Q-Gene: processing quantitative real-time RT-PCR data

SUMMARY: Q-Gene is an application for the processing of quantitative real-time RT-PCR data. It offers the user the possibility to freely choose between two principally different procedures to calculate normalized gene expressions as either means of Normalized Expressions or Mean Normalized Expressions. In this contribution it will be shown that the calculation of Mean Normalized Expressions has to be used for processing simplex PCR data, while multiplex PCR data should preferably be processed by calculating Normalized Expressions. The two procedures, which are currently in widespread use and regarded as more or less equivalent alternatives, should therefore specifically be applied according to the quantification procedure used. AVAILABILITY: Web access to this program is provided at http://www.biotechniques.com/softlib/qgene.html     

Statistical methods for efficiency adjusted real-time PCR quantification

The statistical treatment for hypothesis testing using real-time PCR data is a challenge for quantification of gene expression. One has to consider two key factors in precise statistical analysis of real-time PCR data: a well-defined statistical model and the integration of amplification efficiency (AE) into the model. Previous publications in real-time PCR data analysis often fall short in integrating the AE into the model. Novel, user-friendly, and universal AE-integrated statistical methods were developed for real-time PCR data analysis with four goals. First, we addressed the definition of AE, introduced the concept of efficiency-adjusted Delta Delta Ct, and developed a general mathematical method for its calculation. Second, we developed several linear combination approaches for the estimation of efficiency adjusted Delta Delta Ct and statistical significance for hypothesis testing based on different mathematical formulae and experimental designs. Statistical methods were also adopted to estimate the AE and its equivalence among the samples. A weighted Delta Delta Ct method was introduced to analyze the data with multiple internal controls. Third, we implemented the linear models with SAS programs and analyzed a set of data for each model. In order to allow other researchers to use and compare different approaches, SAS programs are included in the Supporting Information. Fourth, the results from analysis of different statistical models were compared and discussed. Our results underline the differences between the efficiency adjusted Delta Delta Ct methods and previously published methods, thereby better identifying and controlling the source of errors introduced by real-time PCR data analysis.     

SoFAR: software for fully automatic evaluation of real-time PCR data

Quantitative real-time PCR has proven to be an extremely useful technique in life sciences for many applications. Although a lot of attention has been paid to the optimization of the assay conditions, the analysis of the data acquired is often done with software tools that do not make optimum use of the information provided by the data. Particularly, this is the case for high-throughput analysis, which requires a careful characterization and interpretation of the complete data by suitable software. Here we present a software solution for the robust, reliable, accurate, and fast evaluation of real-time PCR data, called SoFAR. The software automatically evaluates the data acquired with the LightCycler system. It applies new algorithms for an adaptive background correction of signal trends, the calculation of the effective signal noise, the automated identification of the exponential phases, the adaptive smoothing of the raw data, and the correction of melting curve data. Finally, it provides information regarding the validity of the results obtained. The SoFAR software minimizes the time required for evaluation and increases the accuracy and reliability of the results. The software is available upon request.     

Computer controlled cryo-electron microscopy--TOM² a software package for high-throughput applications

Automated data acquisition expedites structural studies by electron microscopy and it allows to collect data sets of unprecedented size and consistent quality. In electron tomography it greatly facilitates the systematic exploration of large cellular landscapes and in single particle analysis it allows to generate data sets for an exhaustive classification of coexisting molecular states. Here we describe a novel software philosophy and architecture that can be used for a great variety of automated data acquisition scenarios. Based on our original software package TOM, the new TOM(2) package has been designed in an object-oriented way. The whole program can be seen as a collection of self-sufficient modules with defined relationships acting in a concerted manner. It subdivides data acquisition into a set of hierarchical tasks, bonding data structure and the operations to be performed tightly together. To demonstrate its capacity for high-throughput data acquisition it has been used in conjunction with instrumentation combining the latest technological achievements in electron optics, cryogenics and robotics. Its performance is demonstrated with a single particle analysis case study and with a batch tomography application.     

Standardisation of data from real-time quantitative PCR methods – evaluation of outliers and comparison of calibration curves

Background  

As real-time quantitative PCR (RT-QPCR) is increasingly being relied upon for the enforcement of legislation and regulations dependent upon the trace detection of DNA, focus has increased on the quality issues related to the technique. Recent work has focused on the identification of factors that contribute towards significant measurement uncertainty in the real-time quantitative PCR technique, through investigation of the experimental design and operating procedure. However, measurement uncertainty contributions made during the data analysis procedure have not been studied in detail. This paper presents two additional approaches for standardising data analysis through the novel application of statistical methods to RT-QPCR, in order to minimise potential uncertainty in results.     

Cellular context in epigenetics: quantitative multicolor imaging and automated per-cell analysis of miRNAs and their putative targets

This paper assesses the quantitative resolution of qPCR using copy number variation (CNV) as a paradigm. An error model is developed for real-time qPCR data showing how the precision of CNV determination varies with the number of replicates. Using samples with varying numbers of X chromosomes, experimental data demonstrates that real-time qPCR can readily distinguish four copes from five copies, which corresponds to a 1.25-fold difference in relative quantity. Digital PCR is considered as an alternative form of qPCR. For digital PCR, an error model is shown that relates the precision of CNV determination to the number of reaction chambers. The quantitative capability of digital PCR is illustrated with an experiment distinguishing four and five copies of the human gene MRGPRX1. For either real-time qPCR or digital PCR, practical application of these models to achieve enhanced quantitative resolution requires use of a high throughput PCR platform that can simultaneously perform thousands of reactions. Comparing the two methods, real-time qPCR has the advantage of throughput and digital PCR has the advantage of simplicity in terms of the assumptions made for data analysis.     

qpcR: an R package for sigmoidal model selection in quantitative real-time polymerase chain reaction analysis

The qpcR library is an add-on to the free R statistical environment performing sigmoidal model selection in real-time quantitative polymerase chain reaction (PCR) data analysis. Additionally, the package implements the most commonly used algorithms for real-time PCR data analysis and is capable of extensive statistical comparison for the selection and evaluation of the different models based on several measures of goodness of fit. AVAILABILITY: www.dr-spiess.de/qpcR.html. SUPPLEMENTARY INFORMATION: Statistical evaluations of the implemented methods can be found at www.dr-spiess.de under 'Supplemental Data'.     

Diffprot - software for non-parametric statistical analysis of differential proteomics data

Mass spectrometry-based global proteomics experiments generate large sets of data that can be converted into useful information only with an appropriate statistical approach. We present Diffprot - a software tool for statistical analysis of MS-derived quantitative data. With implemented resampling-based statistical test and local variance estimate, Diffprot allows to draw significant results from small scale experiments and effectively eliminates false positive results. To demonstrate the advantages of this software, we performed two spike-in tests with complex biological matrices, one label-free and one based on iTRAQ quantification; in addition, we performed an iTRAQ experiment on bacterial samples. In the spike-in tests, protein ratios were estimated and were in good agreement with theoretical values; statistical significance was assigned to spiked proteins and single or no false positive results were obtained with Diffprot. We compared the performance of Diffprot with other statistical tests - widely used t-test and non-parametric Wilcoxon test. In contrast to Diffprot, both generated many false positive hits in the spike-in experiment. This proved the superiority of the resampling-based method in terms of specificity, making Diffprot a rational choice for small scale high-throughput experiments, when the need to control the false positive rate is particularly pressing.     

实时荧光定量PCR中内参基因的选择

实时荧光定量PCR技术是分析基因表达谱的一种常用方法,在分析中选择合适的内参基因对数据进行校正是得到可信数据的关键。以Lactobacillus helveticus H9为研究对象,应用实时荧光定量PCR技术,评价了5种常用内参基因ldh、recA、rpoB、gapdh和16S rRNA的表达稳定性,通过geNorm和NormFinder程序进行数据分析,结果表明5个候选内参基因在菌株不同的发酵时间点表达相对都较为稳定,结合两种分析得到其中最为稳定的基因是ldh,适合于用作后续实时荧光定量PCR试验中的内参基因。     

分子生物学技术在肠道微生物研究中的应用进展

肠道微生物与宿主的健康状况息息相关,已成为当今的热点研究领域。随着分子生物学技术的快速发展,高通量测序技术、实时荧光定量PCR技术和PCR-DGGE技术等凭借其高灵敏度、高通量、无需体外培养等优势,为研究微生物结构和功能基因组提供了新方法,并在肠道菌群的研究中应用广泛。本文对这三种分子生物学技术在肠道微生物研究中的应用进行了综述,总结了这三种技术在肠道微生物研究中的应用范围和优缺点,并展望了其在肠道微生物研究中的广阔应用前景。     

Statistical analysis of real-time PCR data

Background  

Even though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of quantitative real-time PCR are still lacking; specifically in the realm of appropriate statistical treatment. Confidence interval and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the standard curve method and other useful data analysis methods, we present and compare four statistical approaches and models for the analysis of real-time PCR data.     

Validation of an algorithm for automatic quantification of nucleic acid copy numbers by real-time polymerase chain reaction

Real-time quantitative polymerase chain reaction (PCR) with on-line fluorescence detection has become an important technique not only for determination of the absolute or relative copy number of nucleic acids but also for mutation detection, which is usually done by measuring melting curves. Optimum assay conditions have been established for a variety of targets and experimental setups, but only limited attention has been directed to data evaluation and validation of the results. In this work, algorithms for the processing of real-time PCR data are evaluated for several target sequences (p53, IGF-1, PAI-1, Factor VIIc) and compared to the results obtained by standard procedures. The algorithms are implemented in software called SoFAR, which allows fully automatic analysis of real-time PCR data obtained with a Roche LightCycler instrument. The software yields results with considerably increased precision and accuracy of quantifications. This is achieved mainly by the correction of amplification-independent signal trends and a robust fit of the exponential phase of the signal curves. The melting curve data are corrected for signal changes not due to the melting process and are smoothed by fitting cubic splines. Therefore, sensitivity, resolution, and accuracy of melting curve analyses are improved.     

Mechanisms of degradation of DNA standards for calibration function during storage

Establishment of molecular diagnostics offering quantitative technology is directly associated with real-time polymerase chain reaction (PCR). This rapid, accurate and sensitive method requires careful execution, including reliable calibration standards. The storage of such standards is crucial to prevent nucleic acid decay and to ensure stable results using real-time PCR. In this study, a broad investigation of possible causes of DNA degradation during storage was performed, including GC-content of the fragments, long-term storage, rapid freeze-and-thaw experiments, genomic DNA and short DNA fragments of different species, the influence of shear stress and the effect of nuclease remaining after DNA isolation. Several known chemical DNA degradation mechanisms have been matched with the experimental data through a process of elimination. Protocols for practical application, as well as a theoretical model describing the underlying mechanisms of deviation of real-time PCR results due to decay of standard DNA, have been developed. Primary amines in the buffer composition, which enhance depurination of the DNA helix, and shear stress due to ice crystal formation, could be identified as major sources of interaction. This results in degradation of the standard DNA, as well as in the probability of occurrence of mismatches affecting real-time PCR performance.     

Statistical diagnostics emerging from external quality control of real-time PCR

Besides the application of conventional qualitative PCR as a valuable tool to enrich or identify specific sequences of nucleic acids, a new revolutionary technique for quantitative PCR determination has been introduced recently. It is based on real-time detection of PCR products revealed as a homogeneous accumulating signal generated by specific dyes. However, as far as we know, the influence of the variability of this technique on the reliability of the quantitative assay has not been thoroughly investigated. A national program of external quality assurance (EQA) for real-time PCR determination involving 42 Italian laboratories has been developed to assess the analytical performance of real-time PCR procedures. Participants were asked to perform a conventional experiment based on the use of an external reference curve (standard curve) for real-time detection of three cDNA samples with different concentrations of a specific target. In this paper the main analytical features of the standard curve have been investigated in an attempt to produce statistical diagnostics emerging from external quality control. Specific control charts were drawn to help biochemists take technical decisions aimed at improving the performance of their laboratories. Overall, our results indicated a subset of seven laboratories whose performance appeared to be markedly outside the limits for at least one of the standard curve features investigated. Our findings suggest the usefulness of the approach presented here for monitoring the heterogeneity of results produced by different laboratories and for selecting those laboratories that need technical advice on their performance.