Metagenomic reads of an 18th century parchment
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB32319 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR3858142_1.fastq.gz | Fastqsanger.gz | |||
| ERR3858142_2.fastq.gz | Fastqsanger.gz | |||
| ERR3858143_1.fastq.gz | Fastqsanger.gz | |||
| ERR3858143_2.fastq.gz | Fastqsanger.gz | |||
| ERR3858144_1.fastq.gz | Fastqsanger.gz |
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Project description:Parchment as a reservoir of ancient DNA for next generation sequencing
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Project description:The literature of environmental microbiology broadly discusses issues associated with microbial hazards in archives, but these publications are mainly devoted to paper documents. There are few articles on historical parchment documents, which used to be very important for the development of literature and the art of writing. These studies present a broad spectrum of methods for the assessment of biodeterioration hazards of the parchment document in question. They are based on both conventional microbiological methods and advanced techniques of molecular biology. Here, a qualitative analysis was conducted, based on genetic identification of bacteria and fungi present on the document as well as denaturing gradient gel electrophoresis profiling and examining the destructive potential of isolated microbes. Moreover, the study involved a quantitative and qualitative microbiological assessment of the indoor air in the room where the parchment was kept. The microbes with the highest destructive potential that were isolated from the investigated item were Bacillus cereus and Acinetobacter lwoffii bacteria and Penicillium chrysogenum,Chaetomium globosum, and Trichoderma longibrachiatum fungi. The presence of the B. cereuss train was particularly interesting since, under appropriate conditions, it leads to complete parchment degradation within several days.
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Project description:BackgroundIn recent years several different fields, such as ecology, medicine and microbiology, have experienced an unprecedented development due to the possibility of direct sequencing of microbioimic samples. Among problems that researchers in the field have to deal with, taxonomic classification of metagenomic reads is one of the most challenging. State of the art methods classify single reads with almost 100% precision. However, very often, the performance in terms of recall falls at about 50%. As a consequence, state-of-the-art methods are indeed capable of correctly classify only half of the reads in the sample. How to achieve better performances in terms of overall quality of classification remains a largely unsolved problem.ResultsIn this paper we propose a method for metagenomics CLassification Improvement with Overlapping Reads (CLIOR), that exploits the information carried by the overlapping reads graph of the input read dataset to improve recall, f-measure, and the estimated abundance of species. In this work, we applied CLIOR on top of the classification produced by the classifier Clark-l. Experiments on simulated and synthetic metagenomes show that CLIOR can lead to substantial improvement of the recall rate, sometimes doubling it. On average, on simulated datasets, the increase of recall is paired with an higher precision too, while on synthetic datasets it comes at expenses of a small loss of precision. On experiments on real metagenomes CLIOR is able to assign many more reads while keeping the abundance ratios in line with previous studies.ConclusionsOur results showed that with CLIOR is possible to boost the recall of a state-of-the-art metagenomic classifier by inferring and/or correcting the assignment of reads with missing or erroneous labeling. CLIOR is not restricted to the reads classification algorithm used in our experiments, but it may be applied to other methods too. Finally, CLIOR does not need large computational resources, and it can be run on a laptop.
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