Transcript Final Project - Computer Science

Yeast Dataset Analysis
Hongli Li
91.580 Final Project
Computer Science Department
UMASS Lowell
Outline
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Gene Ontology Annotation
Data Preprocessing
Cluster
Results
Conclusion
GO Annotations
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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
GO Annotation
GO Anotation
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Of 327 genes with GO at level 3
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170 Genes belong to GO:0008152, the metabolism
90 Genes belong to the GO:0007049 the Cell
Cycle
81 Genes belong to GO:0016043, the cell
organization and biogenesis
51 Genes belong to GO:0006810, the transport
Data Preprocessing
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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)
Cluster
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SOTA – Self-Organizing Tree Algorithm
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Euclidean Distance
Variability Threshold: 80%
Result
Cluster 61
Cluster 61
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67 Genes from 799 fall in Cluster 61
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24 out of 67 genes has GO
10 out of 24 genes belongs to metabolism
14 belongs to Cell Cycle
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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
Cluster 60
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33 Genes in this Cluster
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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
Cluster 59
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38 genes in this cluster
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15 genes has anotation
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7 in metabolism
5 in cell cycle
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M phase of mitotic cell cycle has 3
Nuclear division has 3
No gene in these two classes are same
Conclusion & Future Work
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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
Reference
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http://gepas.bioinfo.cnio.es/index.html
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.
Raymond J Cho. A Genome-Wide Transcriptional Analysis of the Mitotic
Cell Cycle. Mol. Biol. Cell., vol. 2, pp. 65--73, 1998.
Herrero, J., Valencia et al. A hierarchical unsupervised growing neural
network for clustering gene expression patterns. Bioinformatics, 17(2),
126-136. 2001
Orly Alter. Singular value decomposition for genome-wide expression
data processing and modeling. PNS, vol. 97, pp 10101-10106. 2000
http://www.cellsalive.com/cell_cycle.htm
http://www.geneontology.org/
http://fatigo.bioinfo.cnio.es/htdocs/helpFatiGO.html