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I wanted to share links to some resources that I mentioned during yesterday's Danube Epigenetics webinar.
If you're new to designing figures and you're not sure where to start, take 2 minutes to read this excellent blog post from @helenajambor
https://ecrlife420999811.wordpress.com/2018/08/29/better-figures-for-life-sciences/ https://twitter.com/usymmons/status/1349381926713503744
If you're new to designing figures and you're not sure where to start, take 2 minutes to read this excellent blog post from @helenajambor
https://ecrlife420999811.wordpress.com/2018/08/29/better-figures-for-life-sciences/ https://twitter.com/usymmons/status/1349381926713503744
Also check out this brief guide to designing figures for scientific papers: https://pubmed.ncbi.nlm.nih.gov/21960472/
Wondering why you shouldn't use bar graphs for continuous data & what to use instead?
1. Everything you need to know in a Twitter thread: https://twitter.com/T_Weissgerber/status/1192694904603992064
2. Everything you need to know in a webinar: https://elifesciences.org/inside-elife/5114d8e9/webinar-report-transforming-data-visualisation-to-improve-transparency-and-reproducibility
1. Everything you need to know in a Twitter thread: https://twitter.com/T_Weissgerber/status/1192694904603992064
2. Everything you need to know in a webinar: https://elifesciences.org/inside-elife/5114d8e9/webinar-report-transforming-data-visualisation-to-improve-transparency-and-reproducibility
If you want a paper you can cite for peer reviews, etc., here are some options:
2015 paper: http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002128
2019 follow-up (see Table 3 for a list of viz tools): https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.118.037777
This paper also addresses other common visualization problems.
2015 paper: http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002128
2019 follow-up (see Table 3 for a list of viz tools): https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.118.037777
This paper also addresses other common visualization problems.
Wondering how to show individual level data on a line graph? See the supplement of this paper for options: http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002484)
Up to 8% of men and 0.5% of women of northern European ancestry are colorblind. Use a colorblindness simulation tool like Color Oracle ( https://colororacle.org ) to make sure your figures are accessible to colorblind readers.
To learn more about why you shouldn't use rainbow colormaps, and what to use instead, see this piece by @ShyamSaladi https://elifesciences.org/labs/c2292989/jetfighter-towards-figure-accuracy-and-accessibility
Working with images? See this preprint for insight on how to create clear and informative image-based figures. The preprint includes many visual examples, and the OSF repository includes pre-made slides for teaching. https://www.biorxiv.org/content/10.1101/2020.10.08.327718v1
This paper has more information on how to report your imaging methods: https://elifesciences.org/articles/55133
Yesterday I also mentioned our international working group's efforts to use automated screening tools to identify common problems in COVID preprints on bioRxiv and medRxiv, and share reports with authors and readers. You can learn more about this here: https://www.nature.com/articles/s41591-020-01203-7
Esther mentioned that it's important not to forget about your stats. For those working in fields where t-tests and ANOVA are common, this paper explains why we need to report more than "Data were analyzed by t-tests or ANOVA, as appropriate". https://elifesciences.org/articles/36163
Finally, check out this "Science of science reading list for peer reviewers" to learn to identify and fix common problems that impact rigor and reproducibility. https://www.bihealth.org/en/research/quest-center/mission-approaches/meta-research/meta-research-reading-list
Thanks to everyone who attended yesterday, and to the organizers (including @usymmons) and panelists (Esther, @helenajambor and @allycote) and attendees for an interesting discussion. Happy visualizing!
