Auto-qPCR: A Python based web app for automated and reproducible analysis of qPCR data

Quantifying changes in DNA and RNA levels is an essential component of any molecular biology toolkit. Quantitative real time PCR (qPCR) techniques, in both clinical and basic research labs, have evolved to become both routine and standardized. However, the analysis of qPCR data includes many steps that are time consuming and cumbersome, which can lead to mistakes and misinterpretation of data. To address this bottleneck, we have developed an open source software, written in Python, to automate the processing of csv output files from any qPCR machine, using standard calculations that are usually performed manually. Auto-qPCR is a tool that saves time when computing this type of data, helping to ensure standardization of qPCR experiment analyses. Unlike other software packages that process qPCR data, our web-based app (http://auto-q-pcr.com/) is easy to use and does not require programming knowledge or software installation. Additionally, we provide examples of four different data processing modes within one program: (1) cDNA quantification to identify genomic deletion or duplication events, (2) assessment of gene expression levels using an absolute model, (3) relative quantification, and (4) relative quantification with a reference sample. Auto-qPCR also includes options for statistical analysis of the data. Using this software, we performed analysis of differential gene expression following an initial data processing and provide graphs of the findings prepared through the Auto-qPCR program. Thus, our open access Auto-qPCR software saves the time of manual data analysis and provides a more systematic workflow, minimizing the risk of errors when done manually. Our program constitutes a new tool that can be incorporated into bioinformatic and molecular biology pipelines in clinical and research labs.