ppsetApply package:affy R Documentation _A_p_p_l_y _a _f_u_n_c_t_i_o_n _o_v_e_r _t_h_e _P_r_o_b_e_S_e_t_s _i_n _a_n _A_f_f_y_B_a_t_c_h _D_e_s_c_r_i_p_t_i_o_n: Apply a function over the ProbeSets in an AffyBatch _U_s_a_g_e: ppsetApply(abatch, FUN, genenames = NULL, ...) ppset.ttest(ppset, covariate, pmcorrect.fun = pmcorrect.pmonly, ...) _A_r_g_u_m_e_n_t_s: abatch: An object inheriting from 'AffyBatch'. ppset: An object of class 'ProbeSet'. covariate: the name a covariate in the slot 'phenoData'. pmcorrect.fun: a function to corrrect PM intensities FUN: A function working on a 'ProbeSet' genenames: A list of Affymetrix probesets ids to work with. All probe set ids used when 'NULL'. ...: Optional parameters to the function 'FUN' _D_e_t_a_i_l_s: _V_a_l_u_e: Returns a 'list' of objects, or values, as returned by the function 'FUN' for each 'ProbeSet' it processes. _A_u_t_h_o_r(_s): Laurent Gautier _S_e_e _A_l_s_o: 'ProbeSet-class' _E_x_a_m_p_l_e_s: ppset.ttest <- function(ppset, covariate, pmcorrect.fun = pmcorrect.pmonly, ...) { probes <- do.call("pmcorrect.fun", list(ppset)) my.ttest <- function(x) { y <- split(x, get(covariate)) t.test(y[[1]], y[[2]])$p.value } r <- apply(probes, 1, my.ttest) return(r) } ## create a dataset data(affybatch.example) abatch <- merge(affybatch.example, affybatch.example2) intensity(abatch) <- 2^jitter(log2(intensity(abatch)),1,1) chip.variate <- c("a", "b", "a", "a", "b", "a", "a") pData(abatch) <- data.frame(whatever = chip.variate) ## run a test over _all_ probes. all.ttest <- ppsetApply(abatch, ppset.ttest, covariate="whatever")