scholarly journals qPCR data analysis: Better results through iconoclasm

2019 ◽  
Vol 17 ◽  
pp. 100084 ◽  
Author(s):  
Joel Tellinghuisen ◽  
Andrej-Nikolai Spiess
Keyword(s):  
Data Analysis ◽  
Qpcr Data

scholarly journals Pairwise Efficiency: A new mathematical approach to qPCR data analysis increases the precision of the classical calibration curve assay

2018 ◽  
Author(s):  
Yulia Panina ◽  
Arno Germond ◽  
Brit G. David ◽  
Tomonobu M. Watanabe ◽  
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Calibration Curve ◽  
Quantitative Polymerase Chain Reaction ◽  
Expression Ratio ◽  
Qpcr Data ◽  
Novel Approach ◽  
Data Points ◽  
Polymerase Chain ◽  
New Formula

ABSTRACTThe real-time quantitative polymerase chain reaction (qPCR) is routinely used for quantification of nucleic acids and is considered the gold standard in the field of relative nucleic acid measurements. The efficiency of the qPCR reaction is one of the most important parameters that needs to be determined, reported, and incorporated into data analysis in any qPCR experiment. The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines recognize the calibration curve as the method of choice for estimation of qPCR efficiency. The precision of this method has been reported to be between SD=0.007 (3 replicates) and SD=0.022 (no replicates). In this manuscript we present a novel approach to analysing qPCR data obtained by running a dilution series. Unlike previously developed methods, our method relies on a new formula that describes pairwise relationships between data points on separate amplification curves and thus operates extensive statistics (hundreds of estimations). The comparison of our method with classical calibration curve by Monte Carlo simulation shows that our approach can almost double the precision of efficiency and gene expression ratio estimations on the same dataset.

Quantitative PCR (qPCR) Data Analysis of SOD and its Activity and Expression in Elettaria cardamomum under Biotic Stress

2014 ◽  
Vol 11 (2) ◽  
pp. 435-440
Author(s):  
Susan George ◽  
S. Bhasker ◽  
R. Mamkulathil Devasia ◽  
H. Madhav Warrier ◽  
Mohankumar Chinnamma
Keyword(s):  
Data Analysis ◽  
Quantitative Pcr ◽  
Biotic Stress ◽  
Qpcr Data ◽  
Elettaria Cardamomum

scholarly journals Use and Misuse of Cq in qPCR Data Analysis and Reporting

Life ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 496
Author(s):  
Adrián Ruiz-Villalba ◽  
Jan M. Ruijter ◽  
Maurice J. B. van den Hoff
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Concentration Ratio ◽  
Amplification Curve ◽  
Qpcr Data ◽  
Pcr Efficiency ◽  
Qpcr Analysis ◽  
Sampling Variation ◽  
The Difference ◽  
Threshold Setting

In the analysis of quantitative PCR (qPCR) data, the quantification cycle (Cq) indicates the position of the amplification curve with respect to the cycle axis. Because Cq is directly related to the starting concentration of the target, and the difference in Cq values is related to the starting concentration ratio, the only results of qPCR analysis reported are often Cq, ΔCq or ΔΔCq values. However, reporting of Cq values ignores the fact that Cq values may differ between runs and machines, and, therefore, cannot be compared between laboratories. Moreover, Cq values are highly dependent on the PCR efficiency, which differs between assays and may differ between samples. Interpreting reported Cq values, assuming a 100% efficient PCR, may lead to assumed gene expression ratios that are 100-fold off. This review describes how differences in quantification threshold setting, PCR efficiency, starting material, PCR artefacts, pipetting errors and sampling variation are at the origin of differences and variability in Cq values and discusses the limits to the interpretation of observed Cq values. These issues can be avoided by calculating efficiency-corrected starting concentrations per reaction. The reporting of gene expression ratios and fold difference between treatments can then easily be based on these starting concentrations.

scholarly journals Auto-qPCR; a python-based web app for automated and reproducible analysis of qPCR data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gilles Maussion ◽  
Rhalena A. Thomas ◽  
Iveta Demirova ◽  
Gracia Gu ◽  
Eddie Cai ◽  
...  
Keyword(s):  
Data Analysis ◽  
Molecular Biology ◽  
Reference Sample ◽  
Qpcr Data ◽  
Dna And Rna ◽  
Processing Modes ◽  
Duplication Events ◽  
Automate Processing ◽  
Reproducible Analysis ◽  
Programming Knowledge

AbstractQuantifying changes in DNA and RNA levels is essential in numerous molecular biology protocols. Quantitative real time PCR (qPCR) techniques have evolved to become commonplace, however, data analysis includes many time-consuming and cumbersome steps, which can lead to mistakes and misinterpretation of data. To address these bottlenecks, we have developed an open-source Python software to automate processing of result spreadsheets from qPCR machines, employing calculations usually performed manually. Auto-qPCR is a tool that saves time when computing qPCR data, helping to ensure reproducibility of qPCR experiment analyses. Our web-based app (https://auto-q-pcr.com/) is easy to use and does not require programming knowledge or software installation. Using Auto-qPCR, we provide examples of data treatment, display and statistical analyses for four different data processing modes within one program: (1) DNA quantification to identify genomic deletion or duplication events; (2) assessment of gene expression levels using an absolute model, and relative quantification (3) with or (4) without a reference sample. Our open access Auto-qPCR software saves the time of manual data analysis and provides a more systematic workflow, minimizing the risk of errors. Our program constitutes a new tool that can be incorporated into bioinformatic and molecular biology pipelines in clinical and research labs.

scholarly journals Study Design and qPCR Data Analysis Guidelines for Reliable Circulating miRNA Biomarker Experiments: A Review

2018 ◽  
Vol 64 (9) ◽  
pp. 1308-1318 ◽  
Author(s):  
Maurice W J de Ronde ◽  
Jan M Ruijter ◽  
Perry D Moerland ◽  
Esther E Creemers ◽  
Sara-Joan Pinto-Sietsma
Keyword(s):  
Data Analysis ◽  
Experimental Design ◽  
Point Of View ◽  
Circulating Microrna ◽  
Circulating Mirnas ◽  
Experimental Conditions ◽  
Qpcr Data ◽  
Validation Phase ◽  
Analysis Methods ◽  
Discovery Phase

Abstract BACKGROUND In the past decade, the search for circulating microRNA (miRNA) biomarkers has yielded numerous associations between miRNAs and different types of disease. However, many of these relations could not be replicated in subsequent studies under similar experimental conditions. Although this lack of replicability may be explained by the variation in experimental design and analysis methods, guidelines on the most appropriate design and analysis methods to study circulating miRNAs are scarce. CONTENT miRNA biomarker experiments generally consist of a discovery phase and a validation phase. In the discovery phase, typically hundreds of miRNAs are measured in parallel to identify candidate biomarkers. Because of the costs of such high-throughput experiments, the number of individuals included in those studies is often too small, which can easily lead to false positives and false negatives. In the validation phase, a small number of identified biomarker candidates are measured in a large cohort of cases and controls, generally by quantitative PCR (qPCR). Although qPCR is a sensitive method to measure miRNAs in the circulation, experimental design and qPCR data analysis remain challenging. Omitting some crucial steps in the design and analysis of the qPCR experiment or performing them incorrectly can cause serious biases, ultimately leading to false conclusions. SUMMARY In this review, we aim to expose and discuss the most common sources of interstudy variation in miRNA research from a methodological point of view and to provide guidelines on how to perform these steps correctly to increase replicability of studies on circulating miRNAs.

Microchemical imaging in biomedical research

1992 ◽  
Vol 50 (2) ◽  
pp. 1118-1119
Author(s):  
P. Ingram
Keyword(s):  
Data Analysis ◽  
Electron Probe ◽  
The Other ◽  
X Ray ◽  
Cell Element ◽  
Physiological Information ◽  
Functional States ◽  
Elemental Maps ◽  
Electron Energy Loss ◽  
Secondary Ion

It is well established that unique physiological information can be obtained by rapidly freezing cells in various functional states and analyzing the cell element content and distribution by electron probe x-ray microanalysis. (The other techniques of microanalysis that are amenable to imaging, such as electron energy loss spectroscopy, secondary ion mass spectroscopy, particle induced x-ray emission etc., are not addressed in this tutorial.) However, the usual processes of data acquisition are labor intensive and lengthy, requiring that x-ray counts be collected from individually selected regions of each cell in question and that data analysis be performed subsequent to data collection. A judicious combination of quantitative elemental maps and static raster probes adds not only an additional overall perception of what is occurring during a particular biological manipulation or event, but substantially increases data productivity. Recent advances in microcomputer instrumentation and software have made readily feasible the acquisition and processing of digital quantitative x-ray maps of one to several cells.

Perceptions of a Collaborative Professional Learning Program: Seeing the “Bigger Picture”

2020 ◽  
Vol 5 (1) ◽  
pp. 290-303
Author(s):  
P. Charlie Buckley ◽  
Kimberly A. Murza ◽  
Tami Cassel
Keyword(s):  
Data Analysis ◽  
Professional Learning ◽  
Social Communication ◽  
Special Educators ◽  
Service Providers ◽  
Integrative Approach ◽  
Theory Approach ◽  
Learning Program ◽  
Speech Language Pathologists ◽  
Related Service

Purpose The purpose of this study was to explore the perceptions of special education practitioners (i.e., speech-language pathologists, special educators, para-educators, and other related service providers) on their role as communication partners after participation in the Social Communication and Engagement Triad (Buckley et al., 2015 ) yearlong professional learning program. Method A qualitative approach using interviews and purposeful sampling was used. A total of 22 participants who completed participation in either Year 1 or Year 2 of the program were interviewed. Participants were speech-language pathologists, special educators, para-educators, and other related service providers. Using a grounded theory approach (Glaser & Strauss, 1967 ) to data analysis, open, axial, and selective coding procedures were followed. Results Three themes emerged from the data analysis and included engagement as the goal, role as a communication partner, and importance of collaboration. Conclusions Findings supported the notion that educators see the value of an integrative approach to service delivery, supporting students' social communication and engagement across the school day but also recognizing the challenges they face in making this a reality.

Communicative Performance of Adolescents with Severe Speech Impairment

1989 ◽  
Vol 54 (3) ◽  
pp. 403-421 ◽  
Author(s):  
Beth M. Dalton ◽  
Jan L. Bedrosian
Keyword(s):  
Data Analysis ◽  
Peer Interactions ◽  
Consistent Pattern ◽  
Clinical Implications ◽  
Speech Impairment ◽  
Communication Mode ◽  
Mode Function ◽  
Communicative Performance ◽  
Therapy Room ◽  
Communication Board

The communicative performance of 4 preoperational-level adolescents, using limited speech, gestures, and communication board techniques, was examined in a two-part investigation. In Part 1, each subject participated in an academic interaction with a teacher in a therapy room. Data were transcribed and coded for communication mode, function, and role. Two subjects were found to predominantly use the speech mode, while the remaining 2 predominantly used board and one other mode. The majority of productions consisted of responses to requests, and the initiator role was infrequently occupied. These findings were similar to those reported in previous investigations conducted in classroom settings. In Part 2, another examination of the communicative performance of these subjects was conducted in spontaneous interactions involving speaking and nonspeaking peers in a therapy room. Using the same data analysis procedures, gesture and speech modes predominated for 3 of the subjects in the nonspeaking peer interactions. The remaining subject exhibited minimal interaction. No consistent pattern of mode usage was exhibited across the speaking peer interactions. In the nonspeaking peer interactions, requests predominated. In contrast, a variety of communication functions was exhibited in the speaking peer interactions. Both the initiator and the maintainer roles were occupied in the majority of interactions. Pertinent variables and clinical implications are discussed.

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