PubMed · 16089009
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Greg Wilson. 2005-07-28. Software solutions.. https://doi.org/10.1038/nj7050-600b
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MOTIVATION: Malaria, caused by Plasmodium parasites, imposes a significant public health burden. While Plasmodium falciparum remains the primary target of elimination strategies due to its high mortality rate, lesser-known species such as P. malariae, P. vivax, and P. knowlesi continue to contribute to substantial human morbidity. Genomic approaches, including whole-genome sequencing, offer powerful tools for understanding the biology, transmission, and emerging drug resistance of these neglected Plasmodium species. However, there is an urgent need for informatic tools to summarize and visualize the high-dimensional and complex genomic data generated. RESULTS: We developed Malaria-GENOMAP, a user-friendly web-based tool, which integrates genomic variant data, such as allele frequencies, with geographical maps and chromosome-wide to gene views for in-depth exploration. The tool includes variation from P. knowlesi (n = 139), P. malariae (n = 158), P. ovale curtisi (n = 36), P. ovale wallikeri (n = 47), P. simium (n = 38), and P. vivax (n = 1359). It enables the investigation of population structure, geographic associations of mutations, and putative drug resistance markers, offering valuable insights for malaria control efforts. AVAILABILITY AND IMPLEMENTATION: Malaria-GENOMAP is available online at https://genomics.lshtm.ac.uk/malaria-genomaps.
OBJECTIVE: To develop a comprehensive instrument assessing quality of health-related web sites. METHODS: Phase I consisted of a literature review to identify constructs thought to indicate web site quality and to identify items. During content analysis, duplicate items were eliminated and items that were not clear, meaningful, or measurable were reworded or removed. Some items were generated by the authors. Phase II: a panel consisting of six healthcare and MIS reviewers was convened to assess each item for its relevance and importance to the construct and to assess item clarity and measurement feasibility. RESULTS: Three hundred and eighty-four items were generated from 26 sources. The initial content analysis reduced the scale to 104 items. Four of the six expert reviewers responded; high concordance on the relevance, importance and measurement feasibility of each item was observed: 3 out of 4, or all raters agreed on 76-85% of items. Based on the panel ratings, 9 items were removed, 3 added, and 10 revised. The WebMedQual consists of 8 categories, 8 sub-categories, 95 items and 3 supplemental items to assess web site quality. The constructs are: content (19 items), authority of source (18 items), design (19 items), accessibility and availability (6 items), links (4 items), user support (9 items), confidentiality and privacy (17 items), e-commerce (6 items). CONCLUSION: The "WebMedQual" represents a first step toward a comprehensive and standard quality assessment of health web sites. This scale will allow relatively easy assessment of quality with possible numeric scoring.
SNPServer is a real-time flexible tool for the discovery of SNPs (single nucleotide polymorphisms) within DNA sequence data. The program uses BLAST, to identify related sequences, and CAP3, to cluster and align these sequences. The alignments are parsed to the SNP discovery software autoSNP, a program that detects SNPs and insertion/deletion polymorphisms (indels). Alternatively, lists of related sequences or pre-assembled sequences may be entered for SNP discovery. SNPServer and autoSNP use redundancy to differentiate between candidate SNPs and sequence errors. For each candidate SNP, two measures of confidence are calculated, the redundancy of the polymorphism at a SNP locus and the co-segregation of the candidate SNP with other SNPs in the alignment. SNPServer is available at http://hornbill.cspp.latrobe.edu.au/snpdiscovery.html.