Increasingly powerful techniques for high-throughput sequencing open the possibility to comprehensively characterize microbial communities, including rare species. However, a still unresolved issue are the substantial error rates in the experimental process generating these sequences. To overcome these limitations we propose an approach, where each sample is split and the same amplification and sequencing protocol is applied to both halves. This procedure should allow to detect likely PCR and sequencing artifacts, and true rare species by comparison of the results of both parts. The AmpliconDuo package, whereas amplicon duo from here on refers to the two amplicon data sets of a split sample, is intended to help interpret the obtained read frequency distribution across split samples, and to filter the false positive reads.

Functions to simplify and standardise antimicrobial resistance (AMR)
  data analysis and to work with microbial and antimicrobial properties by
  using evidence-based methods, as described in <doi:10.18637/jss.v104.i03>.

Automates regression testing of package 'allelematch'. Over
    2500 tests cover all functions in 'allelematch', reproduce the
    examples from the documentation, and include negative tests. The
    implementation is based on 'testthat'.

Provides functions to compute various clinical scores used in healthcare.
            These include the Charlson Comorbidity Index (CCI), predicting 10-year survival in patients with multiple comorbidities; 
            the EPICES score, an individual indicator of precariousness considering its multidimensional nature;
            the MELD score for chronic liver disease severity; the Alternative Fistula Risk Score (a-FRS) for postoperative pancreatic fistula risk;
            and the Distal Pancreatectomy Fistula Risk Score (D-FRS) for risk following distal pancreatectomy.
            For detailed methodology, refer to Charlson et al. (1987) <doi:10.1016/0021-9681(87)90171-8> ,
            Sass et al. (2006) <doi:10.1007/s10332-006-0131-5>, 
            Kamath et al. (2001) <doi:10.1053/jhep.2001.22172>,
            Kim et al. (2008) <doi:10.1056/NEJMoa0801209>
            Kim et al. (2021) <doi:10.1053/j.gastro.2021.08.050>,
            Mungroop et al. (2019) <doi:10.1097/SLA.0000000000002620>,
            and de Pastena et al. (2023) <doi:10.1097/SLA.0000000000005497>..