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