normPCR                package:SLqPCR                R Documentation

_N_o_r_m_a_l_i_z_a_t_i_o_n _o_f _r_e_a_l-_t_i_m_e _q_u_a_n_t_i_t_a_t_i_v_e _R_T-_P_C_R _d_a_t_a

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

     This function can be used to normalize real-time quantitative
     RT-PCR data.

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

     normPCR(relData, HKs, method = "Vandesompele", na.rm = FALSE)

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

 relData: matrix or data.frame containing relative quantities (genes in
          columns) 

     HKs: integer, column numbers of housekeeping genes 

  method: method for the computation 

   na.rm: a logical value indicating whether 'NA' values should be
          stripped before the computation proceeds. 

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

     This function can be used to normalize real-time quantitative
     RT-PCR data.  The default method '"Vandesompele"' was proposed by 
     Vandesompele et al. (2002).

     Currently, only the method by Vandesompele et al. (2002) is
     implemented.

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

     Normalized expression data

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

     Dr. Matthias Kohl (SIRS-Lab GmbH) kohl@sirs-lab.com

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

     Jo Vandesompele, Katleen De Preter, Filip Pattyn et al. (2002).
     Accurate  normalization of real-time quantitative RT-PCR data by
     geometric averaging  of multiple internal control genes.  Genome
     Biology 2002. 3(7):research0034.1-0034.11. <URL:
     http://genomebiology.com/2002/3/7/research/0034/>

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

     data(SLqPCRdata)
     relData <- apply(SLqPCRdata, 2, relQuantPCR)
     geneStabM(relData[,c(3,4)])
     exprData <- normPCR(SLqPCRdata, c(3,4))

