An extensive evaluation of read trimming effects on Illumina NGS data analysis

Next Generation Sequencing is having an extremely strong impact in biological and medical research and diagnostics, with applications ranging from gene expression quantification to genotyping and genome reconstruction. Sequencing data is often provided as raw reads which are processed prior to analy...

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Bibliographic Details
Published in:PloS one 2013-12, Vol.8 (12), p.e85024-e85024
Main Authors: Del Fabbro, Cristian, Scalabrin, Simone, Morgante, Michele, Giorgi, Federico M
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Bioinformatics
Computational Biology - methods
Computer applications
Data analysis
Data processing
Deoxyribonucleic acid
DNA
DNA methylation
Gene expression
Gene sequencing
Genes
Genetic testing
Genomes
Genomics
Genotyping
High-Throughput Nucleotide Sequencing - methods
Integrated software
Medical research
Perl
Preprocessing
Quality
Reliability analysis
Research Design - standards
Ribonucleic acid
RNA
RNA sequencing
Single-nucleotide polymorphism
Trimming
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Summary:Next Generation Sequencing is having an extremely strong impact in biological and medical research and diagnostics, with applications ranging from gene expression quantification to genotyping and genome reconstruction. Sequencing data is often provided as raw reads which are processed prior to analysis 1 of the most used preprocessing procedures is read trimming, which aims at removing low quality portions while preserving the longest high quality part of a NGS read. In the current work, we evaluate nine different trimming algorithms in four datasets and three common NGS-based applications (RNA-Seq, SNP calling and genome assembly). Trimming is shown to increase the quality and reliability of the analysis, with concurrent gains in terms of execution time and computational resources needed.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0085024