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Related Concept Videos

Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Evolutionary Relationships through Genome Comparisons02:54

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Related Experiment Video

Updated: May 24, 2025

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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MicrobiomeStatPlots: Microbiome statistics plotting gallery for meta-omics and bioinformatics.

Defeng Bai1, Chuang Ma1,2, Jiani Xun1

  • 1Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen Chinese Academy of Agricultural Sciences Shenzhen China.

Imeta
|March 3, 2025
PubMed
Summary

MicrobiomeStatPlots offers streamlined tools for analyzing and visualizing complex microbiome multi-omics data. This platform enhances research efficiency with reproducible workflows and extensive visualization options.

Keywords:
bioinformaticsinterpretationmicrobiomemulti‐omicsvisualization

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Area of Science:

  • Microbiome research
  • Bioinformatics
  • Data visualization

Background:

  • Microbiome research generates vast multi-omics data, posing analysis and visualization challenges.
  • Existing tools may lack integration and user-friendliness for complex datasets.

Purpose of the Study:

  • Introduce MicrobiomeStatPlots, a platform for streamlined microbiome data analysis and visualization.
  • Provide researchers with reproducible tools and diverse visualization strategies.

Main Methods:

  • Development of a comprehensive platform integrating bioinformatics workflows and multi-omics pipelines.
  • Inclusion of 82 distinct visualization cases with tutorials and R-based strategies.
  • Open-source availability on GitHub with customization options.

Main Results:

  • MicrobiomeStatPlots offers accessible and user-friendly tools for microbiome data interpretation.
  • The platform supports reproducible analysis and visualization of multi-omics data.
  • Facilitates efficient exploration of microbiome datasets.

Conclusions:

  • MicrobiomeStatPlots addresses critical gaps in microbiome data analysis and visualization.
  • Enhances the efficiency and impact of microbiome research.
  • Future development includes expanded omics data support and workflow integration.