Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)

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Single Nucleotide Polymorphisms Data Analysis using Improved Ant Colony Algorithm

Authors
Ming Zheng, Mugui Zhuo
Corresponding Author
Ming Zheng
Available Online March 2017.
DOI
10.2991/emcs-17.2017.233How to use a DOI?
Keywords
Single nucleotide polymorphisms; Ant colony algorithm; Data analysis; Data prediction; Optimal strategy
Abstract

Improved classical ant colony clustering algorithm (LF algorithm), applied to salt sensitive hypertension SNPs data analysis, in order to explore the high throughput SNPs statistical analysis to provide new ideas. The LF algorithm was improved, and the improved algorithm was programmed with Mat 1ab8.0 software. The cluster analysis was performed on 335 samples of salt sensitive hypertension. The LF algorithm was successfully improved and the software interface was realized. Using the new algorithm, all samples are divided into 2 categories, the first class of 169 samples, second of 166 samples of consistency test and latent class analysis results, the Kappa value is 0.93, P<0.001, and the two kinds of differences in population SNPs probability distribution statistical test, we selected 3 SNPs:rs848307, rs1739843, rs1010069, clear it plays an important role in the classification of. Conclusion: ant colony clustering algorithm has the characteristics of unique thinking, automatic calculation, easy to improve, etc. it has broad application prospects in the field of high throughput SNPs data analysis and other related fields of genomics.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)
Series
Advances in Computer Science Research
Publication Date
March 2017
ISBN
978-94-6252-335-7
ISSN
2352-538X
DOI
10.2991/emcs-17.2017.233How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Ming Zheng
AU  - Mugui Zhuo
PY  - 2017/03
DA  - 2017/03
TI  - Single Nucleotide Polymorphisms Data Analysis using Improved Ant Colony Algorithm
BT  - Proceedings of the 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017)
PB  - Atlantis Press
SP  - 1213
EP  - 1216
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcs-17.2017.233
DO  - 10.2991/emcs-17.2017.233
ID  - Zheng2017/03
ER  -