ANALIZA SEKVENCI MIKROBIOMA KROZ MOTHUR TOK OBRADA
Ključne reči:
16S rRNK, klasifikacija, mikrobiom, Mothur
Apstrakt
U ovom radu analizirane su 16S rRNK sekvence mikrobioma kroz Mothur tok obrada radi naknadne klasifikacije uzoraka na osnovu utvrđenog taksonomskog sastava. Klasifikacija je vršena random forest algoritmom i postignuta je tačnost od 95,46%. Nakon prikaza i diskusije rezultata, rezultati su upoređeni sa prethodnim istraživanjima nad istim podacima.
Reference
[1] J. Qin, et al., "A human gut microbial gene catalogue established by metagenomic sequencing," nature, 464.7285: 59, 2010.
[2] P. D. Schloss, et al. "Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities", Applied and environmental microbiology 75.23, p.7537-7541, 2009.
[3] https://www.arb-silva.de/documentation/release-132/ (pristupljeno u septembru 2018.)
[4] J. G. Caporaso, C. L. Lauber, E. K. Costello, D. Berg-Lyons, A. Gonzalez, J. Stombaugh, D. Knights, P. Gajer, J. Ravel, N. Fierer et al., "Moving pictures of the human microbiome," Genome Biol, vol. 12, no. 5, 2011.
[5] http://qiime.org/ (pristupljeno u septembru 2018.)
[6] E. Plummer, et al., "A comparison of three bioinformatics pipelines for the analysis of preterm gut microbiota using 16S rRNA gene sequencing data," Journal of Proteomics & Bioinformatics, 8.12: 283, 2015.
[7] http://greengenes.secondgenome.com/ (pristupljeno u oktobru 2018.)
[8] T. K. Ho, "Random decision forests," Document analysis and recognition, proceedings of the third international conference on. vol. 1. IEEE, 1995.
[9] G. James, et al., "An introduction to statistical learning, " New York: springer, 2013.
[10] D. Pavlović, "Stabilna procena klastera konsenzus klasterovanjem uzoraka mikrobioma", Diplomski rad, Fakultet tehničkih nauka, Novi Sad, 2017.
[11] S. Brdar, T. Lončar-Turukalo, V. Crnojević, B. Stres, "Clustering and classification of human microbiome data: evaluating impact of different settings in bioinformatics workflows," Book of Abstracts of the second Belgrade BioInformatics Conference – BelBi 2018, in Biologia Serbica, vol. 40, No1, 2018, pp. 67 Belgrade, June, 18-22, 2018.
[2] P. D. Schloss, et al. "Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities", Applied and environmental microbiology 75.23, p.7537-7541, 2009.
[3] https://www.arb-silva.de/documentation/release-132/ (pristupljeno u septembru 2018.)
[4] J. G. Caporaso, C. L. Lauber, E. K. Costello, D. Berg-Lyons, A. Gonzalez, J. Stombaugh, D. Knights, P. Gajer, J. Ravel, N. Fierer et al., "Moving pictures of the human microbiome," Genome Biol, vol. 12, no. 5, 2011.
[5] http://qiime.org/ (pristupljeno u septembru 2018.)
[6] E. Plummer, et al., "A comparison of three bioinformatics pipelines for the analysis of preterm gut microbiota using 16S rRNA gene sequencing data," Journal of Proteomics & Bioinformatics, 8.12: 283, 2015.
[7] http://greengenes.secondgenome.com/ (pristupljeno u oktobru 2018.)
[8] T. K. Ho, "Random decision forests," Document analysis and recognition, proceedings of the third international conference on. vol. 1. IEEE, 1995.
[9] G. James, et al., "An introduction to statistical learning, " New York: springer, 2013.
[10] D. Pavlović, "Stabilna procena klastera konsenzus klasterovanjem uzoraka mikrobioma", Diplomski rad, Fakultet tehničkih nauka, Novi Sad, 2017.
[11] S. Brdar, T. Lončar-Turukalo, V. Crnojević, B. Stres, "Clustering and classification of human microbiome data: evaluating impact of different settings in bioinformatics workflows," Book of Abstracts of the second Belgrade BioInformatics Conference – BelBi 2018, in Biologia Serbica, vol. 40, No1, 2018, pp. 67 Belgrade, June, 18-22, 2018.
Objavljeno
2019-05-22
Sekcija
Elektrotehničko i računarsko inženjerstvo
