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SSMD
In statistics, the strictly standardized mean difference (SSMD) is a measure of effect size. It is the mean divided by the standard deviation of a difference between two random values each from one of two groups. It was initially proposed for quality control and hit selection in high-throughput screening (HTS) and has become a statistical parameter measuring effect sizes for the comparison of any two groups with random values. Background In high-throughput screening (HTS), quality control (QC) is critical. An important QC characteristic in a HTS assay is how much the positive controls, test compounds, and negative controls differ from one another. This QC characteristic can be evaluated using the comparison of two well types in HTS assays. Signal-to-noise ratio (S/N), signal-to-background ratio (S/B), and the Z-factor have been adopted to evaluate the quality of HTS assays through the comparison of two investigated types of wells. However, the S/B does not take into account any ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hit Selection
In high-throughput screening (HTS), one of the major goals is to select compounds (including small molecules, siRNAs, shRNA, genes, et al.) with a desired size of inhibition or activation effects. A compound with a desired size of effects in an HTS screen is called a hit. The process of selecting hits is called hit selection. Methods for hit selection in general HTS experiments have the ability to screen tens of thousands (or even millions) of compounds rapidly. Hence, it is a challenge to glean chemical/biochemical significance from mounds of data in the process of hit selection. To address this challenge, appropriate analytic methods have been adopted for hit selection. There are two main strategies of selecting hits with large effects. One is to use certain metric(s) to rank and/or classify the compounds by their effects and then to select the largest number of potent compounds that is practical for validation assays. The other strategy is to test whether a compound has effects s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
High-throughput Screening
High-throughput screening (HTS) is a method for scientific discovery especially used in drug discovery and relevant to the fields of biology, materials science and chemistry. Using robotics, data processing/control software, liquid handling devices, and sensitive detectors, high-throughput screening allows a researcher to quickly conduct millions of chemical, genetic, or pharmacological tests. Through this process one can quickly recognize active compounds, antibodies, or genes that modulate a particular biomolecular pathway. The results of these experiments provide starting points for drug design and for understanding the noninteraction or role of a particular location. Assay plate preparation The key labware or testing vessel of HTS is the microtiter plate, which is a small container, usually disposable and made of plastic, that features a grid of small, open divots called ''wells''. In general, microplates for HTS have either 96, 192, 384, 1536, 3456 or 6144 wells. These are a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dual-flashlight Plot
In statistics, a dual-flashlight plot is a type of scatter-plot in which the standardized mean of a contrast variable ( SMCV) is plotted against the mean of a contrast variable representing a comparison of interest . The commonly used dual-flashlight plot is for the difference between two groups in high-throughput experiments such as microarrays and high-throughput screening studies, in which we plot the SSMD versus average log fold-change on the ''y''- and ''x''-axes, respectively, for all genes or compounds (such as siRNAs or small molecules) investigated in an experiment. As a whole, the points in a dual-flashlight plot look like the beams of a flashlight with two heads, hence the name dual-flashlight plot. With the dual-flashlight plot, we can see how the genes or compounds are distributed into each category in effect sizes, as shown in the figure. Meanwhile, we can also see the average fold-change for each gene or compound. The dual-flashlight plot is similar to the volcan ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Z-factor
The Z-factor is a measure of statistical effect size. It has been proposed for use in high-throughput screening (HTS), where it is also known as Z-prime, to judge whether the response in a particular assay is large enough to warrant further attention. Background In HTS, experimenters often compare a large number (hundreds of thousands to tens of millions) of single measurements of unknown samples to positive and negative control samples. The particular choice of experimental conditions and measurements is called an assay. Large screens are expensive in time and resources. Therefore, prior to starting a large screen, smaller test (or pilot) screens are used to assess the quality of an assay, in an attempt to predict if it would be useful in a high-throughput setting. The Z-factor is an attempt to quantify the suitability of a particular assay for use in a full-scale HTS. Definition Z-factor The Z-factor is defined in terms of four parameters: the means (\mu) and standard dev ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Effect Size
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size value. Examples of effect sizes include the correlation between two variables, the regression coefficient in a regression, the mean difference, or the risk of a particular event (such as a heart attack) happening. Effect sizes are a complement tool for statistical hypothesis testing, and play an important role in power analyses to assess the sample size required for new experiments. Effect size are fundamental in meta-analyses which aim to provide the combined effect size based on data from multiple studies. The cluster of data-analysis methods concerning effect sizes is referred to as estima ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SMCV
In statistics, the standardized mean of a contrast variable (SMCV or SMC), is a parameter assessing effect size. The SMCV is defined as mean divided by the standard deviation of a contrast variable. The SMCV was first proposed for one-way ANOVA cases and was then extended to multi-factor ANOVA cases. Background Consistent interpretations for the strength of group comparison, as represented by a contrast, are important. When there are only two groups involved in a comparison, SMCV is the same as the strictly standardized mean difference (SSMD). SSMD belongs to a popular type of effect-size measure called "standardized mean differences" which includes Cohen's d and Glass's \delta. In ANOVA, a similar parameter for measuring the strength of group comparison is standardized effect size (SES). One issue with SES is that its values are incomparable for contrasts with different coefficients. SMCV does not have such an issue. Concept Suppose the random values in t groups ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
C+-probability
C, or c, is the third letter of the Latin alphabet, used in the modern English alphabet, the alphabets of other western European languages and others worldwide. Its name in English is ''cee'' (pronounced ), plural ''cees''. History "C" comes from the same letter as "G". The Semites named it gimel. The sign is possibly adapted from an Egyptian hieroglyph for a staff sling, which may have been the meaning of the name ''gimel''. Another possibility is that it depicted a camel, the Semitic name for which was ''gamal''. Barry B. Powell, a specialist in the history of writing, states "It is hard to imagine how gimel = "camel" can be derived from the picture of a camel (it may show his hump, or his head and neck!)". In the Etruscan language, plosive consonants had no contrastive voicing, so the Greek ' Γ' (Gamma) was adopted into the Etruscan alphabet to represent . Already in the Western Greek alphabet, Gamma first took a '' form in Early Etruscan, then '' in Classical E ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Median
The median of a set of numbers is the value separating the higher half from the lower half of a Sample (statistics), data sample, a statistical population, population, or a probability distribution. For a data set, it may be thought of as the “middle" value. The basic feature of the median in describing data compared to the Arithmetic mean, mean (often simply described as the "average") is that it is not Skewness, skewed by a small proportion of extremely large or small values, and therefore provides a better representation of the center. Median income, for example, may be a better way to describe the center of the income distribution because increases in the largest incomes alone have no effect on the median. For this reason, the median is of central importance in robust statistics. Median is a 2-quantile; it is the value that partitions a set into two equal parts. Finite set of numbers The median of a finite list of numbers is the "middle" number, when those numbers are liste ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Contrast Variable
In statistics, particularly in the analysis of variance and linear regression, a contrast is a linear combination of variables (parameters or statistics) whose coefficients add up to zero, allowing comparison of different treatments. Definitions Let \theta_1,\ldots,\theta_t be a set of variables, either parameters or statistics, and a_1,\ldots,a_t be known constants. The quantity \sum_^t a_i \theta_i is a linear combination. It is called a contrast if Casella 2008, p. 11. Furthermore, two contrasts, \sum_^t a_i \theta_i and \sum_^t b_i \theta_i, are orthogonal if Examples Let us imagine that we are comparing four means, \mu_1,\mu_2,\mu_3,\mu_4. The following table describes three possible contrasts: The first contrast allows comparison of the first mean with the second, the second contrast allows comparison of the third mean with the fourth, and the third contrast allows comparison of the average of the first two means with the average of the last two. In a balanced one-way anal ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
RNAi
RNA interference (RNAi) is a biological process in which RNA molecules are involved in sequence-specific suppression of gene expression by double-stranded RNA, through translational or transcriptional repression. Historically, RNAi was known by other names, including ''co-suppression'', ''post-transcriptional gene silencing'' (PTGS), and ''quelling''. The detailed study of each of these seemingly different processes elucidated that the identity of these phenomena were all actually RNAi. Andrew Fire and Craig Mello shared the 2006 Nobel Prize in Physiology or Medicine for their work on RNAi in the nematode worm '' Caenorhabditis elegans'', which they published in 1998. Since the discovery of RNAi and its regulatory potentials, it has become evident that RNAi has immense potential in suppression of desired genes. RNAi is now known as precise, efficient, stable and better than antisense therapy for gene suppression. Antisense RNA produced intracellularly by an expression vect ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
