Duplicate correlation error in limma
1
0
Entering edit mode
@gordon-smyth
Last seen 15 minutes ago
WEHI, Melbourne, Australia
Dear Paul, While I know what this error is, I haven't seen it arise previously in duplicateCorrelation() with microarray data, so it is hard to give advice. It is a numeric error in the inner optimization routine which may arise for reasons which are hard to pin down. Try removing rows from the hx object, e.g., run duplicateCorrelation() on the top half or bottom half of the spots. One or the other may run if the problem is caused by one particular probe. Also check that your design matrix is appropriate, perhaps by trying it with avedups(). Best wishes Gordon > Date: Fri, 4 Sep 2009 11:25:55 +0100 > From: Paul Geeleher <paulgeeleher at="" gmail.com=""> > Subject: [BioC] Duplicate correlation error in limma > To: Bioconductor mailing list <bioconductor at="" stat.math.ethz.ch=""> > Content-Type: text/plain > > Hello folks, > > I'm getting this error when I run duplicate correlation: > > corfit <- duplicateCorrelation(mat at hx, design, ndups=3, spacing=1) > Error in glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace = > trace) : > Starting values give negative fitted values > > I saw a previous post on the mailing list where this error occurred because > of drastically different values in the input matrix, but I don't have that > problem so any help would be greatly appreciated. Here's some extra info: > > > GSM219865 GSM219869 GSM219870 GSM219872 > Min. : 2.788 Min. : 2.445 Min. : 3.091 Min. : 2.567 > 1st Qu.: 4.491 1st Qu.: 4.639 1st Qu.: 4.434 1st Qu.: 4.782 > Median : 5.252 Median : 5.305 Median : 4.945 Median : 5.450 > Mean : 6.051 Mean : 6.030 Mean : 6.045 Mean : 6.032 > 3rd Qu.: 7.064 3rd Qu.: 6.817 3rd Qu.: 7.231 3rd Qu.: 6.612 > Max. :13.602 Max. :14.033 Max. :13.113 Max. :14.167 > GSM219879 GSM219880 GSM219881 GSM219882 > Min. : 3.201 Min. : 2.832 Min. : 3.058 Min. : 3.144 > 1st Qu.: 4.512 1st Qu.: 4.530 1st Qu.: 4.490 1st Qu.: 4.531 > Median : 5.095 Median : 5.049 Median : 5.124 Median : 5.029 > Mean : 6.023 Mean : 6.028 Mean : 6.011 Mean : 6.052 > 3rd Qu.: 6.886 3rd Qu.: 6.897 3rd Qu.: 7.087 3rd Qu.: 7.087 > Max. :13.979 Max. :13.766 Max. :13.600 Max. :13.382 > GSM219886 GSM219887 GSM219892 GSM219894 > Min. : 3.236 Min. : 3.007 Min. : 3.048 Min. : 2.707 > 1st Qu.: 4.419 1st Qu.: 4.520 1st Qu.: 4.407 1st Qu.: 4.674 > Median : 4.971 Median : 5.146 Median : 4.968 Median : 5.290 > Mean : 6.048 Mean : 6.061 Mean : 6.069 Mean : 6.013 > 3rd Qu.: 7.036 3rd Qu.: 7.023 3rd Qu.: 7.237 3rd Qu.: 6.589 > Max. :13.723 Max. :14.208 Max. :13.281 Max. :14.199 > GSM219896 GSM219899 GSM219900 GSM219902 > Min. : 3.137 Min. : 3.217 Min. : 2.896 Min. : 2.986 > 1st Qu.: 4.523 1st Qu.: 4.559 1st Qu.: 4.430 1st Qu.: 4.514 > Median : 4.960 Median : 5.163 Median : 5.074 Median : 5.090 > Mean : 6.046 Mean : 6.026 Mean : 6.035 Mean : 6.002 > 3rd Qu.: 7.117 3rd Qu.: 6.746 3rd Qu.: 7.074 3rd Qu.: 7.077 > Max. :13.824 Max. :13.816 Max. :13.760 Max. :13.700 > GSM219903 GSM219905 GSM219907 GSM219909 > Min. : 3.014 Min. : 3.179 Min. : 3.062 Min. : 2.756 > 1st Qu.: 4.465 1st Qu.: 4.418 1st Qu.: 4.372 1st Qu.: 4.693 > Median : 5.027 Median : 4.998 Median : 4.885 Median : 5.386 > Mean : 6.057 Mean : 6.045 Mean : 6.056 Mean : 6.027 > 3rd Qu.: 7.280 3rd Qu.: 7.160 3rd Qu.: 7.175 3rd Qu.: 6.380 > Max. :13.592 Max. :13.572 Max. :13.637 Max. :14.457 > GSM219911 GSM219912 GSM219913 GSM219918 > Min. : 3.048 Min. : 1.977 Min. : 2.819 Min. : 2.929 > 1st Qu.: 4.431 1st Qu.: 4.730 1st Qu.: 4.440 1st Qu.: 4.614 > Median : 4.857 Median : 5.303 Median : 4.956 Median : 5.192 > Mean : 6.017 Mean : 6.013 Mean : 6.062 Mean : 6.041 > 3rd Qu.: 7.233 3rd Qu.: 6.513 3rd Qu.: 7.362 3rd Qu.: 6.948 > Max. :13.312 Max. :14.396 Max. :13.212 Max. :14.050 > GSM219919 GSM219920 GSM219934 GSM219937 > Min. : 3.227 Min. : 3.294 Min. : 2.737 Min. : 2.600 > 1st Qu.: 4.363 1st Qu.: 4.385 1st Qu.: 4.518 1st Qu.: 4.665 > Median : 4.991 Median : 4.869 Median : 5.110 Median : 5.318 > Mean : 6.059 Mean : 6.041 Mean : 6.039 Mean : 6.030 > 3rd Qu.: 7.171 3rd Qu.: 7.175 3rd Qu.: 6.915 3rd Qu.: 6.814 > Max. :13.454 Max. :13.221 Max. :13.875 Max. :14.067 > GSM219938 GSM219939 GSM219940 GSM219943 > Min. : 2.946 Min. : 2.861 Min. : 3.266 Min. : 2.729 > 1st Qu.: 4.676 1st Qu.: 4.635 1st Qu.: 4.362 1st Qu.: 4.584 > Median : 5.354 Median : 5.226 Median : 5.048 Median : 5.123 > Mean : 6.047 Mean : 6.034 Mean : 6.046 Mean : 6.019 > 3rd Qu.: 6.909 3rd Qu.: 6.754 3rd Qu.: 7.249 3rd Qu.: 6.928 > Max. :14.083 Max. :14.110 Max. :13.329 Max. :13.836 > GSM219944 GSM219945 GSM219948 GSM219950 > Min. : 2.724 Min. : 3.149 Min. : 2.902 Min. : 2.900 > 1st Qu.: 4.590 1st Qu.: 4.412 1st Qu.: 4.593 1st Qu.: 4.321 > Median : 5.289 Median : 5.076 Median : 5.172 Median : 5.114 > Mean : 6.055 Mean : 6.078 Mean : 6.062 Mean : 6.050 > 3rd Qu.: 6.927 3rd Qu.: 7.097 3rd Qu.: 6.843 3rd Qu.: 7.100 > Max. :14.071 Max. :13.596 Max. :13.920 Max. :13.692 > GSM219952 GSM219953 GSM219954 GSM219955 > Min. : 2.986 Min. : 2.784 Min. : 2.437 Min. : 3.065 > 1st Qu.: 4.581 1st Qu.: 4.613 1st Qu.: 4.710 1st Qu.: 4.410 > Median : 5.221 Median : 5.179 Median : 5.293 Median : 5.094 > Mean : 6.043 Mean : 6.042 Mean : 6.048 Mean : 6.050 > 3rd Qu.: 6.843 3rd Qu.: 6.738 3rd Qu.: 6.552 3rd Qu.: 7.190 > Max. :14.131 Max. :13.695 Max. :14.046 Max. :13.209 > GSM219958 GSM219965 GSM219970 GSM219975 > Min. : 2.868 Min. : 3.196 Min. : 2.765 Min. : 3.061 > 1st Qu.: 4.501 1st Qu.: 4.417 1st Qu.: 4.426 1st Qu.: 4.662 > Median : 5.162 Median : 4.932 Median : 5.103 Median : 5.303 > Mean : 6.070 Mean : 6.044 Mean : 6.028 Mean : 6.039 > 3rd Qu.: 7.001 3rd Qu.: 7.196 3rd Qu.: 6.940 3rd Qu.: 6.500 > Max. :13.765 Max. :13.310 Max. :13.648 Max. :14.177 > GSM219976 GSM219977 GSM219978 GSM219980 > Min. : 3.393 Min. : 3.170 Min. : 2.694 Min. : 2.999 > 1st Qu.: 4.375 1st Qu.: 4.373 1st Qu.: 4.636 1st Qu.: 4.711 > Median : 4.894 Median : 5.021 Median : 5.185 Median : 5.316 > Mean : 6.030 Mean : 6.064 Mean : 6.035 Mean : 6.013 > 3rd Qu.: 7.049 3rd Qu.: 7.179 3rd Qu.: 6.589 3rd Qu.: 6.377 > Max. :13.042 Max. :13.413 Max. :13.906 Max. :13.930 > GSM219981 > Min. : 3.035 > 1st Qu.: 4.419 > Median : 4.998 > Mean : 6.064 > 3rd Qu.: 7.091 > Max. :13.186 > >> dim(mat at hx) > [1] 1077 49 > > >> mat at hx[1:6,] > GSM219865 GSM219869 GSM219870 GSM219872 GSM219879 GSM219880 > GSM219881 > MIRNA174 8.881515 13.19956 12.29140 13.38759 13.13721 12.91034 > 12.76761 > MIRNA174 8.881515 13.19956 12.29140 13.38759 13.13721 12.91034 > 12.76761 > MIRNA174 8.881515 13.19956 12.29140 13.38759 13.13721 12.91034 > 12.76761 > MIRNA175 10.424014 13.95789 13.07468 14.16651 13.93700 13.75428 > 13.59964 > MIRNA175 10.424014 13.95789 13.07468 14.16651 13.93700 13.75428 > 13.59964 > MIRNA175 10.424014 13.95789 13.07468 14.16651 13.93700 13.75428 > 13.59964 > GSM219882 GSM219886 GSM219887 GSM219892 GSM219894 GSM219896 > GSM219899 > MIRNA174 12.56916 12.82551 13.16155 12.43174 13.33032 12.83228 > 12.93335 > MIRNA174 12.56916 12.82551 13.16155 12.43174 13.33032 12.83228 > 12.93335 > MIRNA174 12.56916 12.82551 13.16155 12.43174 13.33032 12.83228 > 12.93335 > MIRNA175 13.37011 13.68271 13.96500 13.28058 14.19234 13.69705 > 13.76962 > MIRNA175 13.37011 13.68271 13.96500 13.28058 14.19234 13.69705 > 13.76962 > MIRNA175 13.37011 13.68271 13.96500 13.28058 14.19234 13.69705 > 13.76962 > GSM219900 GSM219902 GSM219903 GSM219905 GSM219907 GSM219909 > GSM219911 > MIRNA174 12.93294 12.84814 12.78597 12.79087 12.68306 13.49380 > 12.35723 > MIRNA174 12.93294 12.84814 12.78597 12.79087 12.68306 13.49380 > 12.35723 > MIRNA174 12.93294 12.84814 12.78597 12.79087 12.68306 13.49380 > 12.35723 > MIRNA175 13.70059 13.64676 13.57370 13.57222 13.52558 14.36265 > 13.23234 > MIRNA175 13.70059 13.64676 13.57370 13.57222 13.52558 14.36265 > 13.23234 > MIRNA175 13.70059 13.64676 13.57370 13.57222 13.52558 14.36265 > 13.23234 > GSM219912 GSM219913 GSM219918 GSM219919 GSM219920 GSM219934 > GSM219937 > MIRNA174 13.53402 12.27678 13.15308 12.54759 12.38596 12.78409 > 12.35020 > MIRNA174 13.53402 12.27678 13.15308 12.54759 12.38596 12.78409 > 12.35020 > MIRNA174 13.53402 12.27678 13.15308 12.54759 12.38596 12.78409 > 12.35020 > MIRNA175 14.39575 13.15638 13.87750 13.37227 13.13537 13.67619 > 13.36468 > MIRNA175 14.39575 13.15638 13.87750 13.37227 13.13537 13.67619 > 13.36468 > MIRNA175 14.39575 13.15638 13.87750 13.37227 13.13537 13.67619 > 13.36468 > GSM219938 GSM219939 GSM219940 GSM219943 GSM219944 GSM219945 > GSM219948 > MIRNA174 12.69961 13.04254 12.40181 12.94058 13.15582 12.61323 > 12.98207 > MIRNA174 12.69961 13.04254 12.40181 12.94058 13.15582 12.61323 > 12.98207 > MIRNA174 12.69961 13.04254 12.40181 12.94058 13.15582 12.61323 > 12.98207 > MIRNA175 13.64537 13.85869 13.28368 13.73350 13.98935 13.48931 > 13.80361 > MIRNA175 13.64537 13.85869 13.28368 13.73350 13.98935 13.48931 > 13.80361 > MIRNA175 13.64537 13.85869 13.28368 13.73350 13.98935 13.48931 > 13.80361 > GSM219950 GSM219952 GSM219953 GSM219954 GSM219955 GSM219958 > GSM219965 > MIRNA174 12.81962 13.27037 12.72672 13.10274 12.32595 12.87308 > 12.32967 > MIRNA174 12.81962 13.27037 12.72672 13.10274 12.32595 12.87308 > 12.32967 > MIRNA174 12.81962 13.27037 12.72672 13.10274 12.32595 12.87308 > 12.32967 > MIRNA175 13.68518 14.06946 13.63226 13.91247 13.19594 13.66014 > 13.18479 > MIRNA175 13.68518 14.06946 13.63226 13.91247 13.19594 13.66014 > 13.18479 > MIRNA175 13.68518 14.06946 13.63226 13.91247 13.19594 13.66014 > 13.18479 > GSM219970 GSM219975 GSM219976 GSM219977 GSM219978 GSM219980 > GSM219981 > MIRNA174 12.66376 13.28257 12.04305 12.46820 13.02737 13.00563 > 12.22126 > MIRNA174 12.66376 13.28257 12.04305 12.46820 13.02737 13.00563 > 12.22126 > MIRNA174 12.66376 13.28257 12.04305 12.46820 13.02737 13.00563 > 12.22126 > MIRNA175 13.56579 14.06224 12.95079 13.27818 13.82855 13.78838 > 13.02881 > MIRNA175 13.56579 14.06224 12.95079 13.27818 13.82855 13.78838 > 13.02881 > MIRNA175 13.56579 14.06224 12.95079 13.27818 13.82855 13.78838 > 13.02881 > > > >> sessionInfo() > R version 2.9.1 (2009-06-26) > i486-pc-linux-gnu > > locale: > LC_CTYPE=en_IE.UTF-8;LC_NUMERIC=C;LC_TIME=en_IE.UTF-8;LC_COLLATE=en_ IE.UTF-8;LC_MONETARY=C;LC_MESSAGES=en_IE.UTF-8;LC_PAPER=en_IE.UTF-8;LC _NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_IE.UTF-8;LC_IDEN TIFICATION=C > > attached base packages: > [1] stats graphics grDevices utils datasets methods base > > other attached packages: > [1] statmod_1.4.0 limma_2.18.2 vsn_3.12.0 Biobase_2.4.1 > > loaded via a namespace (and not attached): > [1] affy_1.22.0 affyio_1.12.0 grid_2.9.1 > [4] lattice_0.17-25 preprocessCore_1.6.0 > > > -- > Paul Geeleher > School of Mathematics, Statistics and Applied Mathematics > National University of Ireland > Galway > Ireland
Microarray probe Microarray probe • 1.1k views
ADD COMMENT
0
Entering edit mode
Paul Geeleher ★ 1.3k
@paul-geeleher-2679
Last seen 10.2 years ago
Yes avedups() worked fine. I presume it must be a design matrix problem. If there's something obvious maybe you could point it out for me? Otherwise I'll just use avedups(). > design (Intercept) factor(pData$population)2 1 1 1 2 1 1 3 1 1 4 1 1 5 1 0 6 1 1 7 1 1 8 1 1 9 1 1 10 1 0 11 1 1 12 1 1 13 1 1 14 1 1 15 1 1 16 1 1 17 1 0 18 1 0 19 1 1 20 1 1 21 1 1 22 1 1 23 1 0 24 1 0 25 1 1 26 1 1 27 1 0 28 1 1 29 1 1 30 1 1 31 1 0 32 1 1 33 1 1 34 1 1 35 1 1 36 1 1 37 1 0 38 1 1 39 1 1 40 1 1 41 1 1 42 1 0 43 1 0 44 1 1 45 1 0 46 1 1 47 1 1 48 1 0 49 1 1 attr(,"assign") [1] 0 1 attr(,"contrasts") attr(,"contrasts")$`factor(pData$population)` [1] "contr.treatment" > dim(mat@hx) [1] 1077 49 corfit <- duplicateCorrelation(mat@hx, design, ndups=3) On Mon, Sep 7, 2009 at 12:12 AM, Gordon K Smyth <smyth@wehi.edu.au> wrote: > Dear Paul, > > While I know what this error is, I haven't seen it arise previously in > duplicateCorrelation() with microarray data, so it is hard to give advice. > It is a numeric error in the inner optimization routine which may arise for > reasons which are hard to pin down. > > Try removing rows from the hx object, e.g., run duplicateCorrelation() on > the top half or bottom half of the spots. One or the other may run if the > problem is caused by one particular probe. > > Also check that your design matrix is appropriate, perhaps by trying it > with avedups(). > > Best wishes > Gordon > > Date: Fri, 4 Sep 2009 11:25:55 +0100 >> From: Paul Geeleher <paulgeeleher@gmail.com> >> Subject: [BioC] Duplicate correlation error in limma >> To: Bioconductor mailing list <bioconductor@stat.math.ethz.ch> >> Content-Type: text/plain >> >> Hello folks, >> >> I'm getting this error when I run duplicate correlation: >> >> corfit <- duplicateCorrelation(mat@hx, design, ndups=3, spacing=1) >> Error in glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace >> = >> trace) : >> Starting values give negative fitted values >> >> I saw a previous post on the mailing list where this error occurred >> because >> of drastically different values in the input matrix, but I don't have that >> problem so any help would be greatly appreciated. Here's some extra info: >> >> >> GSM219865 GSM219869 GSM219870 GSM219872 >> Min. : 2.788 Min. : 2.445 Min. : 3.091 Min. : 2.567 >> 1st Qu.: 4.491 1st Qu.: 4.639 1st Qu.: 4.434 1st Qu.: 4.782 >> Median : 5.252 Median : 5.305 Median : 4.945 Median : 5.450 >> Mean : 6.051 Mean : 6.030 Mean : 6.045 Mean : 6.032 >> 3rd Qu.: 7.064 3rd Qu.: 6.817 3rd Qu.: 7.231 3rd Qu.: 6.612 >> Max. :13.602 Max. :14.033 Max. :13.113 Max. :14.167 >> GSM219879 GSM219880 GSM219881 GSM219882 >> Min. : 3.201 Min. : 2.832 Min. : 3.058 Min. : 3.144 >> 1st Qu.: 4.512 1st Qu.: 4.530 1st Qu.: 4.490 1st Qu.: 4.531 >> Median : 5.095 Median : 5.049 Median : 5.124 Median : 5.029 >> Mean : 6.023 Mean : 6.028 Mean : 6.011 Mean : 6.052 >> 3rd Qu.: 6.886 3rd Qu.: 6.897 3rd Qu.: 7.087 3rd Qu.: 7.087 >> Max. :13.979 Max. :13.766 Max. :13.600 Max. :13.382 >> GSM219886 GSM219887 GSM219892 GSM219894 >> Min. : 3.236 Min. : 3.007 Min. : 3.048 Min. : 2.707 >> 1st Qu.: 4.419 1st Qu.: 4.520 1st Qu.: 4.407 1st Qu.: 4.674 >> Median : 4.971 Median : 5.146 Median : 4.968 Median : 5.290 >> Mean : 6.048 Mean : 6.061 Mean : 6.069 Mean : 6.013 >> 3rd Qu.: 7.036 3rd Qu.: 7.023 3rd Qu.: 7.237 3rd Qu.: 6.589 >> Max. :13.723 Max. :14.208 Max. :13.281 Max. :14.199 >> GSM219896 GSM219899 GSM219900 GSM219902 >> Min. : 3.137 Min. : 3.217 Min. : 2.896 Min. : 2.986 >> 1st Qu.: 4.523 1st Qu.: 4.559 1st Qu.: 4.430 1st Qu.: 4.514 >> Median : 4.960 Median : 5.163 Median : 5.074 Median : 5.090 >> Mean : 6.046 Mean : 6.026 Mean : 6.035 Mean : 6.002 >> 3rd Qu.: 7.117 3rd Qu.: 6.746 3rd Qu.: 7.074 3rd Qu.: 7.077 >> Max. :13.824 Max. :13.816 Max. :13.760 Max. :13.700 >> GSM219903 GSM219905 GSM219907 GSM219909 >> Min. : 3.014 Min. : 3.179 Min. : 3.062 Min. : 2.756 >> 1st Qu.: 4.465 1st Qu.: 4.418 1st Qu.: 4.372 1st Qu.: 4.693 >> Median : 5.027 Median : 4.998 Median : 4.885 Median : 5.386 >> Mean : 6.057 Mean : 6.045 Mean : 6.056 Mean : 6.027 >> 3rd Qu.: 7.280 3rd Qu.: 7.160 3rd Qu.: 7.175 3rd Qu.: 6.380 >> Max. :13.592 Max. :13.572 Max. :13.637 Max. :14.457 >> GSM219911 GSM219912 GSM219913 GSM219918 >> Min. : 3.048 Min. : 1.977 Min. : 2.819 Min. : 2.929 >> 1st Qu.: 4.431 1st Qu.: 4.730 1st Qu.: 4.440 1st Qu.: 4.614 >> Median : 4.857 Median : 5.303 Median : 4.956 Median : 5.192 >> Mean : 6.017 Mean : 6.013 Mean : 6.062 Mean : 6.041 >> 3rd Qu.: 7.233 3rd Qu.: 6.513 3rd Qu.: 7.362 3rd Qu.: 6.948 >> Max. :13.312 Max. :14.396 Max. :13.212 Max. :14.050 >> GSM219919 GSM219920 GSM219934 GSM219937 >> Min. : 3.227 Min. : 3.294 Min. : 2.737 Min. : 2.600 >> 1st Qu.: 4.363 1st Qu.: 4.385 1st Qu.: 4.518 1st Qu.: 4.665 >> Median : 4.991 Median : 4.869 Median : 5.110 Median : 5.318 >> Mean : 6.059 Mean : 6.041 Mean : 6.039 Mean : 6.030 >> 3rd Qu.: 7.171 3rd Qu.: 7.175 3rd Qu.: 6.915 3rd Qu.: 6.814 >> Max. :13.454 Max. :13.221 Max. :13.875 Max. :14.067 >> GSM219938 GSM219939 GSM219940 GSM219943 >> Min. : 2.946 Min. : 2.861 Min. : 3.266 Min. : 2.729 >> 1st Qu.: 4.676 1st Qu.: 4.635 1st Qu.: 4.362 1st Qu.: 4.584 >> Median : 5.354 Median : 5.226 Median : 5.048 Median : 5.123 >> Mean : 6.047 Mean : 6.034 Mean : 6.046 Mean : 6.019 >> 3rd Qu.: 6.909 3rd Qu.: 6.754 3rd Qu.: 7.249 3rd Qu.: 6.928 >> Max. :14.083 Max. :14.110 Max. :13.329 Max. :13.836 >> GSM219944 GSM219945 GSM219948 GSM219950 >> Min. : 2.724 Min. : 3.149 Min. : 2.902 Min. : 2.900 >> 1st Qu.: 4.590 1st Qu.: 4.412 1st Qu.: 4.593 1st Qu.: 4.321 >> Median : 5.289 Median : 5.076 Median : 5.172 Median : 5.114 >> Mean : 6.055 Mean : 6.078 Mean : 6.062 Mean : 6.050 >> 3rd Qu.: 6.927 3rd Qu.: 7.097 3rd Qu.: 6.843 3rd Qu.: 7.100 >> Max. :14.071 Max. :13.596 Max. :13.920 Max. :13.692 >> GSM219952 GSM219953 GSM219954 GSM219955 >> Min. : 2.986 Min. : 2.784 Min. : 2.437 Min. : 3.065 >> 1st Qu.: 4.581 1st Qu.: 4.613 1st Qu.: 4.710 1st Qu.: 4.410 >> Median : 5.221 Median : 5.179 Median : 5.293 Median : 5.094 >> Mean : 6.043 Mean : 6.042 Mean : 6.048 Mean : 6.050 >> 3rd Qu.: 6.843 3rd Qu.: 6.738 3rd Qu.: 6.552 3rd Qu.: 7.190 >> Max. :14.131 Max. :13.695 Max. :14.046 Max. :13.209 >> GSM219958 GSM219965 GSM219970 GSM219975 >> Min. : 2.868 Min. : 3.196 Min. : 2.765 Min. : 3.061 >> 1st Qu.: 4.501 1st Qu.: 4.417 1st Qu.: 4.426 1st Qu.: 4.662 >> Median : 5.162 Median : 4.932 Median : 5.103 Median : 5.303 >> Mean : 6.070 Mean : 6.044 Mean : 6.028 Mean : 6.039 >> 3rd Qu.: 7.001 3rd Qu.: 7.196 3rd Qu.: 6.940 3rd Qu.: 6.500 >> Max. :13.765 Max. :13.310 Max. :13.648 Max. :14.177 >> GSM219976 GSM219977 GSM219978 GSM219980 >> Min. : 3.393 Min. : 3.170 Min. : 2.694 Min. : 2.999 >> 1st Qu.: 4.375 1st Qu.: 4.373 1st Qu.: 4.636 1st Qu.: 4.711 >> Median : 4.894 Median : 5.021 Median : 5.185 Median : 5.316 >> Mean : 6.030 Mean : 6.064 Mean : 6.035 Mean : 6.013 >> 3rd Qu.: 7.049 3rd Qu.: 7.179 3rd Qu.: 6.589 3rd Qu.: 6.377 >> Max. :13.042 Max. :13.413 Max. :13.906 Max. :13.930 >> GSM219981 >> Min. : 3.035 >> 1st Qu.: 4.419 >> Median : 4.998 >> Mean : 6.064 >> 3rd Qu.: 7.091 >> Max. :13.186 >> >> dim(mat@hx) >>> >> [1] 1077 49 >> >> >> mat@hx[1:6,] >>> >> GSM219865 GSM219869 GSM219870 GSM219872 GSM219879 GSM219880 >> GSM219881 >> MIRNA174 8.881515 13.19956 12.29140 13.38759 13.13721 12.91034 >> 12.76761 >> MIRNA174 8.881515 13.19956 12.29140 13.38759 13.13721 12.91034 >> 12.76761 >> MIRNA174 8.881515 13.19956 12.29140 13.38759 13.13721 12.91034 >> 12.76761 >> MIRNA175 10.424014 13.95789 13.07468 14.16651 13.93700 13.75428 >> 13.59964 >> MIRNA175 10.424014 13.95789 13.07468 14.16651 13.93700 13.75428 >> 13.59964 >> MIRNA175 10.424014 13.95789 13.07468 14.16651 13.93700 13.75428 >> 13.59964 >> GSM219882 GSM219886 GSM219887 GSM219892 GSM219894 GSM219896 >> GSM219899 >> MIRNA174 12.56916 12.82551 13.16155 12.43174 13.33032 12.83228 >> 12.93335 >> MIRNA174 12.56916 12.82551 13.16155 12.43174 13.33032 12.83228 >> 12.93335 >> MIRNA174 12.56916 12.82551 13.16155 12.43174 13.33032 12.83228 >> 12.93335 >> MIRNA175 13.37011 13.68271 13.96500 13.28058 14.19234 13.69705 >> 13.76962 >> MIRNA175 13.37011 13.68271 13.96500 13.28058 14.19234 13.69705 >> 13.76962 >> MIRNA175 13.37011 13.68271 13.96500 13.28058 14.19234 13.69705 >> 13.76962 >> GSM219900 GSM219902 GSM219903 GSM219905 GSM219907 GSM219909 >> GSM219911 >> MIRNA174 12.93294 12.84814 12.78597 12.79087 12.68306 13.49380 >> 12.35723 >> MIRNA174 12.93294 12.84814 12.78597 12.79087 12.68306 13.49380 >> 12.35723 >> MIRNA174 12.93294 12.84814 12.78597 12.79087 12.68306 13.49380 >> 12.35723 >> MIRNA175 13.70059 13.64676 13.57370 13.57222 13.52558 14.36265 >> 13.23234 >> MIRNA175 13.70059 13.64676 13.57370 13.57222 13.52558 14.36265 >> 13.23234 >> MIRNA175 13.70059 13.64676 13.57370 13.57222 13.52558 14.36265 >> 13.23234 >> GSM219912 GSM219913 GSM219918 GSM219919 GSM219920 GSM219934 >> GSM219937 >> MIRNA174 13.53402 12.27678 13.15308 12.54759 12.38596 12.78409 >> 12.35020 >> MIRNA174 13.53402 12.27678 13.15308 12.54759 12.38596 12.78409 >> 12.35020 >> MIRNA174 13.53402 12.27678 13.15308 12.54759 12.38596 12.78409 >> 12.35020 >> MIRNA175 14.39575 13.15638 13.87750 13.37227 13.13537 13.67619 >> 13.36468 >> MIRNA175 14.39575 13.15638 13.87750 13.37227 13.13537 13.67619 >> 13.36468 >> MIRNA175 14.39575 13.15638 13.87750 13.37227 13.13537 13.67619 >> 13.36468 >> GSM219938 GSM219939 GSM219940 GSM219943 GSM219944 GSM219945 >> GSM219948 >> MIRNA174 12.69961 13.04254 12.40181 12.94058 13.15582 12.61323 >> 12.98207 >> MIRNA174 12.69961 13.04254 12.40181 12.94058 13.15582 12.61323 >> 12.98207 >> MIRNA174 12.69961 13.04254 12.40181 12.94058 13.15582 12.61323 >> 12.98207 >> MIRNA175 13.64537 13.85869 13.28368 13.73350 13.98935 13.48931 >> 13.80361 >> MIRNA175 13.64537 13.85869 13.28368 13.73350 13.98935 13.48931 >> 13.80361 >> MIRNA175 13.64537 13.85869 13.28368 13.73350 13.98935 13.48931 >> 13.80361 >> GSM219950 GSM219952 GSM219953 GSM219954 GSM219955 GSM219958 >> GSM219965 >> MIRNA174 12.81962 13.27037 12.72672 13.10274 12.32595 12.87308 >> 12.32967 >> MIRNA174 12.81962 13.27037 12.72672 13.10274 12.32595 12.87308 >> 12.32967 >> MIRNA174 12.81962 13.27037 12.72672 13.10274 12.32595 12.87308 >> 12.32967 >> MIRNA175 13.68518 14.06946 13.63226 13.91247 13.19594 13.66014 >> 13.18479 >> MIRNA175 13.68518 14.06946 13.63226 13.91247 13.19594 13.66014 >> 13.18479 >> MIRNA175 13.68518 14.06946 13.63226 13.91247 13.19594 13.66014 >> 13.18479 >> GSM219970 GSM219975 GSM219976 GSM219977 GSM219978 GSM219980 >> GSM219981 >> MIRNA174 12.66376 13.28257 12.04305 12.46820 13.02737 13.00563 >> 12.22126 >> MIRNA174 12.66376 13.28257 12.04305 12.46820 13.02737 13.00563 >> 12.22126 >> MIRNA174 12.66376 13.28257 12.04305 12.46820 13.02737 13.00563 >> 12.22126 >> MIRNA175 13.56579 14.06224 12.95079 13.27818 13.82855 13.78838 >> 13.02881 >> MIRNA175 13.56579 14.06224 12.95079 13.27818 13.82855 13.78838 >> 13.02881 >> MIRNA175 13.56579 14.06224 12.95079 13.27818 13.82855 13.78838 >> 13.02881 >> >> >> >> sessionInfo() >>> >> R version 2.9.1 (2009-06-26) >> i486-pc-linux-gnu >> >> locale: >> >> LC_CTYPE=en_IE.UTF-8;LC_NUMERIC=C;LC_TIME=en_IE.UTF-8;LC_COLLATE=en _IE.UTF-8;LC_MONETARY=C;LC_MESSAGES=en_IE.UTF-8;LC_PAPER=en_IE.UTF-8;L C_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_IE.UTF-8;LC_IDE NTIFICATION=C >> >> attached base packages: >> [1] stats graphics grDevices utils datasets methods base >> >> other attached packages: >> [1] statmod_1.4.0 limma_2.18.2 vsn_3.12.0 Biobase_2.4.1 >> >> loaded via a namespace (and not attached): >> [1] affy_1.22.0 affyio_1.12.0 grid_2.9.1 >> [4] lattice_0.17-25 preprocessCore_1.6.0 >> >> >> -- >> Paul Geeleher >> School of Mathematics, Statistics and Applied Mathematics >> National University of Ireland >> Galway >> Ireland >> > -- Paul Geeleher School of Mathematics, Statistics and Applied Mathematics National University of Ireland Galway Ireland [[alternative HTML version deleted]]
ADD COMMENT

Login before adding your answer.

Traffic: 871 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6