PMC:7574920 / 57803-58709 JSONTXT

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T463","span":{"begin":103,"end":105},"obj":"http://purl.obolibrary.org/obo/CLO_0001382"},{"id":"T464","span":{"begin":371,"end":372},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"}],"text":"Except where otherwise noted, all data were analyzed with R (46) using the tidyverse (47) and ggplot2 (48) system or with GraphPad Prism. Sensitivity and specificity values were obtained from count tables as follows: Specificity of the RT-LAMP assay was calculated as the fraction of RT-qPCR–negative samples that were also negative in the RT-LAMP assay. Sensitivity for a given CT interval was calculated as the fraction of all samples with an RT-qPCR CT value in that interval that was positive in the RT-LAMP assay. In both cases, 95% confidence intervals were calculated by interpreting the fractions of counts as binomial rates and then using Wilson’s method for binomial confidence intervals as implemented in the R package binom (49). The R code used to perform analyses and produce figures can be found on GitHub, together with all data tables: https://github.com/anders-biostat/LAMP-Paper-Figures."}

{"project":"LitCovid-PubTator","denotations":[{"id":"397","span":{"begin":648,"end":654},"obj":"Disease"}],"attributes":[{"id":"A397","pred":"tao:has_database_id","subj":"397","obj":"MESH:D006527"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"Except where otherwise noted, all data were analyzed with R (46) using the tidyverse (47) and ggplot2 (48) system or with GraphPad Prism. Sensitivity and specificity values were obtained from count tables as follows: Specificity of the RT-LAMP assay was calculated as the fraction of RT-qPCR–negative samples that were also negative in the RT-LAMP assay. Sensitivity for a given CT interval was calculated as the fraction of all samples with an RT-qPCR CT value in that interval that was positive in the RT-LAMP assay. In both cases, 95% confidence intervals were calculated by interpreting the fractions of counts as binomial rates and then using Wilson’s method for binomial confidence intervals as implemented in the R package binom (49). The R code used to perform analyses and produce figures can be found on GitHub, together with all data tables: https://github.com/anders-biostat/LAMP-Paper-Figures."}

{"project":"LitCovid-PD-GO-BP","denotations":[{"id":"T303","span":{"begin":236,"end":238},"obj":"http://purl.obolibrary.org/obo/GO_0001171"},{"id":"T304","span":{"begin":284,"end":286},"obj":"http://purl.obolibrary.org/obo/GO_0001171"},{"id":"T305","span":{"begin":340,"end":342},"obj":"http://purl.obolibrary.org/obo/GO_0001171"},{"id":"T306","span":{"begin":445,"end":447},"obj":"http://purl.obolibrary.org/obo/GO_0001171"},{"id":"T307","span":{"begin":504,"end":506},"obj":"http://purl.obolibrary.org/obo/GO_0001171"}],"text":"Except where otherwise noted, all data were analyzed with R (46) using the tidyverse (47) and ggplot2 (48) system or with GraphPad Prism. Sensitivity and specificity values were obtained from count tables as follows: Specificity of the RT-LAMP assay was calculated as the fraction of RT-qPCR–negative samples that were also negative in the RT-LAMP assay. Sensitivity for a given CT interval was calculated as the fraction of all samples with an RT-qPCR CT value in that interval that was positive in the RT-LAMP assay. In both cases, 95% confidence intervals were calculated by interpreting the fractions of counts as binomial rates and then using Wilson’s method for binomial confidence intervals as implemented in the R package binom (49). The R code used to perform analyses and produce figures can be found on GitHub, together with all data tables: https://github.com/anders-biostat/LAMP-Paper-Figures."}

{"project":"LitCovid-sentences","denotations":[{"id":"T416","span":{"begin":0,"end":137},"obj":"Sentence"},{"id":"T417","span":{"begin":138,"end":216},"obj":"Sentence"},{"id":"T418","span":{"begin":217,"end":354},"obj":"Sentence"},{"id":"T419","span":{"begin":355,"end":518},"obj":"Sentence"},{"id":"T420","span":{"begin":519,"end":741},"obj":"Sentence"},{"id":"T421","span":{"begin":742,"end":906},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Except where otherwise noted, all data were analyzed with R (46) using the tidyverse (47) and ggplot2 (48) system or with GraphPad Prism. Sensitivity and specificity values were obtained from count tables as follows: Specificity of the RT-LAMP assay was calculated as the fraction of RT-qPCR–negative samples that were also negative in the RT-LAMP assay. Sensitivity for a given CT interval was calculated as the fraction of all samples with an RT-qPCR CT value in that interval that was positive in the RT-LAMP assay. In both cases, 95% confidence intervals were calculated by interpreting the fractions of counts as binomial rates and then using Wilson’s method for binomial confidence intervals as implemented in the R package binom (49). The R code used to perform analyses and produce figures can be found on GitHub, together with all data tables: https://github.com/anders-biostat/LAMP-Paper-Figures."}