snprma                 package:crlmm                 R Documentation

_P_r_e_p_r_o_c_e_s_s_i_n_g _t_o_o_l _f_o_r _S_N_P _a_r_r_a_y_s.

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

     SNPRMA will preprocess SNP chips. The preprocessing consists of
     quantile normalization to a known target distribution and
     summarization to the SNP-Allele level.

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

     snprma(filenames, mixtureSampleSize = 10^5, fitMixture = FALSE, eps = 0.1, verbose = TRUE, seed = 1, cdfName, sns)

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

filenames: 'character' vector with file names. 

mixtureSampleSize: Sample size to be use when fitting the mixture
          model. 

fitMixture: 'logical'. Fit the mixture model? 

     eps: Stop criteria. 

 verbose: 'logical'. 

    seed: Seed to be used when sampling. 

 cdfName: cdfName: 'GenomeWideSnp_5', 'GenomeWideSnp_6' 

     sns: Sample names. 

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

       A: Summarized intensities for Allele A

       B: Summarized intensities for Allele B

     sns: Sample names

     gns: SNP names

     SNR: Signal-to-noise ratio

     SKW: Skewness

mixtureParams: Parameters from mixture model

 cdfName: Name of the CDF

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

     if (require(genomewidesnp5Crlmm) & require(hapmapsnp5)){
       path <- system.file("celFiles", package="hapmapsnp5")

       ## the filenames with full path...
       ## very useful when genotyping samples not in the working directory
       cels <- list.celfiles(path, full.names=TRUE)
       snprmaOutput <- snprma(cels)
       snprmaOutput[["A"]][1:10,]
       snprmaOutput[["B"]][1:10,]
     }

