Thank you all for your replies. I have tried transposing my data and before but I did not mention it because I was getting the same error. In the present case though it worked because I put >lm1=lm(*norm~*.,data=t(data)) instead of >lm1=lm(*fm1*, data=t(data)) where *fm1=norm~cols...* I actually didn't know that there exists such a difference between norm~cols and norm~. I wonder why...
Thank you all again! Best, Eleni On Mon, Oct 26, 2009 at 12:24 PM, Petr PIKAL <petr.pi...@precheza.cz> wrote: > Hi > > > r-help-boun...@r-project.org napsal dne 26.10.2009 10:48:51: > > > Dear list, > > > > I have been searching for a week to fit a simple linear model to my > data. I > > have looked into the previous posts but I haven't found anything > relevant to > > my problem. I guess it is something simple...I just cannot see it. > > I have the following data frame, named "data", which is a subset of a > > microarray experiment. The columns are the samples and the rows are the > > probes. I binded the first line, called "norm", which represents the > > estimated output. I want to create a linear model which shows the > > relationship between the gene expressions (rows) and the output (norm). > > > > *data* > > GSM276723.CEL GSM276724.CEL GSM276725.CEL GSM276726.CEL > > norm 0.897000 0.590000 0.683000 0.949000 > > 206427_s_at 5.387205 6.036506 8.824783 10.864122 > > 205338_s_at 6.454779 13.143095 6.123212 12.726562 > > 209848_s_at 6.703062 7.783330 12.175654 9.339651 > > 205694_at 5.894131 5.794516 12.876555 11.534664 > > 201909_at 12.616538 12.913255 12.275182 12.767743 > > 208894_at 13.049286 9.317874 12.873516 13.527182 > > 216512_s_at 6.324789 12.783791 6.216932 12.013404 > > 205337_at 6.175940 12.158796 6.117519 12.041078 > > 201850_at 6.633013 6.465900 6.535434 7.749985 > > 210982_s_at 12.444791 8.597388 12.197696 12.963449 > > GSM276727.CEL GSM276728.CEL GSM276729.CEL GSM276731.CEL > > norm 0.302000 0.597000 0.270000 0.530000 > > 206427_s_at 5.690357 8.014055 13.034753 5.493977 > > 205338_s_at 5.757048 7.706341 13.258410 5.562588 > > 209848_s_at 6.461028 7.036515 13.633649 5.874098 > > 205694_at 5.519552 5.297107 6.498811 5.146150 > > 201909_at 12.814454 11.592632 6.594229 6.650796 > > 208894_at 13.835359 13.028096 5.839909 6.045578 > > 216512_s_at 6.033096 7.273650 12.669054 5.946932 > > 205337_at 5.879028 7.381713 12.633829 5.379559 > > 201850_at 9.684397 6.560014 8.523229 6.573052 > > 210982_s_at 13.342729 12.470517 5.903681 5.658115 > > GSM276732.CEL GSM276735.CEL GSM276736.CEL GSM276737.CEL > > norm 0.43400 0.647000 0.113000 1.000000 > > 206427_s_at 12.80257 5.645002 6.519554 13.572480 > > 205338_s_at 13.38057 5.804107 11.090690 14.024922 > > 209848_s_at 13.27718 6.490851 9.784199 14.101162 > > 205694_at 11.37717 5.802105 7.944963 14.060492 > > 201909_at 13.24126 12.263899 12.578315 6.443491 > > 208894_at 12.29916 7.563361 9.971493 7.094214 > > 216512_s_at 13.00303 5.905789 10.512761 13.647573 > > 205337_at 12.63560 5.430138 10.707242 13.020312 > > 201850_at 12.71874 6.275480 6.987962 12.354580 > > 210982_s_at 11.53559 7.225199 9.322706 6.617615 > > GSM276738.CEL GSM276739.CEL GSM276740.CEL GSM276742.CEL > > norm 0.35700 0.967000 0.823000 1.000000 > > 206427_s_at 13.33764 13.607918 13.190551 12.387189 > > 205338_s_at 13.65492 12.812950 12.237476 12.912605 > > 209848_s_at 13.48525 13.435389 13.851347 12.540495 > > 205694_at 7.70928 10.045331 13.391456 11.103841 > > 201909_at 12.47093 11.937344 6.631023 7.160071 > > 208894_at 12.20508 8.892181 6.478889 5.927860 > > 216512_s_at 13.42313 12.151691 11.620552 12.341763 > > 205337_at 12.67544 12.036528 11.641203 12.275845 > > 201850_at 11.85481 13.172666 12.964316 12.156142 > > 210982_s_at 11.49940 8.380404 6.121762 5.921634 > > GSM276743.CEL GSM276744.CEL GSM276745.CEL GSM276747.CEL > > norm 0.899000 0.927000 0.754000 0.437000 > > 206427_s_at 12.665097 12.604673 11.446630 13.000295 > > 205338_s_at 13.261141 12.448096 13.185698 12.510952 > > 209848_s_at 13.396711 13.882529 13.040600 12.984137 > > 205694_at 10.888474 7.094063 8.630120 12.321685 > > 201909_at 12.100560 6.666787 12.330600 6.572282 > > 208894_at 7.741437 8.348155 10.106442 6.009902 > > 216512_s_at 12.830373 11.504074 12.300163 11.525958 > > 205337_at 12.264569 11.676281 11.940917 11.618351 > > 201850_at 11.055564 12.202366 7.327056 12.853055 > > 210982_s_at 7.285289 8.129298 9.577032 5.924993 > > GSM276748.CEL GSM276752.CEL GSM276754.CEL GSM276756.CEL > > norm 0.321000 0.620000 0.155000 0.946000 > > 206427_s_at 9.081283 11.446978 8.191261 13.192507 > > 205338_s_at 13.737773 13.698520 12.983830 10.948681 > > 209848_s_at 13.234025 12.956672 10.644642 13.176656 > > 205694_at 7.953865 7.397013 7.170732 13.618932 > > 201909_at 12.533684 7.049442 6.804030 7.135974 > > 208894_at 11.868729 8.558455 6.629858 6.850639 > > 216512_s_at 13.589290 12.781853 12.060414 10.143297 > > 205337_at 13.084386 12.442617 12.104849 10.364035 > > 201850_at 6.615453 8.104145 7.058739 6.514298 > > 210982_s_at 11.058085 7.891520 6.516261 6.532226 > > GSM276758.CEL GSM276759.CEL > > norm 0.767000 0.218000 > > 206427_s_at 5.742074 11.232337 > > 205338_s_at 6.375289 13.406557 > > 209848_s_at 6.226996 6.835458 > > 205694_at 5.864042 11.218719 > > 201909_at 6.907489 7.316435 > > 208894_at 12.596987 12.408412 > > 216512_s_at 6.308256 12.318892 > > 205337_at 6.063775 12.389912 > > 201850_at 6.816491 6.602764 > > 210982_s_at 11.985288 11.853911 > > > > *What I did is the following:* > > >fm1=as.formula((norm) ~ "206427_s_at" + "205338_s_at" + "209848_s_at" + > > "205694_at" + "201909_at" + "208894_at" + "216512_s_at" + "205337_at" + > > "201850_at" + "210982_s_at") > > >lm1=lm(fm1,data1new) > > > > And I receive the following error: > > Error in terms.formula(formula, data = data) : > > invalid model formula in ExtractVars > > > > > > *I have also tried:* > > >cols=rownames(data3) %%%%Where data3 is the same data frame with data > > above, but without the "norm" row binded yet > > thus: > cols > > [1] "206427_s_at" "205338_s_at" "209848_s_at" "205694_at" "201909_at" > > [6] "208894_at" "216512_s_at" "205337_at" "201850_at" "210982_s_at" > > > > > lm1=lm(fm1,data1new) > > > > and in this case Ireceive the following error: > > Error in model.frame.default(formula = fm1, data = data1new, > > drop.unused.levels = TRUE) : > > variable lengths differ (found for 'cols') > > > > Could anyone help me with this? > > Usual expectation is that data are arranged columnwise. Each column is a > variable and each row is an observation. So you shall transform your data > to this form e.g. by > > t(yourdata). > > Other issue can be if your data are really numeric what you can test by > > str(yourdata) > > which shall show a structure of your data. > If everything is OK than > > lm(norm ~ . , data = data1new) shall produce linear model of norm on all > other columns in data frame data1new) > > Regards > Petr > > > > > Thank you very much in advance, > > Eleni > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.