ArticleBMC bioinformatics2019
From trash to treasure: detecting unexpected contamination in unmapped NGS data.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed.
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- Routine Detection of Viruses Through Metagenomics: Where Do We Stand?The American journal of tropical medicine and hygiene · 2025Article
- Advantages of Mutant Generation by Genome Rearrangements of Non-Conventional Yeast via Direct Nuclease Transfection.Genes to cells : devoted to molecular & cellular mechanisms · 2025Article
- Sensitivity of transcriptomics: Different samples and methodology alter conclusions in Gulf pipefish (Syngnathus scovelli).The Journal of heredity · 2025Article
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- Whole genome resequencing unveils low-temperature stress tolerance specific genomic variations in jute (Corchorus sp.).Journal, genetic engineering & biotechnology · 2024Article
- Impaired signaling pathways on Berardinelli-Seip congenital lipodystrophy macrophages during Leishmania infantum infection.Scientific reports · 2024Article
- Toward a Predictive Understanding of Cyanobacterial Harmful Algal Blooms through AI Integration of Physical, Chemical, and Biological Data.ACS ES&T water · 2024Review
- MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.BMC bioinformatics · 2024Article
- Transcriptome data reveals the conservation genetics ofFrontiers in plant science · 2024Article
- Adenine methylation is very scarce in theeLife · 2023Article
- Evaluation of noninvasive biospecimens for transcriptome studies.BMC genomics · 2023Article
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- Metatranscriptomic analysis uncovers prevalent viral ORFs compatible with mitochondrial translation.mSystems · 2023Article
- A Protocol for Low-Input RNA-Sequencing of Patients with Febrile Neutropenia Captures Relevant Immunological Information.International journal of molecular sciences · 2023Article
- Benchmarking machine learning robustness in Covid-19 genome sequence classification.Scientific reports · 2023Article
- Pathogen detection in RNA-seq data with Pathonoia.BMC bioinformatics · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNext Generation Sequencing (NGS) experiments produce millions of short sequences that, mapped to a reference genome, provide biological insights at genomic, transcriptomic and epigenomic level. Typically the amount of reads that correctly maps to the reference genome ranges between 70% and 90%, leaving in some cases a consistent fraction of unmapped sequences. This 'misalignment' can be ascribed to low quality bases or sequence differences between the sample reads and the reference genome. Investigating the source of the unmapped reads is definitely important to better assess the quality of the whole experiment and to check for possible downstream or upstream 'contamination' from exogenous nucleic acids.
resultsHere we propose DecontaMiner, a tool to unravel the presence of contaminating sequences among the unmapped reads. It uses a subtraction approach to identify bacteria, fungi and viruses genome contamination. DecontaMiner generates several output files to track all the processed reads, and to provide a complete report of their characteristics. The good quality matches on microorganism genomes are counted and compared among samples. DecontaMiner builds an offline HTML page containing summary statistics and plots. The latter are obtained using the state-of-the-art D3 javascript libraries. DecontaMiner has been mainly used to detect contamination in human RNA-Seq data. The software is freely available at http://www-labgtp.na.icar.cnr.it/decontaminer .
conclusionsDecontaMiner is a tool designed and developed to investigate the presence of contaminating sequences in unmapped NGS data. It can suggest the presence of contaminating organisms in sequenced samples, that might derive either from laboratory contamination or from their biological source, and in both cases can be considered as worthy of further investigation and experimental validation. The novelty of DecontaMiner is mainly represented by its easy integration with the standard procedures of NGS data analysis, while providing a complete, reliable, and automatic pipeline.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.