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Classically, the quantitative endpoint of qPCR is the threshold cycle (C<jats:sub>T<\/jats:sub>) that ignores differences in amplification efficiency among many other drawbacks. While other methods have been developed to analyze qPCR results, none has statistically proven to perform better than the C<jats:sub>T<\/jats:sub> method. Therefore, we aimed to develop a new qPCR analysis method that overcomes the limitations of the C<jats:sub>T<\/jats:sub> method. Our <jats:italic>f<\/jats:italic><jats:sub>0<\/jats:sub>% [eff naught percent] method depends on a modified flexible sigmoid function to fit the amplification curve with a linear part to subtract the background noise. Then, the initial fluorescence is estimated and reported as a percentage of the predicted maximum fluorescence (<jats:italic>f<\/jats:italic><jats:sub>0<\/jats:sub>%).<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>The performance of the new <jats:italic>f<\/jats:italic><jats:sub>0<\/jats:sub>% method was compared against the C<jats:sub>T<\/jats:sub> method along with another two outstanding methods\u2014LinRegPCR and Cy<jats:sub>0<\/jats:sub>. The comparison regarded absolute and relative quantifications and used 20 dilution curves obtained from 7 different datasets that utilize different DNA-binding dyes. In the case of absolute quantification, <jats:italic>f<\/jats:italic><jats:sub>0<\/jats:sub>% reduced CV%, variance, and absolute relative error by 1.66, 2.78, and 1.8 folds relative to C<jats:sub>T<\/jats:sub>; and by 1.65, 2.61, and 1.71 folds relative to LinRegPCR, respectively. While, regarding relative quantification, <jats:italic>f<\/jats:italic><jats:sub>0<\/jats:sub>% reduced CV% by 1.76, 1.55, and 1.25 folds and variance by 3.13, 2.31, and 1.57 folds regarding C<jats:sub>T<\/jats:sub>, LinRegPCR, and Cy<jats:sub>0<\/jats:sub>, respectively. Finally, <jats:italic>f<\/jats:italic><jats:sub>0<\/jats:sub>% reduced the absolute relative error caused by LinRegPCR by 1.83 folds.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>We recommend using the <jats:italic>f<\/jats:italic><jats:sub>0<\/jats:sub>% method to analyze and report qPCR results based on its reported advantages. Finally, to simplify the usage of the <jats:italic>f<\/jats:italic><jats:sub>0<\/jats:sub>% method, it was implemented in a macro-enabled Excel file with a user manual located on <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/Mahmoud0Gamal\/F0-perc\/releases\">https:\/\/github.com\/Mahmoud0Gamal\/F0-perc\/releases<\/jats:ext-link>.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-024-05630-y","type":"journal-article","created":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T10:02:29Z","timestamp":1704967349000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["Introducing the f0% method: a reliable and accurate approach for qPCR analysis"],"prefix":"10.1186","volume":"25","author":[{"given":"Mahmoud","family":"Gamal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marwa A.","family":"Ibrahim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,1,11]]},"reference":[{"key":"5630_CR1","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1016\/j.cca.2014.10.017","volume":"439","author":"E Navarro","year":"2015","unstructured":"Navarro E, Serrano-Heras G, Casta\u00f1o MJ, Solera J. 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