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Datasets of the manuscript "Rational design of profile HMMs for sensitive and specific sequence detection with case studies applied to viruses, bacteriophages, and casposons"

<p><strong>DATASETS</strong></p> <p>Rational design of profile HMMs for sensitive and specific sequence detection with case studies applied to viruses, bacteriophages, and casposons</p> <p>Liliane S. Oliveira, Alejandro Reyes, Bas E. Dutilh and Arthur Gruber<sup>*</sup></p> <p>*&nbsp;Correspondence: <a href="mailto:argruber@usp.br">argruber@usp.br</a> (AG); Tel. +55 11 3091 7274</p> <p>&nbsp;</p> <p>Here we provide different data of <em>Microviridae</em>, <em>Flavivirus</em> and casposons used throughout the work:</p> <ul> <li>Microviridae folder <ul> <li>conserved_HMMs &ndash; profile HMMs constructed with TABAJARA in Conservation mode for <em>Microviridae</em></li> <li>discriminative_HMMs &ndash; profile HMMs constructed with TABAJARA in Discrimination mode for <em>Microviridae</em></li> <li>sequences &ndash; different sequence datasets and respective multiple sequence alignments <ul> <li>Microviridae_113-seq_training_set.fasta - 113 VP1 sequences covering diversity of the <em>Microviridae</em> family</li> <li>Microviridae_113-seq.aln &ndash; multiple sequence alignment of the 113-protein dataset</li> <li>Microviridae_1836-seq_testset.fasta - 1,836 sequence dataset covering 1,836 sequences of the major capsid protein (VP1) comprising 501 <em>Alpavirinae</em> sequences, 1,040 <em>Gokushovirinae</em> sequences and 295 <em>Pichovirinae</em> sequences</li> <li>Microviridae_1866-seq.aln - multiple sequence alignment of the 1,866-protein <em>Microviridae</em> dataset used in the experiment of Figure 4</li> </ul> </li> </ul> </li> <li>Flavivirus folder <ul> <li>conserved_HMMs &ndash; profile HMMs constructed with TABAJARA in Conservation mode for <em>Flavivirus</em></li> <li>discriminative_HMMs &ndash; profile HMMs constructed with TABAJARA in Discrimination mode for <em>Flavivirus</em> <ul> <li>full-length &ndash; models constructed from full-length protein sequences</li> <li>short - models constructed from selected short alignment blocks of the protein sequences</li> </ul> </li> <li>sequences &ndash; different sequence datasets and respective multiple sequence alignments <ul> <li>Flavivirus_127-seq_training_set.fasta - 127 polyprotein sequences covering species diversity of the genus <em>Flavivirus</em></li> <li>Flavivirus_127-seq.aln &ndash; multiple sequence alignment of the 127-protein dataset</li> <li>Flavivirus_6364-seq_testset.fasta - 6,364 sequence dataset covering species diversity of <em>Flavivirus</em>, including 3,919 of dengue virus (DENV), 327 of Zika virus (ZIKV), 63 of yellow fever virus (YFV), and the remaining 2,055 sequences covering other available flaviviruses</li> <li>Flavivirus_6364-seq.aln - multiple sequence alignment of the 6,364-protein <em>Flavivirus</em> dataset</li> </ul> </li> </ul> </li> <li>Casposons folder <ul> <li>casposon_generic_HMMs &ndash; profile HMMs constructed with TABAJARA in Discrimination mode for the generic detection of all casposons and discrimination from CRISPRs.</li> <li>casposon_family_discriminative_HMMs &ndash; profile HMMs constructed with TABAJARA in Discrimination mode for the specific discrimination among casposon families and from CRISPRs.</li> <li>sequences &ndash; different sequence datasets and respective multiple sequence alignments <ul> <li>casposons_crisprs.fasta &ndash; 106 Cas1 <em>bona fide</em> sequences derived from 52 CRISPRs and 54 casposons</li> <li>casposon_family_discrimination.aln - multiple sequence alignment of 52 <em>bona fide</em> CRISPR and 54 casposon sequences, with appropriate nomenclature to run TABAJARA for the discrimination of each casposon family.</li> <li>casposons_crisprs_discrimination.aln - multiple sequence alignment of 52 <em>bona fide</em> CRISPR and 54 casposon sequences, with appropriate nomenclature to run TABAJARA for discrimination of CRISPRs and casposons.</li> </ul> </li> </ul> </li> </ul>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
4

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