ArticleInternational journal of molecular sciences2018
Hierarchical Clustering of DNA k-mer Counts in RNAseq Fastq Files Identifies Sample Heterogeneities.
Article in International journal of molecular sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Article
- Article
- Application of the Interaction between Tissue Immunohistochemistry Staining and Clinicopathological Factors for Evaluating the Risk of Oral Cancer Progression by Hierarchical Clustering Analysis: A Case-Control Study in a Taiwanese Population.Diagnostics (Basel, Switzerland) · 2021Article
- Natural compounds attenuate heavy metal-induced PC12 cell damage.The Journal of international medical research · 2020Article
- Age, gender and UV-exposition related effects on gene expression in in vivo aged short term cultivated human dermal fibroblasts.PloS one · 2017Article
- How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use?RNA (New York, N.Y.) · 2016Article
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Authors and funding
3 authors.
Funding
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Abstract
We apply hierarchical clustering (HC) of DNA k-mer counts on multiple Fastq files. The tree structures produced by HC may reflect experimental groups and thereby indicate experimental effects, but clustering of preparation groups indicates the presence of batch effects. Hence, HC of DNA k-mer counts may serve as a diagnostic device. In order to provide a simple applicable tool we implemented sequential analysis of Fastq reads with low memory usage in an R package (seqTools) available on Bioconductor. The approach is validated by analysis of Fastq file batches containing RNAseq data. Analysis of three Fastq batches downloaded from ArrayExpress indicated experimental effects. Analysis of RNAseq data from two cell types (dermal fibroblasts and Jurkat cells) sequenced in our facility indicate presence of batch effects. The observed batch effects were also present in reads mapped to the human genome and also in reads filtered for high quality (Phred > 30). We propose, that hierarchical clustering of DNA k-mer counts provides an unspecific diagnostic tool for RNAseq experiments. Further exploration is required once samples are identified as outliers in HC derived trees.
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Registered trials
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