4 Applications of DNA Sequencing Data Analysis
DNA sequencing data analysis is of vital importance for multiple
reasons [9–12]; one strong point is it can be applied in multiple
conditions:- Obtaining information encoded in gene.
We can compare sequences, predict the sequence of promoters
and enhancers, and identify the order of amino acids in certain
proteins. - Discovering new genes.
We can discover new genes by analyzing EST (expressed
sequence tag) sequences and using DNA chip technology. - Analyzing gene polymorphism.
We can analyze gene polymorphism, especially SNP (single-
nucleotide polymorphism) to identify and locate functional
genes, which can be targets of human evolution or diseases. - Predicting advanced structures.
We can use the information of the primary structure to predict
advanced structures of nucleic acids and proteins, thus predict-
ing their functions. - Achieving personalized medicine.
With the soaring need for personalized medicine, health-care
providers are capable of using DNA sequencing data to give
medical suggestions to patients.
Besides all these applications above, next-generation sequenc-
ing data analysis distinguishes itself in the following aspects:- Sequence the whole genomes rapidly and can zoom in to
deeply sequence target regions. - Analyze genome-wide methylation or DNA-protein
interactions. - Help researchers to dig into microbial diversity in humans or in
the environment.
Although using computers for data analysis has obvious advan-
tages, there still exist weaknesses:- Processing DNA sequencing data requires time and experience.
- Although results are illustrated by those tools, researchers are
supposed to analyze DNA sequencing results, to see whether
the outcome is reasonable, and to plan future experiments. - We cannot depend on computer analysis totally; the software
also make mistakes.
12 Keyi Long et al.