In recent years, the high throughput and the low cost of next-generation sequencing (NGS) technologies have led to an increase of the amount of (meta)genomic data, revolutionizing genomic research studies. However, the quality of sequencing data could be affected by experimental errors derived from defective methods and protocols. This represents a serious problem for the scientific community with a negative impact on the correctness of studies that involve genomic sequence analysis. As a countermeasure, several alignment and taxonomic classification tools have been developed to uncover and correct errors. In this critical review some of these integrated software tools and pipelines used to detect contaminations in reference genome databases and sequenced samples are reported. In particular, case studies of bacterial contaminations, contaminations of human origin, mitochondrial contaminations of ancient DNA, and cross contaminations are examined.

De Simone, G., Pasquadibisceglie, A., Proietto, R., Polticelli, F., Aime, S., J. M. Op den Camp, H., et al. (2020). Contaminations in (meta)genome data: An open issue for the scientific community. IUBMB LIFE, 72(4), 698-705 [10.1002/iub.2216].

Contaminations in (meta)genome data: An open issue for the scientific community

De Simone G.;Pasquadibisceglie A.;Polticelli F.;Ascenzi P.
2020-01-01

Abstract

In recent years, the high throughput and the low cost of next-generation sequencing (NGS) technologies have led to an increase of the amount of (meta)genomic data, revolutionizing genomic research studies. However, the quality of sequencing data could be affected by experimental errors derived from defective methods and protocols. This represents a serious problem for the scientific community with a negative impact on the correctness of studies that involve genomic sequence analysis. As a countermeasure, several alignment and taxonomic classification tools have been developed to uncover and correct errors. In this critical review some of these integrated software tools and pipelines used to detect contaminations in reference genome databases and sequenced samples are reported. In particular, case studies of bacterial contaminations, contaminations of human origin, mitochondrial contaminations of ancient DNA, and cross contaminations are examined.
2020
De Simone, G., Pasquadibisceglie, A., Proietto, R., Polticelli, F., Aime, S., J. M. Op den Camp, H., et al. (2020). Contaminations in (meta)genome data: An open issue for the scientific community. IUBMB LIFE, 72(4), 698-705 [10.1002/iub.2216].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/371288
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 10
  • ???jsp.display-item.citation.isi??? 9
social impact