Yeast Dataset Analysis

1
Yeast Dataset Analysis

• Hongli Li
• 91.580 Final Project
• Computer Science Department
• UMASS Lowell

2
Outline

• Gene Ontology Annotation
• Data Preprocessing
• Cluster
• Results
• Conclusion

3
GO Annotations

• Total Number of Gene 799
• 327 Gene has GO at level 3 of Biological Process
• Genes with GO but not at level 3 272
• Genes without GO 200

4
GO Annotation
5
GO Anotation

• Of 327 genes with GO at level 3
• 170 Genes belong to GO0008152, the metabolism
• 90 Genes belong to the GO0007049 the Cell Cycle
• 81 Genes belong to GO0016043, the cell
  organization and biogenesis
• 51 Genes belong to GO0006810, the transport

6
Data Preprocessing

• Dataset 799 Cell Cycle Regulated Genes
• Filter Minimum Exiting value over 85
• Impute Missing Values Using KNN
• Standardize Patterns (mean 0 and standard
  deviation 1)

7
Cluster

• SOTA Self-Organizing Tree Algorithm
• Euclidean Distance
• Variability Threshold 80

8
Result
9
Cluster 61

• 67 Genes from 799 fall in Cluster 61
• 24 out of 67 genes has GO
• 10 out of 24 genes belongs to metabolism
• 14 belongs to Cell Cycle
• 8 belongs to S phase of mitotic cell cycle
• 8 belongs to DNA replication
• 4 belongs to G1/S transition of mitotic cell
  cycle
• Only one genes that belongs to metabolism not in
  cell cycles

10
Cluster 60

• 33 Genes in this Cluster
• 11 of 33 has GO
• 4 of 11 genes are in M-phase specific
  microtubule process which belongs to Cell Cycle
• 7 in organelle organization and biogenesis which
  belongs to cell growth and/or maintenance
• totally 8 in cell cycle

11
Cluster 59

• 38 genes in this cluster
• 15 genes has anotation
• 7 in metabolism  
• 5 in cell cycle
• M phase of mitotic cell cycle has 3
• Nuclear division has 3
• No gene in these two classes are same

12
Conclusion Future Work

• Cluster 61 has strong relations with cell cycle,
  next is cluster 60 and 59
• Sub-Cluster the cluster 59, 60, 61
• Analyze the gene expression data of those genes
  that are known belongs to GO cell cycle
  annotations
• Analyze other clusters
• Do the same analyze to 6000 gene dataset

13
Reference

1. http//gepas.bioinfo.cnio.es/index.html
2. P. T. Spellman et al., Comprehensive
   identification of cell cycleregulated genes of
   the yeast Saccharomyces cerevisiae by microarray
   hybridization Mol. Biol. Cell., vol. 9, pp.
   3273--3297, 1998.
3. Raymond J Cho. A Genome-Wide Transcriptional
   Analysis of the Mitotic Cell Cycle. Mol. Biol.
   Cell., vol. 2, pp. 65--73, 1998.
4. Herrero, J., Valencia et al. A hierarchical
   unsupervised growing neural network for
   clustering gene expression patterns.
   Bioinformatics, 17(2), 126-136. 2001
5. Orly Alter. Singular value decomposition for
   genome-wide expression data processing and
   modeling. PNS, vol. 97, pp 10101-10106. 2000
6. http//www.cellsalive.com/cell_cycle.htm
7. http//www.geneontology.org/
8. http//fatigo.bioinfo.cnio.es/htdocs/helpFatiGO.ht
   ml