ArticleBMC bioinformatics2016
Additive methods for genomic signatures.
Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- CGRclust: Chaos Game Representation for twin contrastive clustering of unlabelled DNA sequences.BMC genomics · 2024Article
- On leveraging self-supervised learning for accurate HCV genotyping.Scientific reports · 2024Article
- Environment and taxonomy shape the genomic signature of prokaryotic extremophiles.Scientific reports · 2023Article
- Genomic Signature in Evolutionary Biology: A Review.Biology · 2023Review
- ANXA2 is a potential biomarker for cancer prognosis and immune infiltration: A systematic pan-cancer analysis.Frontiers in genetics · 2023Article
- Microbial characterization based on multifractal analysis of metagenomes.Frontiers in cellular and infection microbiology · 2023Article
- Development and Validation of a 6-Gene Hypoxia-Related Prognostic Signature For Cholangiocarcinoma.Frontiers in oncology · 2022Article
- Development and clinical validation of a necroptosis-related gene signature for prediction of prognosis and tumor immunity in lung adenocarcinoma.American journal of cancer research · 2022Article
- Exploring the Lethality of Human-Adapted Coronavirus Through Alignment-Free Machine Learning Approaches Using Genomic Sequences.Current genomics · 2021Article
- Development and validation of a survival model for esophageal adenocarcinoma based on autophagy-associated genes.Bioengineered · 2021Article
- Differential Expression of theFrontiers in cell and developmental biology · 2021Article
- Application of an Autophagy-Related Gene Prognostic Risk Model Based on TCGA Database in Cervical Cancer.Frontiers in genetics · 2020Article
- Identification and validation of an individualized autophagy-clinical prognostic index in gastric cancer patients.Cancer cell international · 2020Article
- Alignment-free genomic sequence comparison using FCGR and signal processing.BMC bioinformatics · 2019Article
- An open-source k-mer based machine learning tool for fast and accurate subtyping of HIV-1 genomes.PloS one · 2018Article
- Formalin-fixed paraffin-embedded sample conditions for deep next generation sequencing.The Journal of surgical research · 2017Article
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5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundStudies exploring the potential of Chaos Game Representations (CGR) of genomic sequences to act as "genomic signatures" (to be species- and genome-specific) showed that CGR patterns of nuclear and organellar DNA sequences of the same organism can be very different. While the hypothesis that CGRs of mitochondrial DNA sequences can act as genomic signatures was validated for a snapshot of all sequenced mitochondrial genomes available in the NCBI GenBank sequence database, to our knowledge no such extensive analysis of CGRs of nuclear DNA sequences exists to date.
resultsWe analyzed an extensive dataset, totalling 1.45 gigabase pairs, of nuclear/nucleoid genomic sequences (nDNA) from 42 different organisms, spanning all major kingdoms of life. Our computational experiments indicate that CGR signatures of nDNA of two different origins cannot always be differentiated, especially if they originate from closely-related species such as H. sapiens and P. troglodytes or E. coli and E. fergusonii. To address this issue, we propose the general concept of additive DNA signature of a set (collection) of DNA sequences. One particular instance, the composite DNA signature, combines information from nDNA fragments and organellar (mitochondrial, chloroplast, or plasmid) genomes. We demonstrate that, in this dataset, composite DNA signatures originating from two different organisms can be differentiated in all cases, including those where the use of CGR signatures of nDNA failed or was inconclusive. Another instance, the assembled DNA signature, combines information from many short DNA subfragments (e.g., 100 basepairs) of a given DNA fragment, to produce its signature. We show that an assembled DNA signature has the same distinguishing power as a conventionally computed CGR signature, while using shorter contiguous sequences and potentially less sequence information.
conclusionsOur results suggest that, while CGR signatures of nDNA cannot always play the role of genomic signatures, composite and assembled DNA signatures (separately or in combination) could potentially be used instead. Such additive signatures could be used, e.g., with raw unassembled next-generation sequencing (NGS) read data, when high-quality sequencing data is not available, or to complement information obtained by other methods of species identification or classification.
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