Topics & Articles
Here are the topics with scientific papers that we believe would make good seminar presentations. For each topic there are two articles and those articles introduce methods that aim to solve a similar problem, but they do it in a different way. The aim of a presentation would be to compare those two methods. So, the combined presentation would look following: first presenter introduces first method, second presenter second method and then reviewers can give their opinion. It would be nice if presenters discuss those methods beforehand and adjust their presentations so that the problem and tools that are intended to solve that particular problem are introduced to the audience in a clear and coherent manner. Also, given that there are articles that benchmark those tools then it would be useful to check them out (they help to get better and wider understating about given topic/problem). If you have trouble finding benchmarking articles (or something introductory to given topic) then please ask us and we will gladly help!
If you are interested in another method or even another topic then please let us know and we will add it here (provided of course that it is suitable).
Discovering drugs against aging
- Article 1: Using the drug-protein interactome to identify anti-ageing compounds for humans link
- Article 2: Gene expression‐based drug repurposing to target aging link
Analysis of CRISPR/Cas9 knock-out screens
Predicting the mutations generated by CRSIPR editing experiments
RNA-Seq alignment
Methods in this section serve a similar purpose as those that are in previous topic, but now the origin of short reads is mRNA (product of a gene) not DNA. Why is a separate program needed for mRNA? BWA and Bowtie are not aware of splicing (mRNA editing step - nascent mRNA contains segments called exons and introns, introns are usually spliced out and the edited mRNA contains only exons). Therefore, reads from mRNA cannot be mapped directly on DNA meaning that the absence of introns in mRNA should be dealt with. kallisto is also somewhat different, it does "pseudoalignment", to find out what it is, check the article!
Mendelian Randomization
This method is used for finding causal associations. Let's imagine an experiment when we are interested in whether some specific biomarker (e.g. some inflammation marker in the blood) is associated with a disease (let's say Alzheimer's). We do our experiment and observe this relationship (increased level of this biomarker is associated with Alzheimer's disease). Okay, there is an association but that doesn't necessarily mean that there is a causal relationship. All of us have seen correlations between some strange stuff, e.g. ice cream consumption correlates with drowning. This example is most likely confounded by some other factor - like a good weather. Good weather correlates well with both - consumption of ice cream and risk of drowning (because people swim more with good weather). So, how to find whether our observed association is causal or not? There are many GWAS studies made (check colocalisation and genotype imputation topic) that report associations between SNP-s and all sorts of traits. Now, if we find a study that showed association with our biomarker of interest, then we have two correlations. One with biomarker and Alzheimer's the other with SNP-s and Alzheimer's. Now we can check whether there is an association between those SNP-s and Alzheimer's, and if there is then there might be a causal relationship. Of course, it doesn't rule out that there isn't a confounder, it just shows that even despite of this, it still has a real effect as well. This method is called Mendelian Randomization and it makes several assumptions, firstly our selected SNP-s shouldn't affect disease in any other way than through our biomarker and the relationship between biomarker and SNP should be unidirectional (which it is because we all get our gene variants pretty randomly). Here you can find articles that discuss given method:
- Article 1: Fulfilling the promise of Mendelian randomization
- Article 2: Mendelian randomization: a premature burial?
PS: If you need some extra biological information to better understand your article, then there is a good chance that you will find it from here: https://www.nature.com/scitable/topic/gene-expression-and-regulation-15