1.Introduction             package:limma             R Documentation

_I_n_t_r_o_d_u_c_t_i_o_n _t_o _t_h_e _L_I_M_M_A _P_a_c_k_a_g_e

_D_e_s_c_r_i_p_t_i_o_n:

     LIMMA is a library for the analysis of gene expression microarray
     data, especially the use of linear models for analysing designed
     experiments and the assessment of differential expression. LIMMA
     provides the ability to analyse comparisons between many RNA
     targets simultaneously. The normalization and data analysis
     functions are for two-colour spotted microarrays. The linear model
     and differential expression functions apply to all microarrays
     including Affymetrix and other multi-array oligonucleotide
     experiments.

     There are three types of documentation available. (1) The _LIMMA
     User's Guide_ can be reached through the "Accompanying
     documentation" at the top of the LIMMA contents page. (2) An
     overview of limma functions grouped by purpose is contained in the
     numbered chapters at the top of the LIMMA contents page, of which
     this page is the first. (3) The LIMMA contents page gives an
     alphabetical index of detailed help topics.

_A_u_t_h_o_r(_s):

     Gordon Smyth

_R_e_f_e_r_e_n_c_e_s:

     Smyth, G. K., Yang, Y.-H., Speed, T. P. (2003). Statistical issues
     in microarray data analysis. In: _Functional Genomics: Methods and
     Protocols_, M. J. Brownstein and A. B. Khodursky (eds.), Methods
     in Molecular Biology Volume 224, Humana Press, Totowa, NJ, pages
     111-136.

