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Biostatistics with R: An Introduction to Statistics Through Biological Data Babak Shahbaba
Publisher: Springer

4-hour practical course given by the BioSC. Biostatistics with R : an introduction to statistics through biological data. An Introduction to Statistics Through Biological Data. Service for Biomathematical and Biostatistical Analyses – University of Geneva. The aim of these half day courses is to provide to scientists the necessary statistical and computer tools enabling them to properly and efficiently analyse their data. We hypothesize, that using statistical methods to detect differential expression between samples is biased by transcript length and that this bias is inherent to the standard RNA-seq process. The book explains Biostatistics with R. However, the original COPA algorithm did not identify down-regulated outliers, and the currently available R package implementing the method is similarly restricted to the analysis of over-expressed outliers. This has implications for the ranking of differentially expressed genes, and in particular may introduce bias in gene set testing for pathway analysis and other multi-gene systems biology analyses. United Kingdom : Brooks/Cole Cengage Learning, c2013. Feature of current protocols for RNA-seq technology. Two sessions: Wednesday, April 24 and Tuesday, April 30 13 h 30 – 17 h 30. Computer room 112 – Acacias 1. Introduction to probability and statistics. Biostatistics with R is designed around the dynamic interplay among statistical methods, their applications in biology, and their implementation.