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.

PENGARUH TERAPI TERTAWA TERHADAP PENURUNAN TEKANAN DARAH LANSIA DI UPT PANTI WREDHA BUDHI DHARMA YOGYAKARTA

2019 ◽  
Vol 13 (1) ◽  
Author(s):  
Niken Setyaningrum ◽  
Andri Setyorini ◽  
Fachruddin Tri Fitrianta
Keyword(s):  
Blood Pressure ◽  
Data Analysis ◽  
The Elderly ◽  
Control Group ◽  
Group Comparison ◽  
Control Blood Pressure ◽  
Men And Women ◽  
Treatment Of Hypertension ◽  
Before And After ◽  
The Difference

ABSTRACTBackground: Hypertension is one of the most common diseases, because this disease is suffered byboth men and women, as well as adults and young people. Treatment of hypertension does not onlyrely on medications from the doctor or regulate diet alone, but it is also important to make our bodyalways relaxed. Laughter can help to control blood pressure by reducing endocrine stress andcreating a relaxed condition to deal with relaxation.Objective: The general objective of the study was to determine the effect of laughter therapy ondecreasing elderly blood pressure in UPT Panti Wredha Budhi Dharma Yogyakarta.Methods: The design used in this study is a pre-experimental design study with one group pre-posttestresearch design where there is no control group (comparison). The population in this study wereelderly aged over> 60 years at 55 UPT Panti Wredha Budhi Dharma Yogyakarta. The method oftaking in this study uses total sampling. The sample in this study were 55 elderly. Data analysis wasused to determine the difference in blood pressure before and after laughing therapy with a ratio datascale that was using Pairs T-TestResult: There is an effect of laughing therapy on blood pressure in the elderly at UPT Panti WredhaBudhi Dharma Yogyakarta marked with a significant value of 0.000 (P <0.05)

scholarly journals Malpigmentation of Common Sole (Solea solea) during Metamorphosis Is Associated with Differential Synaptic-Related Gene Expression

Animals ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 2273
Author(s):  
Menelaos Kavouras ◽  
Emmanouil E. Malandrakis ◽  
Ewout Blom ◽  
Kyriaki Tsilika ◽  
Theodoros Danis ◽  
...  
Keyword(s):  
Gene Expression ◽  
Nervous System ◽  
De Novo ◽  
Close Association ◽  
Ionic Channels ◽  
Long Term Potentiation ◽  
General Term ◽  
The Difference ◽  
Common Sole

In farmed flatfish, such as common sole, color disturbances are common. Dyschromia is a general term that includes the color defects on the blind and ocular sides of the fish. The purpose was to examine the difference in gene expression between normal pigmented and juveniles who present ambicoloration. The analysis was carried out with next-generation sequencing techniques and de novo assembly of the transcriptome. Transcripts that showed significant differences (FDR < 0.05) in the expression between the two groups, were related to those of zebrafish (Danio rerio), functionally identified, and classified into categories of the gene ontology. The results revealed that ambicolorated juveniles exhibit a divergent function, mainly of the central nervous system at the synaptic level, as well as the ionic channels. The close association of chromophore cells with the growth of nerve cells and the nervous system was recorded. The pathway, glutamate binding–activation of AMPA and NMDA receptors–long-term stimulation of postsynaptic potential–LTP (long term potentiation)–plasticity of synapses, appears to be affected. In addition, the development of synapses also seems to be affected by the interaction of the LGI (leucine-rich glioma inactivated) protein family with the ADAM (a disintegrin and metalloprotease) ones.

scholarly journals Impact of RNA-seq data analysis algorithms on gene expression estimation and downstream prediction

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Li Tong ◽  
◽  
Po-Yen Wu ◽  
John H. Phan ◽  
Hamid R. Hassazadeh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Disease Outcome ◽  
Rna Seq ◽  
Next Generation Sequencing Technology ◽  
Normalization Methods ◽  
The Us ◽  
Sequencing Quality ◽  
Improved Accuracy ◽  
The Impact

Abstract To use next-generation sequencing technology such as RNA-seq for medical and health applications, choosing proper analysis methods for biomarker identification remains a critical challenge for most users. The US Food and Drug Administration (FDA) has led the Sequencing Quality Control (SEQC) project to conduct a comprehensive investigation of 278 representative RNA-seq data analysis pipelines consisting of 13 sequence mapping, three quantification, and seven normalization methods. In this article, we focused on the impact of the joint effects of RNA-seq pipelines on gene expression estimation as well as the downstream prediction of disease outcomes. First, we developed and applied three metrics (i.e., accuracy, precision, and reliability) to quantitatively evaluate each pipeline’s performance on gene expression estimation. We then investigated the correlation between the proposed metrics and the downstream prediction performance using two real-world cancer datasets (i.e., SEQC neuroblastoma dataset and the NIH/NCI TCGA lung adenocarcinoma dataset). We found that RNA-seq pipeline components jointly and significantly impacted the accuracy of gene expression estimation, and its impact was extended to the downstream prediction of these cancer outcomes. Specifically, RNA-seq pipelines that produced more accurate, precise, and reliable gene expression estimation tended to perform better in the prediction of disease outcome. In the end, we provided scenarios as guidelines for users to use these three metrics to select sensible RNA-seq pipelines for the improved accuracy, precision, and reliability of gene expression estimation, which lead to the improved downstream gene expression-based prediction of disease outcome.

Computational Strategies for Analyzing Data in Gene Expression Microarray Experiments

2003 ◽  
Vol 01 (03) ◽  
pp. 541-586 ◽  
Author(s):  
Tero Aittokallio ◽  
Markus Kurki ◽  
Olli Nevalainen ◽  
Tuomas Nikula ◽  
Anne West ◽  
...  
Keyword(s):  
Gene Expression ◽  
Data Analysis ◽  
Microarray Data ◽  
Microarray Data Analysis ◽  
Biological Research ◽  
Microarray Experiments ◽  
Dna Microarray Data ◽  
Open Questions ◽  
Analysis Technique ◽  
Wide Range

Microarray analysis has become a widely used method for generating gene expression data on a genomic scale. Microarrays have been enthusiastically applied in many fields of biological research, even though several open questions remain about the analysis of such data. A wide range of approaches are available for computational analysis, but no general consensus exists as to standard for microarray data analysis protocol. Consequently, the choice of data analysis technique is a crucial element depending both on the data and on the goals of the experiment. Therefore, basic understanding of bioinformatics is required for optimal experimental design and meaningful interpretation of the results. This review summarizes some of the common themes in DNA microarray data analysis, including data normalization and detection of differential expression. Algorithms are demonstrated by analyzing cDNA microarray data from an experiment monitoring gene expression in T helper cells. Several computational biology strategies, along with their relative merits, are overviewed and potential areas for additional research discussed. The goal of the review is to provide a computational framework for applying and evaluating such bioinformatics strategies. Solid knowledge of microarray informatics contributes to the implementation of more efficient computational protocols for the given data obtained through microarray experiments.

scholarly journals What happens when data are fitted to the wrong equation?

1978 ◽  
Vol 171 (3) ◽  
pp. 513-517 ◽  
Author(s):  
K J Ellis ◽  
R G Duggleby
Keyword(s):  
Data Analysis ◽  
Random Errors ◽  
Mathematical Equation ◽  
Error Structure ◽  
Weighting Factors ◽  
The Difference ◽  
Residual Plots

In many problems of data analysis it is necessary to fit the data to a mathematical equation. Random errors of measurement will be responsible for deviations between the data and the equation, but superimposed on this there may be deviations that result from the equation being an inadequate description of the system from which the data were obtained. Plots of the residual (i.e. the difference between the experimental and calculated values of the dependent variable) against each of the experimental variables have been previously used to detect a misfit between the data and the equation. In the present paper, we show that the shape of the residual plots may be used as a guide in choosing a more appropriate equation. In addition, residual plots give useful information on the error structure of the data, and hence the weighting factors that should be used in the analysis.

PSIV-6 Differential gene expression of fibro/adipogenic progenitors between Wagyu and Brahman cattle: A possible contribution to their different meat quality

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 301-301
Author(s):  
Chaoyang Li ◽  
Qianglin Liu ◽  
Matt Welborn ◽  
Leshan Wang ◽  
Yuxia Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Meat Quality ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cattle Breed ◽  
Intramuscular Fat ◽  
Brahman Cattle ◽  
Differential Gene ◽  
The Difference

Abstract The amount of intramuscular fat directly influences the meat quality. However, significant differences in the ability to accumulate intramuscular fat are present among different beef cattle breeds. While Wagyu, a cattle breed that originated from Japan, is renowned for abundant intramuscular fat, Brahman cattle generally have very little intramuscular fat accumulation and produce tougher meat. We identified that bovine intramuscular fat is derived from a group of bipotent progenitor cells named fibro/adipogenic progenitors (FAPs) which also give rise to fibroblasts. Thus, the variation in intramuscular fat development between Wagyu and Brahman is likely attributed to the difference in FAPs between these two breeds. In order to understand the gene expression difference between FAPs of the two breeds, single-cell RNA-seq was performed using total single-nucleated cells isolated from the longissimus muscle of young purebred Wagyu, purebred Brahman, and Wagyu-Brahman cross cattle. FAPs constitute the largest single-nucleated cell population in both Wagyu and Brahman skeletal muscle. Multiple subpopulations of FAPs with different gene expression profiles were identified, suggesting that FAP is a heterogeneous population. A unique FAP cluster expressing lower levels of fibrillar collagen and extracellular remodeling enzyme genes but higher levels of select proadipogenic genes was identified exclusively in Wagyu skeletal muscle, which likely contributes to the robust intramuscular adipogenic efficiency of Wagyu FAPs. In conclusion, the difference in the cellular composition and gene expression of FAPs between Wagyu and Brahman cattle likely contribute to their distinct meat quality.

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