Databases
StackOverflow2013
Postsdbo
POClustering and heatmap in R
 

Note that there are some explanatory texts on larger screens.

plurals
  1. POClustering and heatmap in R
    primarykey
    data
    text
    <p>I am a newbie to R and I am trying to do some clustering on a data table where rows represent individual objects and columns represent the features that have been measured for these objects. I've worked through some clustering tutorials and I do get some output, however, the heatmap that I get after clustering does not correspond at all to the heatmap produced from the same data table with another programme. While the heatmap of that programme does indicate clear differences in marker expression between the objects, my heatmap doesn't show much differences and I cannot recognize any clustering (i.e., colour) pattern on the heatmap, it just seems to be a randomly jumbled set of colours that are close to each other (no big contrast). Here is an example of the code I am using, maybe someone has an idea on what I might be doing wrong.</p> <pre><code>mydata &lt;- read.table("mydata.csv") datamat &lt;- as.matrix(mydata) datalog &lt;- log(datamat) </code></pre> <p>I am using log values for the clustering because I know that the other programme does so, too</p> <pre><code>library(gplots) hr &lt;- hclust(as.dist(1-cor(t(datalog), method="pearson")), method="complete") mycl &lt;- cutree(hr, k=7) mycol &lt;- sample(rainbow(256)); mycol &lt;- mycol[as.vector(mycl)] heatmap(datamat, Rowv=as.dendrogram(hr), Colv=NA, col=colorpanel(40, "black","yellow","green"), scale="column", RowSideColors=mycol) </code></pre> <p>Again, I plot the original colours but use the log-clusters because I know that this is what the other programme does.</p> <p>I tried to play around with the methods, but I don't get anything that would at least somehow look like a clustered heatmap. When I take out the scaling, the heatmap becomes extremely dark (and I am actually quite sure that I have somehow to scale or normalize the data by column). I also tried to cluster with k-means, but again, this didn't help. My idea was that the colour scale might not be used completely because of two outliers, but although removing them slightly increased the range of colours plotted on the heatmap, this still did not reveal proper clusters.</p> <p>Is there anything else I could play around with?</p> <p>And is it possible to change the colour scale with heatmap so that outliers are found in the last bin that has a range of "everything greater than a particular value"? I tried to do this with heatmap.2 (argument "breaks"), but I didn't quite succeed and also I didn't manage to put the row side colours that I use with the heatmap function.</p>
    singulars
    1. PO
      singulars
      1. PTAnswer
    1. This table or related slice is empty.
    1. PTQuestion
    1. This table or related slice is empty.
    1. USAnjaM
    plurals
    1. PL
      singulars
      1. LTLinked
    1. This table or related slice is empty.
    1. This table or related slice is empty.
    1. PO
      singulars
      1. PTAnswer
    1. VO
      singulars
      1. POClustering and heatmap in R
      1. This table or related slice is empty.
      1. VTUpMod
    2. VO
      singulars
      1. POClustering and heatmap in R
      1. This table or related slice is empty.
      1. VTUpMod
    1. COA tutorial on heat map creation using ggplot2 is available at [http://learnr.wordpress.com/2010/01/26/ggplot2-quick-heatmap-plotting/]
      singulars
      1. POClustering and heatmap in R
      1. USEtienne Low-Décarie
    2. COA tutorial on cluster analysis in R is available at [http://www.statmethods.net/advstats/cluster.html]
      singulars
      1. POClustering and heatmap in R
      1. USEtienne Low-Décarie
    3. CO@EtienneLow-Décarie: Thanks, I did go through these tutorials as well as through the tutorial of Thomas Girke before, but it didn't help me to identify the problem. In fact, I've been trying to find a solution for the whole week now using a number of websites and tutorials. I would be greatful if you could give me a hint on which particular detail I might have overlooked due to which the clustering doesn't work properly.
      singulars
      1. POClustering and heatmap in R
      1. USAnjaM
 

Querying!

 
Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

SQuiL has stopped working due to an internal error.

If you are curious you may find further information in the browser console, which is accessible through the devtools (F12).

Reload