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ggplot2: Elegant Graphics for Data Analysis

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TLDR
This book describes ggplot2, a new data visualization package for R that uses the insights from Leland Wilkisons Grammar of Graphics to create a powerful and flexible system for creating data graphics.
Abstract
This book describes ggplot2, a new data visualization package for R that uses the insights from Leland Wilkisons Grammar of Graphics to create a powerful and flexible system for creating data graphics. With ggplot2, its easy to: produce handsome, publication-quality plots, with automatic legends created from the plot specification superpose multiple layers (points, lines, maps, tiles, box plots to name a few) from different data sources, with automatically adjusted common scales add customisable smoothers that use the powerful modelling capabilities of R, such as loess, linear models, generalised additive models and robust regression save any ggplot2 plot (or part thereof) for later modification or reuse create custom themes that capture in-house or journal style requirements, and that can easily be applied to multiple plots approach your graph from a visual perspective, thinking about how each component of the data is represented on the final plot. This book will be useful to everyone who has struggled with displaying their data in an informative and attractive way. You will need some basic knowledge of R (i.e. you should be able to get your data into R), but ggplot2 is a mini-language specifically tailored for producing graphics, and youll learn everything you need in the book. After reading this book youll be able to produce graphics customized precisely for your problems,and youll find it easy to get graphics out of your head and on to the screen or page.

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Data reuse and the open data citation advantage

TL;DR: There is a direct effect of third-party data reuse that persists for years beyond the time when researchers have published most of the papers reusing their own data, and a robust citation benefit from open data is found, although a smaller one than previously reported.
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Lipidomics Profiling and Risk of Cardiovascular Disease in the Prospective Population-based Bruneck Study

TL;DR: This study applied mass spectrometry-based lipidomics profiling to population-based cohorts and identified molecular lipid signatures for cardiovascular disease that outperform the conventional biochemical measurements of lipid classes currently used in clinics.
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The genetics of Mexico recapitulates Native American substructure and affects biomedical traits

TL;DR: Pre-Columbian genetic substructure is recapitulated in the indigenous ancestry of admixed mestizo individuals across the country, and two independently phenotyped cohorts of Mexicans and Mexican Americans showed a significant association between subcontinental ancestry and lung function.
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Examination of real-time fluctuations in suicidal ideation and its risk factors: Results from two ecological momentary assessment studies.

TL;DR: The results advance the understanding of how suicidal Ideation changes over short periods and provide a novel method of improving the short-term prediction of suicidal ideation.
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c-Jun overexpression in CAR T cells induces exhaustion resistance

TL;DR: It is concluded that a functional deficiency in c-Jun mediates dysfunction in exhausted human T cells, and that engineering CAR T cells to overexpress c- Jun renders them resistant to exhaustion, thereby addressing a major barrier to progress for this emerging class of therapeutic agents.
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