HTQC: a fast quality control toolkit for Illumina sequencing data

Yang, Xi; Liu, Di; Liu, Fei; Wu, Jun; Zou, Jing; Xiao, Xue; Zhao, Fangqing; Zhu, Baoli

doi:10.1186/1471-2105-14-33

Cited by 160 publications

(121 citation statements)

References 6 publications

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“…Reference-free approaches for analyzing WGS data typically involve examining base calling quality, read length, GC content (Yang et al , 2013) and exploring k-mer (words of size k ) spectra (Chor et al , 2009; Lo and Chain, 2014). A frequently used reference-free quality control tool is FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/).…”

Section: Introductionmentioning

confidence: 99%

KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies

et al. 2016

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Motivation De novo assembly of whole genome shotgun (WGS) next-generation sequencing (NGS) data benefits from high-quality input with high coverage. However, in practice, determining the quality and quantity of useful reads quickly and in a reference-free manner is not trivial. Gaining a better understanding of the WGS data, and how that data is utilized by assemblers, provides useful insights that can inform the assembly process and result in better assemblies.ResultsWe present the K-mer Analysis Toolkit (KAT): a multi-purpose software toolkit for reference-free quality control (QC) of WGS reads and de novo genome assemblies, primarily via their k-mer frequencies and GC composition. KAT enables users to assess levels of errors, bias and contamination at various stages of the assembly process. In this paper we highlight KAT’s ability to provide valuable insights into assembly composition and quality of genome assemblies through pairwise comparison of k-mers present in both input reads and the assemblies.Availability and ImplementationKAT is available under the GPLv3 license at: https://github.com/TGAC/KAT.Supplementary information Supplementary data are available at Bioinformatics online.

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Section: Introductionmentioning

confidence: 99%

KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies

et al. 2016

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“…The raw reads were trimmed and filtered on the basis of sequence quality (20 Q-score cutoff) and length (20 bp cutoff) using HTQC 1.92.344. A preliminary assembly was generated by ABySS 1.9.045 with the options of k-mer = 41 and insert size = 400 bp.…”

Section: Methodsmentioning

confidence: 99%

Genome Analysis of a Zygomycete Fungus Choanephora cucurbitarum Elucidates Necrotrophic Features Including Bacterial Genes Related to Plant Colonization

Min

Park

et al. 2017

Sci Rep

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A zygomycete fungus, Choanephora cucurbitarum is a plant pathogen that causes blossom rot in cucurbits and other plants. Here we report the genome sequence of Choanephora cucurbitarum KUS-F28377 isolated from squash. The assembled genome has a size of 29.1 Mbp and 11,977 protein-coding genes. The genome analysis indicated that C. cucurbitarum may employ a plant pathogenic mechanism similar to that of bacterial plant pathogens. The genome contained 11 genes with a Streptomyces subtilisin inhibitor-like domain, which plays an important role in the defense against plant immunity. This domain has been found only in bacterial genomes. Carbohydrate active enzyme analysis detected 312 CAZymes in this genome where carbohydrate esterase family 6, rarely found in dikaryotic fungal genomes, was comparatively enriched. The comparative genome analysis showed that the genes related to sexual communication such as the biosynthesis of β-carotene and trisporic acid were conserved and diverged during the evolution of zygomycete genomes. Overall, these findings will help us to understand how zygomycetes are associated with plants.

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“…The original read pairs are classified into two distinct datasets: the assembled reads pairs and the nonassembled ones. Notably, the whole process in this step was performed by HTQC (24).…”

Section: Computational Pipeline For Tcr Sequence Analysismentioning

confidence: 99%

TCRklass: A New K-String–Based Algorithm for Human and Mouse TCR Repertoire Characterization

Yang

Liu

et al. 2015

The Journal of Immunology

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The next-generation sequencing technology has promoted the study on human TCR repertoire, which is essential for the adaptive immunity. To decipher the complexity of TCR repertoire, we developed an integrated pipeline, TCRklass, using K-string–based algorithm that has significantly improved the accuracy and performance over existing tools. We tested TCRklass using manually curated short read datasets in comparison with in silico datasets; it showed higher precision and recall rates on CDR3 identification. We applied TCRklass on large datasets of two human and three mouse TCR repertoires; it demonstrated higher reliability on CDR3 identification and much less biased V/J profiling, which are the two components contributing the diversity of the repertoire. Because of the sequencing cost, short paired-end reads generated by next-generation sequencing technology are and will remain the main source of data, and we believe that the TCRklass is a useful and reliable toolkit for TCR repertoire analysis.

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HTQC: a fast quality control toolkit for Illumina sequencing data

Cited by 160 publications

References 6 publications

KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies

KAT: a K-mer analysis toolkit to quality control NGS datasets and genome assemblies

Genome Analysis of a Zygomycete Fungus Choanephora cucurbitarum Elucidates Necrotrophic Features Including Bacterial Genes Related to Plant Colonization

TCRklass: A New K-String–Based Algorithm for Human and Mouse TCR Repertoire Characterization

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