Hi all,
Who would like to have a meeting next Monday?
I would like to present, demonstrate and get opinions on a R package I have developed over the past week (called anovaGO for the time being, but may change if it moves on to publication). Also, I would like to present it at the VIBE meeting in Carlow on the 5th of May, and the OpenSeq group is a very good place to train myself for that sort of meetings.
In a sentence, the package identifies GO terms enriched in genes clustering best samples according to a given factor (e.g. "Treatment").
A lot like many pathway analyses tools out there, except for the added value of built-in heatmap, hierarchical clustering, and gene expression profile visualisation functions, once the GO terms and genes of interest
The current release only support RNA-seq data, but I just finished writing some unrelease code that support microarray data too.
Cheers
Kevin
Some additional remarks:
- log2cpm a sample-by-gene matrix providing the expression level of each gene (rows; ensembl gene identifiers expected) in each sample (columns). In this example, we consider log2-transformed counts per million data obtained from RNA-sequencing after normalisation by the library size and filtering of lowly expressed genes (e.g. edgeR)
- targets an AnnotatedDataFrame (from the Biobase package) providing phenotypic information about the samples. Row names are samples, column names must include at least one factor (in the R meaning) with two or more levels (in the R meaning). Additional factors and phenotypic traits can be present in other columns and used later to re-label the samples in the heatmap and hierarchical clustering plots. In this example, we assume the presence of a column named "Treatment" which has three levels (e.g. "Control", "Low", and "High"), another column named "Timepoint" which has four levels (e.g. "2", "6", "24", and "48" as numeric values), and one last column named "Animal" with 10 levels (e.g. "A1", "A2", ..., "A10").
The package also comes with vignettes documenting the API.
Cheers