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Related Concept Videos

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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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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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Related Experiment Video

Updated: Mar 30, 2026

A Computational Pipeline for Intergenic/Intragenic Enhancer RNA Quantification in Mouse Embryonic Stem Cells
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AGA: Interactive pipeline for reproducible genomics analyses.

Michael Considine1, Hilary Parker2, Yingying Wei2

  • 1Department of Oncology Biostatistics & Bioinformatics, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.

F1000Research
|December 5, 2017
PubMed
Summary
This summary is machine-generated.

Automated Genomics Analysis (AGA) provides an intuitive platform for high-throughput genomic data analysis. This tool facilitates data integration, comparison, and reproducible research for both novice and expert users.

Keywords:
analysis, datasets, DNAarraysautomatedgenomicmethylation, expression

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • High-throughput genomic data analysis requires sophisticated tools.
  • Existing automated programs often lack flexibility in data comparison.
  • Reproducibility and collaboration are key challenges in bioinformatics.

Purpose of the Study:

  • To introduce Automated Genomics Analysis (AGA), an interactive program for analyzing high-throughput genomic data.
  • To provide a user-friendly, guided pipeline for data integration, comparison, and customization.
  • To support reproducible research and collaborative efforts between users of varying expertise.

Main Methods:

  • Development of an interactive, point-and-click graphical user interface (GUI).
  • Implementation of a guided pipeline for combining, defining, and comparing datasets.
  • Integration of flexible sample group selection from complex annotations.
  • Inclusion of batch correction techniques for diverse dataset integration.
  • Functionality to save outputs (plots, tables, data) and log files for R script reproducibility.

Main Results:

  • AGA enables easy combination and comparison of complex genomic datasets.
  • The program supports flexible selection of sample groups for analysis.
  • Batch correction facilitates integration of data from diverse studies.
  • Users can save analysis outputs and log files for reproducible research.
  • The interface supports collaboration, allowing novices to initiate analyses extendable by advanced R users.

Conclusions:

  • Automated Genomics Analysis (AGA) offers a flexible and user-friendly solution for high-throughput genomic data analysis.
  • The program enhances reproducibility and facilitates collaboration in bioinformatics research.
  • AGA empowers both novice and advanced users to perform complex genomic data analyses effectively.