what are gwas summary statistics?
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GWAS summary statistics refer to supplying three important pieces of information: SNP, Phenotype, and P-value. This differs from full GWAS data which would have calls for every individual at every SNP.
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['Find the mean of all the x-values.', 'Find the standard deviation of all the x-values (call it sx) and the standard deviation of all the y-values (call it sy). ... ', 'For each of the n pairs (x, y) in the data set, take.', 'Add up the n results from Step 3.', 'Divide the sum by sx ∗ sy.']
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['Scatter plot. Scatter plots present data on the x- and y-axes and are used to investigate an association between two variables. ... ', 'Bar graph and histogram. ... ', 'Pie chart. ... ', 'Box and whisker chart. ... ', 'Three-dimensional effects. ... ', 'Drawing a graph: example.']
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Parameters are numbers that summarize data for an entire population. Statistics are numbers that summarize data from a sample, i.e. some subset of the entire population. Problems (1) through (6) below each present a statistical study*. For each study, identify both the parameter and the statistic in the study.
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['Go to the data table.', 'Click analyze.', 'If you have a XY or Grouped table: Choose "Row means/totals". If you have a column table: Choose "Column statistics".', 'Choose options on the dialog and click OK.']
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['Simplicity: ADVERTISEMENTS: ... ', 'Representation: Average should represent the entire mass of data.', 'Rigidly Defined: ADVERTISEMENTS: ... ', 'Algebraic Treatment: Averages are always capable of further algebraic treatment.', 'Clear and Stable Definition: ... ', 'Absolute Number: ... ', 'Effect of fluctuations of Sampling: ... ', 'Not affected by skewness:']
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Two types of statistical methods are used in analyzing data: descriptive statistics and inferential statistics. Descriptive statistics are used to synopsize data from a sample exercising the mean or standard deviation. Inferential statistics are used when data is viewed as a subclass of a specific population.
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['Data and its Frequency Distribution.', 'Pictographs.', 'Bar Graphs.', 'Histogram and Pie-Charts.', 'Chance and Probability.', 'Arithmetic Mean.', 'Median and Mode.']
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Cross‐sectional studies may be either descriptive or analytical. Descriptive studies mostly aim to provide estimates of prevalence of disease, traits such as smoking behavior, people′s attitudes, knowledge or health behavior, whereas analytical studies aim to assess associations between different parameters.
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Genotype imputation is carried out by statistical methods that combine the GWAS data together with a reference panel of haplotypes. These methods take advantage of sharing of haplotypes between individuals over short stretches of sequence to impute alleles.
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Statisticians use summary measures to describe the amount of variability or spread in a set of data. The most common measures of variability are the range, the interquartile range (IQR), variance, and standard deviation.
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Data that summarize all observations in a category are called summarized data. The summary could be the sum of the observations, the number of occurrences, their mean value, and so on. ... This is in contrast to raw data, where each row in the worksheet represents an individual observation.
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['AVG() - Returns the average value.', 'COUNT() - Returns the number of rows.', 'FIRST() - Returns the first value.', 'LAST() - Returns the last value.', 'MAX() - Returns the largest value.', 'MIN() - Returns the smallest value.', 'SUM() - Returns the sum.']
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[' The Law of Segregation: Each inherited trait is defined by a gene pair. ... ', ' The Law of Independent Assortment: Genes for different traits are sorted separately from one another so that the inheritance of one trait is not dependent on the inheritance of another.']
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A Punnett grid shows the possible allele combinations that result in the offspring from parents with known genotypes. Pedigree charts are used to trace the inheritance pattern of a genetic condition through a family.
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Statistics is a form of mathematical analysis that uses quantified models, representations and synopses for a given set of experimental data or real-life studies. Statistics studies methodologies to gather, review, analyze and draw conclusions from data. Some statistical measures include the following: Mean.
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['Measures of central tendency and location (mean, median, mode)', 'Measures of dispersion (range, variance, standard deviation)', 'The extent of symmetry/asymmetry (skewness)', 'The flatness or peakedness (kurtosis).']