pamr.batchadjust            package:pamr            R Documentation

_A _f_u_n_c_t_i_o_n _t_o _m_e_a_n-_a_d_j_u_s_t _m_i_c_r_o_a_r_r_a_y _d_a_t_a _b_y _b_a_t_c_h_e_s

_D_e_s_c_r_i_p_t_i_o_n:

     A function to mean-adjust microarray data by batches

_U_s_a_g_e:

     pamr.batchadjust(data)

_A_r_g_u_m_e_n_t_s:

    data: The input data. A list with components: x- an expression
          genes in the rows, samples in the columns, and y-  a vector
          of the class labels for each sample, and batchlabels- a
          vector of batch labels for each sample.

     This object if the same form as that produced by pamr.from.excel.

_D_e_t_a_i_l_s:

     'pamr.batchadjust'  does a genewise one-way ANOVA adjustment for
     expression values. Let x(i,j) be the expression for gene i in
     sample j. Suppose sample j in in batch b, and let B be the set of
     all samples in batch b. Then 'pamr.batchadjust'  adjusts  x(i,j)
     to x(i,j) - mean[x(i,j)]  where the mean is taken over all samples
     j in B

_V_a_l_u_e:

     A data object  of the same form as the input data, with x replaced
     by the adjusted x

_A_u_t_h_o_r(_s):

     Trevor Hastie,Robert Tibshirani, Balasubramanian Narasimhan, and
     Gilbert Chu

_R_e_f_e_r_e_n_c_e_s:

_E_x_a_m_p_l_e_s:

     set.seed(120)
     #generate some data
     x <- matrix(rnorm(1000*20),ncol=20)
     y <- sample(c(1:4),size=20,replace=TRUE)
     batchlabels <- sample(c(1:5),size=20,replace=TRUE)
     mydata <- list(x=x,y=factor(y),batchlabels=factor(batchlabels))

     mydata2 <- pamr.batchadjust(mydata)

