The adventure through the random forests continues
For the summer school in statistical genomics NGSchool is looking for applicants who:
have to apply the methods of statistical genomics in their current or future projects (thus, a connection with both life sciences and bioinformatics that heavily relies on statistics is assumed);
have just started their path in this field, but have a knowledge of intermediate level statistics and a general understanding about what Statistical Genomics is and the methods used in Statistical Genomics (any in-depth knowledge is not necessary);
will benefit from the school’s program (are not overqualified and not underqualified, which will be additionally assessed by the organising committee);
are able to perform data analysis in either R or Python programming language, and are comfortable with using Linux command line; since the workshops at the school will be mainly provided in R, people with limited R experience will be advised to learn basic syntax of R and may be pass some short course on R;
if needed, are motivated to prepare for the school using the materials provided by the organisers (e.g., improve the level of their statistical knowledge using provided online-courses or improve their programming-for-data-science skills);
are able to clearly express what they want to get from the school and describe their motivation to participate;
are willing to participate in social events, eager to build networks, and communicate with participants, speakers, and organisers;
have a laptop that they can bring to school. Laptop should be based on Linux/macOS or virtual box is possible. Windows support by the organisers is limited and not guaranteed;
ideally, have never participated in previous NGSchool events - we assume that alumni will benefit less from NGSchool2020 and therefore we will give priority to the first-time attendees, however, we do not discourage the alumni from applying as well;
preference will be given to potential participants with clearly limited access to similar educational events that satisfy the previous criteria on the expected level of knowledge.
We expect our future participants to know statistics at the intermediate level, to be familiar with Linux terminal, to understand basic ideas of statistical genomics (we will teach you the methods), being able to code basic data analysis scripts in both R and Python. If you feel that you do not match the above criteria, we provide a list of materials you may use for self-preparation. This list is not extensive and you are not obliged to finish any of these courses or provide any proofs that you have actually finished them. However, we can not guarantee your progress during the school if you do not have the above mentioned skills. We will provide introductory lessons, but they will be more recap sessions since it is not possible to teach any of these skills in several hours.
We recommend https://www.coursera.org/learn/biostatistics and https://www.coursera.org/learn/biostatistics-2 or analogous (1st part is minimum, 2nd part would be beneficial too).
We would recommend to understand the problems described in e.g. http://statweb.stanford.edu/~sabatti/research.html, however without focusing on the particular researcher and without going deep into methods (we will teach the methods at the school).
If you need to learn R, try https://www.coursera.org/learn/r-programming or https://swirlstats.com/.
If you need more experience with Python, go to https://www.learnpython.org/ or https://www.codecademy.com.
If you want to train using Linux terminal, refer to https://ubuntu.com/tutorials/command-line-for-beginners#1-overview or (more hardcore) https://missing.csail.mit.edu.
Again, you are NOT obliged to do any of these, but we assume that your skills match our expectations, so you can maximally benefit from the very beginning of the school!