Cited by 1,357Genomics and Phylogenetic StudiesFractal and DNA sequence analysisGenetics, Bioinformatics, and Biomedical Research

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

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

DOI 10.1186/1471-2105-11-485PMC PMC2956736

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Abstract

BACKGROUND: Illumina'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. RESULTS: We 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. CONCLUSION: The 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.

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Figure 1 Example heat map showing several commonly observed quality defects. Nucleotide positions 1-75 are plotted from left-to-right along the x-axis; tiles 1-100 are ranked from top-to-bottom along the y-axis. (These numbers may vary for other datasets). The scale depicts the mean probability of observing a base call error for each tile at each nucleotide position. The defects evident in this dataset (see text for details) are atypical of Illumina sequencing; this dataset was chosen specifically to illustrate the capabilities of SolexaQA.CC BY · PubMed Central

Figure 2 Distribution of mean quality (probability of error, y-axis) at each nucleotide position (x-axis) for each tile individually (dotted black lines) and the entire dataset combined (red circles). Note the considerable variance in data quality between tiles. The defects evident in this dataset (see text for details) are atypical of Illumina sequencing; this dataset was chosen specifically to illustrate the capabilities of SolexaQA.CC BY · PubMed Central

Figure 3 Distribution of longest read segments passing a user-defined quality threshold (here, P = 0.05, or equivalently, Phred quality score Q ≈ 13, or a base call error rate of 1-in-20). Note that reads in this dataset would be trimmed on average to ~25 nucleotides (i.e., only approximately one-third of the initial 75 nucleotide read length). The defects evident in this dataset (see text for details) are atypical of Illumina sequencing; this dataset was chosen specifically to illustrate the capabilities of SolexaQA.CC BY · PubMed Central

Figure 4 Effect of dynamically trimmed versus untrimmed reads on de novo assembly with the Velvet assembler. Dynamically trimmed reads (solid symbols) relative to untrimmed reads (open symbols) yield improved N50 values (red squares) and maximum contig sizes (blue triangles). Summary statistics were averaged across de novo assemblies for 20 isolates of Campylobacter coli and C. jejuni, and normalized by the total number of reads employed in each assembly.CC BY · PubMed Central

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R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
Velvet: Algorithms for de novo short read assembly using de Bruijn graphsPreprint
Zerbino, D. R., & Birney, E. (2008) · Genome Research · doi:10.1101/gr.074492.107 · Cited by 9,575
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066
The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants
Cock, P., Fields, C. J., Goto, N., Heuer, M., & Rice, P. M. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp1137 · Cited by 1,896
Substantial biases in ultra-short read data sets from high-throughput DNA sequencing
Dohm, J. C., Lottaz, C., Borodina, T., & Himmelbauer, H. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn425 · Cited by 1,088
Matrix2png: a utility for visualizing matrix data
Pavlidis, P., & Noble, W. S. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.295 · Cited by 345
Probabilistic base calling of Solexa sequencing data
Rougemont, J., Amzallag, A., Iseli, C., Farinelli, L., Xénarios, I., & Naef, F. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-431 · Cited by 104
PIQA: pipeline for Illumina G1 genome analyzer data quality assessment
Martinez-Alcántara, A., Ballesteros, E., Feng, C., Rojas, M., Koshinsky, H. A., Fofanov, V. Y., Havlak, P., & Fofanov, Y. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp429 · Cited by 50
TileQC: A system for tile-based quality control of Solexa data
Dolan, P. C., & Denver, D. R. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-250 · Cited by 38

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Authors: Cox, M. P., Peterson, D. A., & Biggs, P. J.
Affiliations: Massey University (NZ)
Corresponding author: Cox, Murray P
ORCID: Cox, Murray P
Peterson, Daniel A
Biggs, Patrick J
Venue: BMC Bioinformatics
Publisher: Springer Science and Business Media LLC
Published: 2010-09-27
Volume: 11
Issue: 1
Pages: 485-485
ISSN: 1471-2105 (ISSN-L)
DOI: 10.1186/1471-2105-11-485
PMC: PMC2956736
OpenAlex: W2097205777
Cited by: 1,357
References: 9
Citations by year: 2026: 29 · 2025: 50 · 2024: 57 · 2023: 86 · 2022: 86 · 2021: 131 · 2020: 118 · 2019: 118 · 2018: 135 · 2017: 105 · 2016: 148 · 2015: 95 · 2014: 97 · 2013: 56 · 2012: 37
FWCI: 13.30
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/2.0 (tdm)
Locations: BMC Bioinformatics (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders: Royal Society
Royal Society Te Apārangi (MAU0802)
Massey University
Marsden Fund (MAU0802)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fractal and DNA sequence analysis
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genetics, Bioinformatics, and Biomedical Research
Keywords: sequence trimming, quality control software
MeSH terms: Base Sequence, Software, Sequence Analysis, DNA, Sequence Analysis, RNA, Internet

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

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