SolexaQA: At-a-glance quality assessment of Illumina second-generation sequencing data

By Murray P. Cox, Daniel A. Peterson, Patrick J. Biggs. BMC Bioinformatics, 2010

1,318 citations recorded by the source corpus.

BackgroundIllumina's second-generation sequencing platform is playing an increasingly prominent role in modern DNA and RNA sequencing efforts. However, rapid, simple, standardized and independent measures of run quality are currently lacking, as are tools to process sequences for use in downstream applications based on read-level quality data.ResultsWe present SolexaQA, a user-friendly software package designed to generate detailed statistics and at-a-glance graphics of sequence data quality both quickly and in an automated fashion. This package contains associated software to trim sequences dynamically using the quality scores of bases within individual reads.ConclusionThe SolexaQA package produces standardized outputs within minutes, thus facilitating ready comparison between flow cell lanes and machine runs, as well as providing immediate diagnostic information to guide the manipulation of sequence data for downstream analyses.

Subfields: Cancer Research, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e030639c6f34e4415df052fb66de5003c61df9d9

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Citations in the corpus

MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: detection of more than 230 subtropical marine species (2015, methodology): “pl from the SOLEXAQA software package [25] with a cut-off threshold set at a Phred score of 10 (= 10−1 error rate) [26].”
PEAR: a fast and accurate Illumina Paired-End reAd mergeR (2013, neutral): “Furthermore, there is an exponential increase in error rates (ERs) along the reads (Cox et al. , 2010).”
A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae (2012, methodology): “Bad quality reads (phred score <20) were trimmed using the BWA trimming algorithm (40) through the SolexaQA tool kit (41).”
The Microbial Genomes Atlas (MiGA) webserver: taxonomic and gene diversity analysis of Archaea and Bacteria at the whole genome level (2018, methodology): “Datasets initialized from raw short reads are trimmed, stripped from typically used adaptor sequences, and quality-checked using SolexaQA++ with Phred quality score threshold of 20 and minimum length of 50 bp (12), Scythe with default parameters (13), and FastQC (14), respectively.”
MeDuSa: a multi-draft based scaffolder (2015, methodology): “Each paired ends-based software was used both on trimmed (using DYNAMICTRIMMING from the SOLEXAQA package (Cox et al., 2010) and Phred 30 as the quality threshold) and untrimmed reads datasets.”
NGS QC Toolkit: A Toolkit for Quality Control of Next Generation Sequencing Data (2012, methodology): “A few online/standalone software packages/pipelines with different features have been developed for QC of NGS data [5–9].”
WebMGA: a customizable web server for fast metagenomic sequence analysis (2011, methodology): “The third tool (Trim) trims low-quality tails of inputted Illumina reads using SolexaQA [30].”
A survey of tools for variant analysis of next-generation genome sequencing data (2013, background): “Galaxy offers an integrated tool [59] that creates FASTQ summary statistics and performs flexible trimming and filtering tasks. htSeqTools [60] and SolexaQA [55] include quality assessment, processing and visualization functionality.”
AfterQC: automatic filtering, trimming, error removing and quality control for fastq data (2017, methodology): “…data, some good tools can already perform quality control, such like FastQC [4] with per-base and per-sequence quality profiling functions and PRIN-SEQ [5] with FASTA/FASTQ statistics capability, while some other tools being able to read trimming, such like Trimmomatic [6] and SolexaQA [7].”
Metagenomics: Tools and Insights for Analyzing Next-Generation Sequencing Data Derived from Biodiversity Studies (2015, methodology): “77 SolexaQA 78 and Lucy 2 79 are also used for FASTQ files.”
An Extensive Evaluation of Read Trimming Effects on Illumina NGS Data Analysis (2013, methodology): “Window based algorithms: SolexaQA (Dynamic Trim implementation) The default algorithm implemented by SolexaQA was named “Dynamic Trim” [29].”