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 Bayesian methods in ecology and evolution¶ https://bitbucket.org/mfumagal/statistical_inference day 1c: Bayesian applications in genomics¶ Reconstructing genomes from sequencing data¶ You are going to develop and implement a Bayesian approach to reconstruct genomes from data produced from high-throughput sequencing machines. Specifically, you will be doing genotype calling from short-read NGS data.  Load the R functions

This is a header¶ some text in bold or italic and even some quick math $A_j \leq e^x$ or long equations \begin{equation} QX(x) = \sum{i=0}^{\infty} y_i \end{equation} In [3]: # this is some code in R a

Probability theory¶ Probability theory is the foundation for all statistical inferences. Through the use of models of experiments, we are able to draw inferences about populations based on examining only a part of the whole. In this first lecture, we are going to outline the basic ideas of probability theory that are of direct importance

 Bayesian methods in ecology and evolution¶ https://bitbucket.org/mfumagal/statistical_inference part 2b: Bayesian inference¶ Once we have specified the prior, we can use Bayes’ theorem to obtain the posterior distribution of model parameters. However, the density (or cumulative) function can be difficult to interpret. Therefore we want to summarise the information enclosed in these distributions. We can

OPEN ACCESS Citation: Weissgerber TL, Milic NM, Winham SJ, Garovic VD (2015) Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm. PLoS Biol 13(4): e1002128. doi:10.1371/journal. pbio.1002128 Published: April 22, 2015 PERSPECTIVE Beyond Bar and Line Graphs: Time for a New Data Presentation Paradigm Tracey L. Weissgerber1*, Natasa M. Milic1,2, Stacey J.