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

[peer.b]

Hi all,

check this PLOS ONE paper out:
An Extensive Evaluation of Read Trimming Effects on Illumina NGS Data Analysis

http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0085024

Researchers from the Institute of Applied Genomics, Italy evaluated 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.

The trimming tools investigated are:
Cutadapt
Condetri
ERNE-filter
FASTX
prinseq
Trimmomatic
SolexaQA
SolexaQA-bwa
Sickle

[Fernando Seixas]

Hi all,

About this paper. Is it clearer to anyone why they claim that the window based tools are better for de novo assembly when at the same time they say these same tools (e.g. Trimmomatic and Sickle) give more fragmented assemblies (see N50 in Fig. 5)? I might being quite naif in the way I'm interpreting the results but except for the N50 I don't see any great differences in the two other parameter used to analyse assembly quality, and N50 seems to me to be worse in the window based tools..

[AdrianP]

I disagree with the findings. They didn't even compare trimmed vs untrimmed in terms of misassemblies.