Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)

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Software Tools for Microbiome Data Analysis

Authors
Ruhina Afroz Patel1, *, Shazia Shadab Mazhar1, Sanjay N. Harke1
1Institute of Biosciences and Technology, MGM University, Aurangabad, India
*Corresponding author. Email: patelruhina2019@gmail.com
Corresponding Author
Ruhina Afroz Patel
Available Online 1 May 2023.
DOI
10.2991/978-94-6463-136-4_52How to use a DOI?
Keywords
Open-source Tools; R Tool; Microbiome Data Analysis; QIIME; USEARCH; Scatter Plot; Box Plot
Abstract

Rapid improvements in microbiome research have been driven by advances in high-throughput sequencing (HTS), and enormous microbiome databases are now being developed. However, the variety of software tools and the intricacy of analytic pipelines make entry into this field challenging. Here, we provide a thorough overview of the benefits and limits of microbiome data analytic approaches. Then, we offer various pipelines for amplicon and metagenomic analysis, as well as discuss widely used software and databases, to assist researchers in selecting the most suitable tools. To further assist researchers in making wise choices, we illustrate statistical and visualisation techniques suitable for microbiome analysis, such as correlation, taxonomic structure, network, source tracing, differential comparative, pattern recognition, alpha, beta diversity and popular visualisation styles. We expect that this study will enable researchers to conduct data analysis more efficiently and to choose the proper tools quickly in order to efficiently extract the biological meaning hidden within the data.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
Series
Advances in Computer Science Research
Publication Date
1 May 2023
ISBN
10.2991/978-94-6463-136-4_52
ISSN
2352-538X
DOI
10.2991/978-94-6463-136-4_52How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Ruhina Afroz Patel
AU  - Shazia Shadab Mazhar
AU  - Sanjay N. Harke
PY  - 2023
DA  - 2023/05/01
TI  - Software Tools for Microbiome Data Analysis
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 612
EP  - 621
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_52
DO  - 10.2991/978-94-6463-136-4_52
ID  - Patel2023
ER  -