Estefania and Dario A more efficient way to do this: > row.positive.counts <- apply(dup.data$counts, 1, function(a.row) sum(a.row > > 0))
would be this: row.positive.counts <- rowSums( dup.data$counts > 0 ) You might prefer to use the functions rowSums(), rowMeans(), colSums(), colMeans() instead of apply(), where you can. They are much faster. Best wishes Davis On 26 August 2011 10:00, Dario Strbenac <d.strbe...@garvan.org.au> wrote: > Hi Estefania, > > If you want both columns to be non-zero, you should do > > filtered <- dup.data[row.positive.counts == ncol(dup.data$counts), ] > > It makes a boolean vector for each row, then sums it, because TRUE is the > same as 1, so the sum gives you how many columns are greater than zero. Then, > the rows that have as many positive numbers as there are columns in the data > frame are kept. > > To find unchanged genes, you might do > > unchanged <- dup.de.com$table[dup.de.com$table[, "logFC"] > -0.2 & > dup.de.com$table[, "logFC"] < 0.2, ] > > replacing 0.2 with what you think the biggest fold change that unchanged > genes might have. > > ---- Original message ---- >>Date: Thu, 25 Aug 2011 11:39:03 -0300 (ART) >>From: bioc-sig-sequencing-boun...@r-project.org (on behalf of Estefania >>Mancini <estefania.manc...@indear.com>) >>Subject: [Bioc-sig-seq] extract non-zero rows >>To: bioc-sig-sequencing@r-project.org >> >>Dear all >>I have loaded and analyzed properly 4 454 dataset, corresponding to control >>and stress samples with their biological replicates. >>I would like to know if is possible to filter, in my DGEList object >> >>-which tags dont have zero in any column, >>-which of these tags could be consider "housekeeping" (at least with logFC >>near 0) >> >>The object DGEList looks like this: >> >>>dup.data >>An object of class "DGEList" >>$samples >> group lib.size norm.factors >>A8_control control 77953 1 >>A8_stress stress 176860 1 >>mq_control control 98109 1 >>mq_stress stress 145839 1 >>pi_control control 132479 1 >>pi_stress stress 142484 1 >>tj_control control 65827 1 >>tj_stress stress 144278 1 >> >>I have tried to filter using the suggested function: >>>dup.de.filter <- dup.data[rowSums(dup.data$counts) >= 0, ] >>or with >>>dup.de.filter <- dup.data[rowSums(dup.data$counts) >= 1, ] >>but have no changes at all. I have many rows which 0 and 1 read in some >>column which should be excluded. >> >>Also: >>dup.de.com >>An object of class "DGEExact" >>$table >> logConc logFC p.value >>Glyma13g11940.8 -2.588833 0.26176050 0.7348221 >>Glyma13g11900.1 -2.875548 0.03020441 0.9688072 >>Glyma09g24780.1 -3.501041 -0.12108619 0.8754371 >>Glyma13g12050.1 -3.224648 0.03036675 0.9691009 >>Glyma13g12070.1 -3.743064 0.14416487 0.8521188 >>19860 more rows ... >> >>$comparison >>[1] "control" "stress" >>$genes >>NULL >> >>Thanks in advance, >>Estefania >> >>_______________________________________________ >>Bioc-sig-sequencing mailing list >>Bioc-sig-sequencing@r-project.org >>https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing > > > -------------------------------------- > Dario Strbenac > Research Assistant > Cancer Epigenetics > Garvan Institute of Medical Research > Darlinghurst NSW 2010 > Australia > > _______________________________________________ > Bioc-sig-sequencing mailing list > Bioc-sig-sequencing@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing > _______________________________________________ Bioc-sig-sequencing mailing list Bioc-sig-sequencing@r-project.org https://stat.ethz.ch/mailman/listinfo/bioc-sig-sequencing
