Project report Project instructions Students are required to work on a research project and submit a report on one of two topics. The project report follows the format of a scientific paper. Students are required to submit their report via Moodle as a PDF file Please make your choice from one of the two topics below and start working on the project early in the term. Make sure that as you go along you ask your unit coordinator for help in Moodle and regularly discuss your progress. The project comprises a small research project using real data and a written assignment in which you report your results. The project report should follow the format of a scientific paper. Students are required to submit their report via e-submission in Moodle. The project will be evaluated as follows: • 10% Presentation – title, abstract, headings, referencing and writing • 20% Background information and literature review of the topic – what is known and what has been done about the topic • 10% Experimental question – what you are trying to do, your hypothesis • 20% Presentation of results • 40% Analysis and Discussion of results The objective of this exercise is for you to work and analyse a real dataset generated by current gene technologies. You have to think about the experimental question that you want to address and develop/implement an analysis strategy or computational method that will allow you to answer the experimental question. Then you will analyse the data using computational and/or statistical approaches and interpret the results. Finally, present and discuss your findings. GENE552 GENE552 students are expected to demonstrate a higher level of understanding of their project topic and perform more in-depth analyses. Topics Use R as the key platform for the analyses. The datasets are available for download in Moodle as zipped files. In each file you'll find a brief description of the data and some suggested analyses. There are many angles that can be explored in each dataset. It is up to you to decide what you want to do. • Genome wide association studies using single SNP and functional analyses • Estimation of genetic variability and genetic architecture in populations How to get started At this point it probably sounds rather daunting. And quite frankly, this is not a trivial exercise. There is no script telling you to click here and then click there, you cannot just Google away and put together bits and pieces from the web. You will have to think this one out. To help you get your head around the problem, a few hints: 1. Choose the topic that you are more interested in. The easiest way to get things done is to actually enjoy doing them! 2. Picture yourself as a researcher. You want to work on a scientific problem/question. The first thing you have to do is understand the theory behind the problem. The best way to do this is to read the literature about the topic. The project topics require data analysis using SNP data to learn something about the underlying biology. 3. Now that you know all about the subject you are interested in, you have to work on your analysis. The Primer to Analysis of Genomic Data Using R is your friend here.As you work your way through the case studies in the book, you should become comfortable using R and there you will find snippets of code that you can use straight in your own analysis. But, do not expect a simple cut and paste exercise, you will need to think on how to adapt code from all over the book into your analyses. And remember that we are here to help – discuss with the lecturers any difficulties or how tos. 4. Finally make sense out of it all. See how your results fit into what was previously known, did you get what you expected – why or why not. How similar are your results to what other researchers have observed. How does your computational solution compare/fit in with what others have done previously. And then it’s time to write it all up. Some writing tips in the next section, but the best one is to read lots and lots of scientific papers – the more you read, the more comfortable you’ll be with this style of writing. Remember that the best way to learn to write is reading. Check out the articles in the main bioinformatics journals (e.g. Bioinformatics or BMC Bioinformatics). An excellent source of high level, well-written reviews can be found in Nature Reviews Genetics – these texts review the latest and greatest in current interesting genetic research areas (http://www.nature.com/nrg/index.html). Information for writing the project The project report should be concise and follow the format of a scientific paper. Ensure your general writing style is of a high standard. Sentences should be complete and non-ambiguous. Each paragraph should relate to one point or theme and should be comprised of an introductory sentence, body of two or more sentences and a concluding sentence. Paragraphs should be ordered in a logical fashion. Proof read what you have written before e-submission to check these points. Remember to include a title, author (your name!) and an abstract (short summary that tells the whole story in a few lines – what you did, why you did it and what you found out). The general structure and contents for the practical report would normally include the headers below. But you are free to find the style/headers that works best for your story – at the end of the day this is storytelling and it should be interesting, coherent and well written. Introduction Describe the problem that is being addressed by the project and the relevant background (e.g. what has been done so far, the underlying theory – see below). Read, summarize, comment and reference work from various sources, but be sure that the introduction represents your own work (slightly re-wording what others have said does not constitute your own work). Devote the final paragraph of this section to stating the aim or aims of the project. Background Give a general description of the reasons why this topic is relevant. If it fits within the topic, consider the e.g. biological or computational issues. Reference publications that have discussed these issues and choose lead articles that address the various facets of the topic. This section will cover only overall/general concepts with the detailed findings, experiments and/or hypotheses discussed later on. The two key words here are in-depth and critical. • in-depth: discuss/explain the main current advances and state of affairs in the topic you chose to work on. You can also present challenges and opportunities and how the field is likely to evolve (if relevant for your topic). • critical: it is not a simple listing of what other authors wrote. A good text will reflect the writer's opinion and his/her view and perspectives of the field; build an entirely new story around the theme with your perspective. Methods Explain what was done and how this was achieved. The method section should give enough information to allow others to repeat the work, but without being overly long or tedious. Pay special attention to explain (and justify) your experimental design and how you analysed the data (omit boring details as e.g. how you imported the data into R). Ensure the method section resembles the general format used in a scientific paper, which is paragraph style with formula or tables referred to in the text. Use the past tense. Common mistakes in the write-up of methods include the use of dot points (rather than paragraphs) and confounding of methods with results. Results Summarize the key points in a narrative style; do not try to include everything (e.g. below the 500,000 genotypes for each of the 10,000 individuals in my population!). Present results using text, tables, figures and graphs. Remember to label tables and figures (e.g. Table 1. The effect of…). Tables are labelled above and figures are labelled below. Ensure that all tables and figures are referred to in the text (e.g. Table 1 shows….). In particular, draw the reader’s attention to the most important results and any unexpected results. Use informative sub-headings to make it easier to understand (and it helps to structure the text). Discussion Discuss the results in a clear and concise manner. The main purpose of this section is to consider the results in a broader sense. Start by re-capping the aim and key results of the project, and then discuss these results in a wider context. Try to explain why you got the results you did and how they fit in with other research and/or the theory. In the introduction you mainly expressed the views of others (with due referencing to them and in your own words). This is now your chance to show your ability to synthesise the ideas/concepts you read about and link them in to your work. Feel free to critique previous work. It is good if you feel strongly about some aspect of the topic. A significant proportion of the marks is allocated to this section and is judged on how well you present your synthesis of previous work and your views, backed up by evidence from your experiment. Conclusion This can be within the discussion section or can be a section on its own. It is up to you to decide what structure makes the story more eloquent. Here you may extend your views to what lies ahead, or what research needs to be done and what else you could have done or what is the likely progress and achievements that will be made in the future. The last paragraph is usually an overall conclusion. This paragraph should emphasize the key messages without introducing any new ideas. References Make sure that all papers from other authors are correctly referenced. All references that appear in the text should also appear in the references (and vice-versa of course). Choose a referencing style that you like but be consistent in it, preferable APA. When choosing references, they should be current or at least classics (as opposed to simply old and out dated) and from reliable sources – high profile refereed scientific journals (translation: no Wikipedia or dodgy website links!).