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A comprehensive approach to clustering of expressed human gene sequence: the sequence tag alignment and consensus
R T Miller1, A G Christoffels, C Gopalakrishnan
1South African National Bioinformatics Institute, Private Bag X17, Bellville 7535, University of the Western Cape, South Africa.
Genome Research
|November 24, 1999
Summary
This study integrates human expressed sequence tags (ESTs) into unified transcript indices, improving gene expression analysis and capturing genetic variations. The new STACK system offers a higher fidelity representation of the human transcriptome.
Area of Science:
- Genomics
- Bioinformatics
- Molecular Biology
Background:
- Disparate sequencing efforts yield fragmented human expressed sequence tag (EST) data.
- Existing data quality and partial nature hinder discovery of full-length cDNA and gene expression forms.
- Need for integrated analysis of expressed human genome data.
Purpose of the Study:
- To process and unify a large human EST dataset into comprehensive transcript indices.
- To develop a hierarchical system reflecting gene expression and genetic polymorphism.
- To improve the fidelity and completeness of human transcriptome representation.
Main Methods:
- Application of the STACK_PACK clustering system to dbEST release 121598.
- Processing of over 1.3 million Homo sapiens ESTs into tissue-level clusters and assemblies.
- Hierarchical indexing of alignments and cross-linking to UniGene for data browsing.
Main Results:
- Condensation of 64% of ESTs into 143,885 tissue clusters, forming 68,701 assemblies.
- 81% of input ESTs captured in STACK clusters, with improved EST consolidation compared to UniGene.
- Demonstrated lower spurious repeat content and capture of alternate splicing in STACK clusters.
Conclusions:
- The developed STACK system provides a unified and higher fidelity index of human transcript forms.
- This approach enhances the analysis of gene expression and genetic variation from EST data.
- The integrated indices facilitate a more comprehensive understanding of the human transcriptome.