TY - GEN
T1 - Metagenomic clustering in search of common origin
AU - Kawulok, Jolanta
AU - Kawulok, Michal
N1 - Publisher Copyright:
Copyright © 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
PY - 2020
Y1 - 2020
N2 - Analysis of metagenomic samples is aimed at extracting relevant information on these samples, including their composition and origin. To determine where a sample comes from, it is commonly compared with a set of reference samples extracted from known locations. However, if such reference samples are unavailable or when the origins of the investigated samples are not covered by the reference set, it may be helpful to identify groups of similar samples that may have a common origin. In this paper, we tackle this problem with hierarchical clustering applied to analyse a matrix of mutual similarities obtained using the Mash and our CoMeta programs. We report initial, yet encouraging results of our experimental study performed for the metagenomic data extracted from two large metropolises, downloaded from the Sequence Read Archive repository. The obtained results indicate that the proposed approach is effective, which justifies further exploration of the topic using more extensive data.
AB - Analysis of metagenomic samples is aimed at extracting relevant information on these samples, including their composition and origin. To determine where a sample comes from, it is commonly compared with a set of reference samples extracted from known locations. However, if such reference samples are unavailable or when the origins of the investigated samples are not covered by the reference set, it may be helpful to identify groups of similar samples that may have a common origin. In this paper, we tackle this problem with hierarchical clustering applied to analyse a matrix of mutual similarities obtained using the Mash and our CoMeta programs. We report initial, yet encouraging results of our experimental study performed for the metagenomic data extracted from two large metropolises, downloaded from the Sequence Read Archive repository. The obtained results indicate that the proposed approach is effective, which justifies further exploration of the topic using more extensive data.
KW - Hierarchical Clustering
KW - K-mers
KW - Metagenome
KW - Metagenomic Reads
KW - Urban Microbiome
UR - https://www.scopus.com/pages/publications/85083570874
U2 - 10.5220/0009177700002513
DO - 10.5220/0009177700002513
M3 - Conference contribution
AN - SCOPUS:85083570874
T3 - BIOINFORMATICS 2020 - 11th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020
SP - 218
EP - 225
BT - BIOINFORMATICS 2020 - 11th International Conference on Bioinformatics Models, Methods and Algorithms, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020
A2 - De Maria, Elisabetta
A2 - Fred, Ana
A2 - Gamboa, Hugo
PB - SciTePress
T2 - 11th International Conference on Bioinformatics Models, Methods and Algorithms, BIOINFORMATICS 2020 - Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020
Y2 - 24 February 2020 through 26 February 2020
ER -