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Inspired by @westwoodsam1, @AleLautarescu and my birthday (who doesn't want to do something crazy on their birthday), let's start with #PaperPerDayChallenge. I am v curious about this: new The Way or dangerously close to reviewing candidate genes? https://onlinelibrary.wiley.com/doi/full/10.1002/ajmg.b.32766
2/ Shots fired: "[S]tudies of gene-environment interaction . . . are more likely to be productive than studies of genes or environmental factors individually" (written v neatly; not sure criticisms of twin studies apply to the whole field?) https://www.sciencedirect.com/science/article/pii/S0165178119306298#bib0037
3/ My brain is the worst: it's a v interesting paper, with a key gene sequenced, my brain "oh no, doughnut chart that contributes little!" which is a v minor point https://www.nature.com/articles/s41380-019-0583-1
4/ This study reminds me of a later Ruderfer et al's v insightful multiple symptoms across psychosis and PRSs paper - I like how this one makes bold claims and then is v clear & transparent on limitations, potentially simultaneously diluting bold claims https://onlinelibrary.wiley.com/doi/full/10.1111/acps.12307
5/ Instead of genetics, reading collected writings by Douglas Crimp (RIP), a beautifully lucid writer on art history, AIDS-related activism & art etc. The most famous book on that crisis is (perhaps) And the Band Played On. This is a sublime critique of it https://www.jstor.org/stable/pdf/3397576.pdf?seq=1#page_scan_tab_contents
6/ Confirmation bias in an interesting manner in post-GWAS. Not on gene pathways but got me thinking: how do people address confirmation bias in pathway work (my dream I know little of)? Compare multiple databases and meta-analyse GWAS hit interpretations? https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6590226/
7/ I really didn't enjoy the unfunny wittiness but some criticisms I felt: citizen science programmes feel like unpaid labour, we are potentially not giving the general public what it wants, who considers Facebook for science cool, what is really "open"? https://journals.sagepub.com/doi/full/10.1177/0306312718772086
8/ This study includes APOE B rather than everyone's beloved APOE E but still, it is so detailed (there are even comparisons between pre- and post-menopausal women and men!) https://www.biorxiv.org/content/biorxiv/early/2019/11/09/837021.full.pdf
9/ Eek, so sorry, I am already falling behind! The trouble is I am reading my articles v in between other things. Anyhow. Some good stuff will be coming up to get me back on track! For today: figures a bit messy but steps fair and described clearly https://link.springer.com/article/10.1007/s10654-019-00576-5
10/ The title is slightly misleading but it is good these points are making rounds https://jamanetwork.com/journals/jama/fullarticle/2755743?guestAccessKey=164ba7f3-eb3c-453e-8842-3b099088b480&utm_source=twitter&utm_medium=social_jama&utm_term=2830883020&utm_content=followers-article_engagement-tfl-text&utm_campaign=article_alert&linkId=77063793
11/ Oh, do I have to reanalyse a lot of data now? (Jokes aside, thanks for bringing this interesting paper to my attention, @Don_lyall!) https://www.medrxiv.org/content/10.1101/19012021v1
12/ @weihuali11, @giacomolivan and colleagues: while the definition of "top" is convincing, I wonder if results would be v different if different "topness" was considered (e.g. researchers well-known nationally, less so internationally, if even possible?) https://www.nature.com/articles/s41467-019-13130-4
13/ Those "suggestive" GWAS associations are gonna make some scream... Jokes aside, great work. I think results weren't broken down by infection type (sample size was)? It would be interesting to dig (ofc I need to know what's up with my beloved flu) https://www.nature.com/articles/s41398-019-0622-3
14/ I am happy to see this sort of work finally out! https://www.nature.com/articles/s41588-019-0512-x
15/ As all articles about slow academia, this one annoyed me slightly. It didn't really present how we would make the transition into slow (definitely wise!) without harming ECRs ("tenured key members" can sort of chill a bit more anyway, compared to ECRs) https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(19)30242-6
16/ A beautifully clear review of genetics of ageing by @d_melzer, @lcpilling and @Ferruccilu was actually out on my birthday https://www.nature.com/articles/s41576-019-0183-6.pdf?fbclid=IwAR3w3Q7KUkr2mu1sl0Bo2X32Bmd1GZeeq1-JLvpVwZQPQL46eJXpsSohcfY
17/ Let's try again (sorry for a broken link!): this paper has really cool methodological solutions in place but I occasionally wonder if the omnigenic model can even be really falsified (or falsified under methods we have for now) https://www.nature.com/articles/s41386-019-0410-z
18/ I really think that this series would be useful to students and for teaching purposes https://jamanetwork.com/journals/jama/article-abstract/2656816
19/ See an excellent thread from @NicoleBarbaro on how the design of this study is tight but its statistical analysis... not so much https://www.cambridge.org/core/journals/ps-political-science-and-politics/article/exploring-bias-in-student-evaluations-gender-race-and-ethnicity/91670F6003965C5646680D314CF02FA4
20/ Finally read this article and I'm glad. While the conclusion is obviously distressing, it was also a really neatly written article, describing key issues very clearly https://insights.ovid.com/crossref?an=00041444-201810000-00002
21/ Cool idea to look into whether artificial neural networks would be more useful in predicting case-control status in schizophrenia than PRS but the title feels a bit misleading https://arxiv.org/ftp/arxiv/papers/1911/1911.08996.pdf
22/ Lovely schizophrenia GWAS review by @CA_Dennison, @sophlegge, @AFPopgen, and @drjameswalters (although apparently now one could argue that lots of thesis introductions will now just be "So, this review by Dennison et al., thank you, goodnight") https://www.sciencedirect.com/science/article/pii/S0920996419304839
23/ I'd love to learn more about networks but what if it's Brexit of genetics (oh no). Some very interesting (and... entertaining?) writing from @jonathan_flint1 & @TreyIdeker https://doi.org/10.1371/journal.pgen.1008519
24/ @Ygoes2B_more, Inge Schwabe et al. wrote a very neat overview of methodological/phenotype considerations in genetics of depression (we have the schizophrenia GWAS, the MDD paper, is there a new genetics of bipolar overview somewhere?) https://www.cambridge.org/core/journals/psychological-medicine/article/unraveling-the-genetic-architecture-of-major-depressive-disorder-merits-and-pitfalls-of-the-approaches-used-in-genomewide-association-studies/4E0EBA7F38A44EACE24819EDB02F254F/core-reader
25/ Goodbye to candidate gene studies, from @LaramieDuncan, @RecoveryDoctor and Jacob Ballon https://www.nature.com/articles/s41386-019-0389-5
26/ This work, by @melindacmills and Charles Rahal, is so in-depth. I knew our samples were genome-white but I didn't know for instance that we are bad at even describing samples in a way that enables straightforward identification of ancestries included https://www.nature.com/articles/s42003-018-0261-x
27/ The WHO released its Global Influenza Strategy for the next decade in March, and this paper by @MarkRTurner, @alexandraphelan & @RebeccaKatz5 discusses v neatly what the strategy is and challenges to its implementation https://www.nejm.org/doi/full/10.1056/NEJMp1905224
