Your example is not reproducible (see the posting guide), but using example(hclust)

hc <- hclust(dist(USArrests), "ave")
plot(hc)
plot(hc, cex = 0.3)

the second has much smaller case names.

On 27/06/2013 11:12, Gitte Brinch Andersen wrote:
Hello

I have done a cluster analysis, and I would like to change the font size of my 
sample names. I have tried using cex, but this doesn't work/change anything. I 
have tried to specify it with cex.main, cex.lab, cex.axis and cex.sub, and can 
change all other names in the picture but my sample names.
I can't see what I am doing wrong.

I hope somebody can help me, and I apologize for this probably very simple 
question/mistake.

I have around 1000 rows and 50 columns, but have only included a few in my 
example.

Thank you in advance!

Kind regards

Gitte Andersen


#Read in data
data<-read.table("/Users/gban/Desktop/Heatmap/Heatmap with selected 
genes/Probes_for_heatmap_35_meth_diff_both_hypo_and_hypermeth_Gene&probenames.txt",sep="\t",dec=",",header=TRUE,row.names=1)

data
                                   OS_Tumor1_08_14985_2_3 OS_Tumor2_08_226869_1
CHST3_cg04268405_1                            0.95038060            0.76433753
DLX5_cg19962750_2                             0.93111825            0.75384523
ZIC4_cg12892506_3                             0.86033747            0.69614933
DLX5_cg05597836_4                             0.90698171            0.66414891



#Turn the data into a matrix, and transpose to get the columns to be clustered
Data_matrix<-as.matrix(t(data))

Data_matrix
                             CHST3_cg04268405_1 DLX5_cg19962750_2
OS_Tumor1_08_14985_2_3               0.9503806         0.9311183
OS_Tumor2_08_226869_1                0.7643375         0.7538452
OS_Tumor3_10_201917_2_3              0.7109182         0.7778035
OS_Tumor4_00_2395                    0.7772400         0.6769241
OS_Tumor5_02_2669                    0.9638739         0.9023436
OS_Tumor6_02_4738                    0.9028490         0.9586764
OS_Tumor7_02_4850                    0.8786524         0.8872261
OS_Tumor8_02_6935                    0.8434550         0.7180251
OS_Tumor9_03_1430                    0.7494400         0.9190213
OS_Tumor10_03_1701                   0.9148253         0.7692125
OS_Tumor11_03_220                    0.9270112         0.8607459
OS_Tumor12_03_2558                   0.9344832         0.5013390
OS_Tumor13_03_373                    0.9549153         0.9559071
OS_Tumor14_03_82                     0.9117558         0.3993953
OS_Tumor15_06_22319                  0.9580999         0.9645215
OS_Tumor16_07_16581                  0.6213243         0.9033265
OS_Tumor17_07_28523                  0.9064597         0.4421651
OS_Tumor18_07_3212                   0.6439032         0.4344106
OS_Tumor19_07_6990                   0.9350585         0.9238712
OS_Tumor20_07_6990sample2            0.9526839         0.9027684
OS_Tumor21_07_7724                   0.9338156         0.8335415
OS_Tumor22_08_10238                  0.9028336         0.8529122
OS_Tumor23_08_14985Sample2           0.9609952         0.9478541
OS_Tumor24_08_16592                  0.9168102         0.9138002
OS_Tumor25_08_21197                  0.9148711         0.9109843
OS_Tumor26_08_21197Sample2           0.9583610         0.8830407
OS_Tumor27_08_222863                 0.9478853         0.8395278
OS_Tumor28_08_225814                 0.9451414         0.9407933
OS_Tumor29_08_226869Sample2          0.9028336         0.8337000
OS_Tumor30_08_230660                 0.9599117         0.9363075
OS_Tumor31_08_4485                   0.8247909         0.8336728
OS_Tumor32_09_214654                 0.9531564         0.8957473
OS_Tumor33_09_214654Sample2          0.9552210         0.9034464
OS_Tumor34_10_200150                 0.9332627         0.8551589
OS_Tumor35_10_201917                 0.9397219         0.9470733
OS_Tumor36_10_201917Sample2          0.9607446         0.9523402
OS_Tumor37_10_202221                 0.9264254         0.9413189
OS_Tumor38_10_204294                 0.8388658         0.8956207
OS_Tumor39_10_204294Sample2          0.8071109         0.8474199
OS_Tumor40_10_205933                 0.8788835         0.4950936
OS_Tumor41_10_225662                 0.9334545         0.8910134
OS_Tumor42_10_229129                 0.5872184         0.8394597
OS_Tumor43_11_236261                 0.9015548         0.9293858
OS_Tumor44_12_211561                 0.6793692         0.1856015
Normalbone.3.                        0.1636323         0.1222070
Normalbone.UA.                       0.1934500         0.1303734
Normalbone.UA2.                      0.1737224         0.1604758
CRL_11372                            0.9779593         0.2533844
CRL_1427                             0.9598825         0.8862426
CRL_1543                             0.9283976         0.7198934
CRL_2098                             0.9325895         0.6360936
Ho_f.4610                            0.9370865         0.6279557
HTB_85                               0.9441092         0.1037401
HTB_96                               0.9511175         0.9160013
                             ZIC4_cg12892506_3 DLX5_cg05597836_4
OS_Tumor1_08_14985_2_3             0.86033747        0.90698171
OS_Tumor2_08_226869_1              0.69614933        0.66414891
OS_Tumor3_10_201917_2_3            0.58728927        0.65086446
OS_Tumor4_00_2395                  0.41747130        0.45464648
OS_Tumor5_02_2669                  0.74259213        0.88244165
OS_Tumor6_02_4738                  0.79690018        0.93691928
OS_Tumor7_02_4850                  0.05513471        0.91753824
OS_Tumor8_02_6935                  0.70742299        0.77802530
OS_Tumor9_03_1430                  0.84563086        0.87202952
OS_Tumor10_03_1701                 0.81318017        0.72446802
OS_Tumor11_03_220                  0.72489087        0.80580733
OS_Tumor12_03_2558                 0.06656780        0.14739011
OS_Tumor13_03_373                  0.94011867        0.95742989
OS_Tumor14_03_82                   0.52129769        0.54734874
OS_Tumor15_06_22319                0.93025191        0.94392535
OS_Tumor16_07_16581                0.67236887        0.88546907
OS_Tumor17_07_28523                0.25764851        0.45550666
OS_Tumor18_07_3212                 0.33624514        0.18623351
OS_Tumor19_07_6990                 0.82904776        0.88946081
OS_Tumor20_07_6990sample2          0.76836030        0.82519665
OS_Tumor21_07_7724                 0.90314315        0.71810973
OS_Tumor22_08_10238                0.83715782        0.86426252
OS_Tumor23_08_14985Sample2         0.82588214        0.90655043
OS_Tumor24_08_16592                0.77582828        0.83500490
OS_Tumor25_08_21197                0.90274785        0.96119490
OS_Tumor26_08_21197Sample2         0.87385578        0.83341529
OS_Tumor27_08_222863               0.72588195        0.59849569
OS_Tumor28_08_225814               0.87931232        0.89657489
OS_Tumor29_08_226869Sample2        0.86379063        0.88825605
OS_Tumor30_08_230660               0.92495563        0.95137547
OS_Tumor31_08_4485                 0.84465179        0.66948504
OS_Tumor32_09_214654               0.92036441        0.71915709
OS_Tumor33_09_214654Sample2        0.93955431        0.46490552
OS_Tumor34_10_200150               0.80337813        0.82519665
OS_Tumor35_10_201917               0.87734686        0.91265824
OS_Tumor36_10_201917Sample2        0.93627004        0.94319232
OS_Tumor37_10_202221               0.93107776        0.96075927
OS_Tumor38_10_204294               0.85892154        0.94595920
OS_Tumor39_10_204294Sample2        0.69839075        0.76396555
OS_Tumor40_10_205933               0.25850129        0.43418918
OS_Tumor41_10_225662               0.71442683        0.88154146
OS_Tumor42_10_229129               0.42328977        0.77763541
OS_Tumor43_11_236261               0.82946721        0.87242385
OS_Tumor44_12_211561               0.84785994        0.12366988
Normalbone.3.                      0.06840225        0.08229536
Normalbone.UA.                     0.07383344        0.12502117
Normalbone.UA2.                    0.07741817        0.09563505
CRL_11372                          0.05409689        0.13815797
CRL_1427                           0.91730069        0.92421230
CRL_1543                           0.77789918        0.94650563
CRL_2098                           0.91524115        0.50725942
Ho_f.4610                          0.05736418        0.51843963
HTB_85                             0.95464468        0.05260867
HTB_96                             0.88410529        0.92872206


#Calculate the distance
Data_dist<-dist(Data_matrix)

#Make the cluster
Data_clust<-hclust(Data_dist,method="ward")

#Save the plot as a pdf file
pdf(file="Cluster_Probes_From_genes_morethan_2_probes_and_morethan_30_methdiff.pdf")

#Plot the cluster
plot(Data_clust, cex=0.5)

dev.off() #Ends the pdf saving.

Gitte Brinch Andersen

Kandidat-Ph.d. studerende
Biomedicinsk Institut
Wilhelm Meyers Allé 4
Aarhus Universitet
DK-8000 Aarhus C

Mobil: +45 30433317
E-mail: gitt...@hum-gen.au.dk<mailto:gitt...@hum-gen.au.dk>



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--
Brian D. Ripley,                  rip...@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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and provide commented, minimal, self-contained, reproducible code.

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