search for: biclustering

Displaying 10 results from an estimated 10 matches for "biclustering".

2010 Feb 01
0
Biclust package: drawHeatmap()
Hi, I was trying to draw a heatmap of the bicluster results. With the code given in the biclust package I can only get the heatmap for one cluster at a time (drawHeatmap function). Is there any way that I can get the heatmap for all the clusters at the same time? The code that I am using (biclust documentation) is: #Random 100x50 matrix with a single, up-regulated 10x10 bicluster
2010 Jul 12
1
Extract Clusters from Biclust Object
Dear all, I share the problem Linda Garcia and Ram Kumar Basnet described; I have a biclust object, containing several clusters. For drawing a heatmap, it is possible to specify the cluster to be plotted. However, I'd like to extract the clusters in this manner: Cond.1 Cond.2 Gene - value - value just like drawHeatmap specifies each cluster. Is there a way to extract single
2010 Sep 01
0
biclust package
Hi, I wanted to compare the quality of biclusters obtained from the various biclustering algorithms. Is there a function/metric in biclust (or some other package) that will enable me to do this? thanks! [[alternative HTML version deleted]]
2012 Nov 21
6
Scaling values 0-255 -> -1 , 1 - how can this be done?
I have a dataframe in which I have values 0-255, I wish to transpose them such that: if value > 127.5 value = 1 if value < 127.5 value = -1 I did something similar using the "binarize" function of the biclust package, this transforms my dataframe to 0 and 1 values, but I wish to use -1 and 1 and looking for a way in R to do this. Brian
2012 Nov 17
2
Using cbind to combine data frames and preserve header/names
I have a dataframe that has a header like so: class value1 value2 value3 class is a factor the actual values in the columns value1, value2 and value3 are 0-255, I wish to binarize these using biclust. I can do this like so: binarize(dataframe[,-1]) this will return a dataframe, but then I lose my first column class, so I thought I could combine it like so: dataframe <-
2008 Sep 10
1
Two way clustering
Hi R users,   I am trying to do two-way clustering (using information of both observation and variables). Is there any package available in R. Another querry, if somebody can provide related information (website) regarding this statistics, it will be great. Thanks in advance.   Regards,   Ram Kumar Basnet, Wageningen University. [[alternative HTML version deleted]]
2009 Aug 31
3
Two way joining vs heatmap
Hi STATISTICA has a function called "Two-way joining" (see http://www.statsoft.com/TEXTBOOK/stcluan.html#twotwo) and the reference material states that this is based on the method as published by Hartigan (found this paper: http://www.jstor.org/pss/2284710 through wikipedia). What is the relationship (if any) between the "heatmap" function in R and this technique? Is there an
2010 Aug 25
1
Documenting S4 Methods
I'm in the process of converting some S3 methods to S4 methods. I have this function : setGeneric("enrichmentCalc", function(rs, organism, seqLen, ...){standardGeneric("enrichmentCalc")}) setMethod("enrichmentCalc", c("GenomeDataList", "BSgenome"), function(rs, organism, seqLen, ...) { ... ... ... })
2009 Dec 13
3
CRAN (and crantastic) updates this week
CRAN (and crantastic) updates this week New packages ------------ * Bergm (1.0) Alberto Caimo http://crantastic.org/packages/Bergm Functions implementing Bayesian estimation for exponential random graph models via exchange algorithm Updated packages ---------------- lmtest (0.9-26), logcondens (1.3.5), MTSKNN (0.0-4), pmml (1.2.21), r2lUniv (0.9.4), rattle (2.5.11), rgdal (0.6-23),
2010 Feb 03
2
Installation woes for rattle (and other packages)
Yesterday I wanted to try rattle on Ubuntu 9.04 Jaunty. I had (and still have) it running (though it complains on startup a bit -- I'll look into that later) on a different bootup on the same machine with 8.04 Hardy. I got an error that libglade cannot be found, and various attempts to get glade support failed. I removed and reinstalled R -- same problem. To avoid the issue of local setup