2021
DOI: 10.1099/mgen.0.000603
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DiSCo: a sequence-based type-specific predictor of Dsr-dependent dissimilatory sulphur metabolism in microbial data

Abstract: Current methods in comparative genomic analyses for metabolic potential prediction of proteins involved in, or associated with the Dsr (dissimilatory sulphite reductase)-dependent dissimilatory sulphur metabolism are both time-intensive and computationally challenging, especially when considering metagenomic data. We developed DiSCo, a Dsr-dependent dissimilatory sulphur metabolism classification tool, which automatically identifies and classifies the protein type from sequence data. It takes user-supplied pro… Show more

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Cited by 26 publications
(34 citation statements)
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“…HMS-S-S was compared with Psi-BLAST, BLASTp and ProteinOrtho6 in terms of precision and recall in functional annotation (Figure 5). Comparison methods were chosen as they had also been used in the validation of DiSCo (Neukirchen & Sousa, 2021).…”
Section: Discussionmentioning
confidence: 99%
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“…HMS-S-S was compared with Psi-BLAST, BLASTp and ProteinOrtho6 in terms of precision and recall in functional annotation (Figure 5). Comparison methods were chosen as they had also been used in the validation of DiSCo (Neukirchen & Sousa, 2021).…”
Section: Discussionmentioning
confidence: 99%
“…This tool has the advantage of having been created for the classification into orthologue groups of very large numbers of genomes (Lechner et al, 2014). DiSCo is a novel tool that also created HMMs for the detection and classification of sulphur metabolism proteins with a specific focus on the Dsr and Qmo-Apr-Sat pathways (Neukirchen & Sousa, 2021). Sequences for method comparison were taken from the comparison data set.…”
Section: Methods Comparisonmentioning
confidence: 99%
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“…The genome sequence was annotated using the rast server version 2.0 [27], the dfast server version 1.2.4 [28] and Prokka version 1.14 [29] with the default settings. The annotation was manually curated based on the results from kegg [30], FeGenie [31] and DiSCo [32].…”
mentioning
confidence: 99%