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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.

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Related Experiment Video

Updated: Jun 4, 2026

Pyrosequencing: A Simple Method for Accurate Genotyping
13:06

Pyrosequencing: A Simple Method for Accurate Genotyping

Published on: January 8, 2008

Flower: extracting information from pyrosequencing data.

Ketil Malde1

  • 1The Norwegian Marine Data Centre, Institute of Marine Research, Bergen, Norway. ketil.malde@imr.no

Bioinformatics (Oxford, England)
|February 19, 2011
PubMed
Summary
This summary is machine-generated.

Flower is a new, freely available program that extracts crucial flow data from Roche 454 sequencing system files (SFF). This enables accurate error estimation for applications like metagenomics, overcoming limitations of proprietary software.

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Last Updated: Jun 4, 2026

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Roche's 454 sequencing technology generates data in the SFF file format.
  • SFF files contain essential flow values for base and quality calling.
  • Access to flow values is critical for accurate error estimation in sequence data.

Purpose of the Study:

  • To develop a publicly available tool for accessing SFF file information.
  • To enable accurate error estimation in sequencing reads.

Main Methods:

  • Developed the Flower program.
  • Flower extracts flow values from SFF files.
  • Flower converts SFF data into various textual output formats.

Main Results:

  • Flower successfully extracts flow values from SFF files.
  • The program provides access to previously inaccessible data.
  • Enables downstream analysis requiring flow information.

Conclusions:

  • Flower provides a valuable, open-source solution for accessing Roche 454 sequencing data.
  • Facilitates improved accuracy in metagenomics and other sequence-based applications.
  • Overcomes limitations of proprietary software for SFF file analysis.