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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation
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SeqBox: RNAseq/ChIPseq reproducible analysis on a consumer game computer.

Marco Beccuti1, Francesca Cordero1, Maddalena Arigoni2

  • 1Department of Computer Sciences, University of Torino, 10124 Turin, Italy.

Bioinformatics (Oxford, England)
|October 26, 2017
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Summary
This summary is machine-generated.

SeqBox offers a cost-effective hardware and software solution for reproducible RNA sequencing (RNAseq) and ChIP sequencing (ChIPseq) data analysis. This system enhances accessibility for researchers lacking scripting expertise.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Short reads sequencing technologies are widely used but RNAseq and ChIPseq data analysis remains computationally intensive.
  • Reproducibility of sequencing data analysis across different laboratories is a persistent challenge.
  • Lack of user-friendly tools limits access to advanced bioinformatics analysis for many scientists.

Purpose of the Study:

  • To develop an affordable, efficient, and reproducible hardware/software solution for RNAseq and ChIPseq data analysis.
  • To provide a graphical user interface (GUI) that simplifies complex bioinformatics workflows.
  • To enable scientists, regardless of scripting experience, to perform reliable sequencing data analysis.

Main Methods:

  • Development of SeqBox, a integrated hardware/software system utilizing a mini-PC (NUC6I7KYK) with a powerful processor and SSD.
  • Implementation of Docker container platform for consistent and reproducible software environment.
  • Integration of a user-friendly GUI for streamlined RNAseq and ChIPseq data analysis.

Main Results:

  • SeqBox provides a cost-effective and efficient platform for analyzing RNAseq and ChIPseq data.
  • The Docker-based approach ensures reproducibility of analysis results.
  • The GUI facilitates rapid and reliable data analysis for users with varying levels of bioinformatics expertise.

Conclusions:

  • SeqBox addresses the computational demands and reproducibility issues in RNAseq and ChIPseq data analysis.
  • The system democratizes access to high-quality bioinformatics analysis, empowering a broader range of researchers.
  • SeqBox represents a significant advancement in making complex sequencing data analysis more accessible and reliable.