Systematic or
common names

Last updated
July, 2011

Yeast Databases to Query

Compiled Knowledge Sources:
MIPS Functional Classification
MIPS Phenotypes
MIPS Subcellular Localization
MIPS Protein Complexes
MIPS Protein Classes
GO Molecular Function
GO Biological Process
GO Cellular Component
SMART Domains
Pfam Domains

Published Datasets
Yeast Two Hybrid - Uetz et al.
Yeast Two Hybrid - Ito et al. (core)
Yeast Two Hybrid - Ito et al. (full)
Synthetic Genetic Array - Tong et al.
MDS Proteomics Complexes - Ho et al.
Cellzome Complexes - Gavin et al.
Proteome Localization - Kumar et al. (observed)
Proteome Localization - Kumar et al. (predicted)
Essentiality and Morphology - Giaever et al.
Yeast Fitness Data - Giaever et al.

Published Complexes

Bonferroni correction? Yes No

P-value cutoff:


FunSpec (an acronym for "Functional Specification") inputs a list of yeast gene names, and outputs a summary of functional classes, cellular localizations, protein complexes, etc. that are enriched in the list. The classes and categories evaluated were downloaded from the MIPS Database and the GO Database . In addition, many published datasets have been compiled to evaluate enrichment against. Hypertext links to the publications are given.

The p-values, calculated using the hypergeometric distribution, represent the probability that the intersection of given list with any given functional category occurs by chance. The Bonferroni-correction divides the p-value threshold, that would be deemed significant for an individual test, by the number of tests conducted and thus accounts for spurious significance due to multiple testing over the categories of a database. After the Bonferroni correction, only those categories are displayed for which the chance probability of enrichment is lower than: p-value/#CD where #CD is the number of categories in the selected database. Without the Bonferroni Correction, all categories are displayed for which the same probability of enrichment is lower than: p-value threshold in an individual test

Note that many genes are contained in many categories, especially in the MIPS database (which are hierarchical) and that this can create biases for which FunSpec currently makes no compensation. Also the databases are treated as independent from one another, which is really not the case, and each is searched seperately, which may not be optimal for statistical calculations. Nonetheless, we find it useful for sifting through the results of clustering analysis, TAP pulldowns, etc.

For more information, click here.

Instructions on how to use FUNSPEC can be found here.

Funspec was created by Jorg Grigull, Naveed Mohammad and Mark Robinson. It is currently maintained by Harm van Bakel ( )