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Related Concept Videos

RNA-seq03:21

RNA-seq

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. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...
Next-generation Sequencing03:00

Next-generation Sequencing

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.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features.
Ribosome Profiling02:24

Ribosome Profiling

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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Genomics02:02

Genomics

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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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

NGS-Trex: Next Generation Sequencing Transcriptome profile explorer.

Ilenia Boria1, Lara Boatti, Graziano Pesole

  • 1Dipartimento di Chimica, Università degli Studi di Milano, Milano, Italy.

BMC Bioinformatics
|July 3, 2013
PubMed
Summary
This summary is machine-generated.

Next-Generation Sequencing (NGS) Transcriptome profile explorer (NGS-Trex) simplifies transcriptome analysis for biologists. This web-based tool automates data mining for gene and splice variant identification without requiring bioinformatics expertise.

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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Next-Generation Sequencing (NGS) offers powerful DNA sequencing capabilities but necessitates advanced bioinformatics skills and resources.
  • Many biological research projects require standard analyses for gene, transcript, and splice variant identification, achievable with accessible tools.
  • A gap exists for user-friendly systems that automate sequence analysis and data mining for researchers without extensive computational backgrounds.

Purpose of the Study:

  • To develop an automated system for analyzing NGS data from transcriptome studies.
  • To provide an easy-to-use web interface for researchers to characterize transcriptome profiles.
  • To enable differential gene and transcript expression analysis for comparing biological samples.

Main Methods:

  • Development of an automatic system named NGS-Trex (NGS Transcriptome profile explorer).
  • Implementation of a web interface (http://www.ngs-trex.org) for raw sequence uploading and analysis parameter setting.
  • Integration of data mining tools for ranking and filtering genes, transcripts, and splice sites, with visualization options.

Main Results:

  • NGS-Trex provides an accurate characterization of transcriptome profiles.
  • The system facilitates differential expression analysis at both gene and transcript levels.
  • Users can easily obtain ranked and filtered lists of genes, transcripts, and splice sites via query forms.
  • Data visualization is supported through tables, text files, and a genome browser.

Conclusions:

  • NGS-Trex is a user-friendly tool designed for RNA-Seq data analysis.
  • It primarily targets 'wet biology' researchers with limited bioinformatics expertise.
  • The tool simplifies transcriptome profile exploration using NGS data.