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Related Concept Videos

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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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Intact DNA strands can be found in fossils, while scientists sometimes struggle to keep RNA intact under laboratory conditions. The structural variations between RNA and DNA underlie the differences in their stability and longevity. Because DNA is double-stranded, it is inherently more stable. The single-stranded structure of RNA is less stable but also more flexible and can form weak internal bonds. Additionally, most RNAs in the cell are relatively short, while DNA can be up to 250 million...
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RNA Interference01:23

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RNA Structure01:23

RNA Structure

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The basic structure of RNA consists of a five-carbon sugar and one of four nitrogenous bases. Although most RNA is single-stranded, it can form complex secondary and tertiary structures. Such structures play essential roles in the regulation of transcription and translation.
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RNA Splicing01:32

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Updated: Jan 25, 2026

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

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FastqPuri: high-performance preprocessing of RNA-seq data.

Paula Pérez-Rubio1, Claudio Lottaz1, Julia C Engelmann2

  • 1Statistical Bioinformatics, Institute of Functional Genomics, University of Regensburg, Am BioPark 9, Regensburg, 93053, Germany.

BMC Bioinformatics
|May 5, 2019
PubMed
Summary
This summary is machine-generated.

FastqPuri is a new, efficient tool for preprocessing raw sequencing data, streamlining RNA sequencing analysis by performing quality control, adapter, and contamination filtering. It offers superior speed and comprehensiveness compared to existing methods.

Keywords:
PreprocessingQuality controlRNA-seqSequence datafastq

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Identification of Footprints of RNA:Protein Complexes via RNA Immunoprecipitation in Tandem Followed by Sequencing RIPiT-Seq
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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • RNA sequencing (RNA-seq) is standard for gene expression analysis.
  • Preprocessing raw sequence data is the most time-consuming step in RNA-seq analysis.
  • Existing tools lack a comprehensive, flexible, and fast solution for all preprocessing steps.

Purpose of the Study:

  • Introduce FastqPuri, a novel software for efficient preprocessing of raw sequencing data.
  • Address the need for a comprehensive and fast tool to handle RNA-seq data preprocessing.
  • Improve the speed and efficiency of the initial stages of next-generation sequencing data analysis.

Main Methods:

  • Developed FastqPuri, a light-weight and efficient preprocessing tool for fastq data.
  • Implemented quality control reporting, adapter sequence removal, and biological contamination filtering.
  • Designed to accept single- and paired-end data in uncompressed or compressed fastq files.

Main Results:

  • FastqPuri provides detailed sequence quality reports with new plots for decision making.
  • The tool efficiently removes adapter sequences and biological contaminants.
  • Benchmarking shows FastqPuri outperforms existing tools in speed, memory usage, versatility, and comprehensiveness.

Conclusions:

  • FastqPuri offers a comprehensive solution for short read sequence data preprocessing.
  • It is optimized for RNA-seq but suitable for any short read data requiring high quality.
  • The tool provides flexible filtering options and is available under GPL v3.