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Cited by 475

The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.

An Extensive Evaluation of Read Trimming Effects on Illumina NGS Data Analysis

Open access
Del Fabbro, Cristian, Scalabrin, Simone, Morgante, Michele, Giorgi, Federico M.·2013·PLoS ONE

Abstract

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.

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Metadata

Authors
Del Fabbro, C., Scalabrin, S., Morgante, M., & Giorgi, F. M.
Venue
PLoS ONE
Published
2013-12-23
Volume
8
Issue
12
Pages
e85024
ISSN
1932-6203 (ISSN-L)
OpenAlex
W1983426138
Cited by
475
References
12
FWCI
9.82
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: An Extensive Evaluation of Read Trimming Effects on Illumina NGS Data Analysis. https://app.cochat.ai/papers/10.1371/journal.pone.0085024
The paper
Del Fabbro, C., Scalabrin, S., Morgante, M., & Giorgi, F. M. (2013). An Extensive Evaluation of Read Trimming Effects on Illumina NGS Data Analysis. PLoS ONE. https://doi.org/10.1371/journal.pone.0085024

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.