2(1-p))'

   SNPQC: SNP Quality Scores

 batchQC: Batch Quality Scores

     along with center and scale parameters when 'returnParams=TRUE' in
     the 'featureData' slot.

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

     Matt Ritchie

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

     Carvalho B, Bengtsson H, Speed TP, Irizarry RA. Exploration,
     normalization, and genotype calls of high-density oligonucleotide
     SNP array data. Biostatistics. 2007 Apr;8(2):485-99. Epub 2006 Dec
     22. PMID: 17189563.

     Carvalho B, Louis TA, Irizarry RA. Describing Uncertainty in
     Genome-wide Genotype Calling. (in prep)

_E_x_a_m_p_l_e_s:

     ## crlmmOut = crlmmIllumina(RG)

