Training Programs for 2018:
All Infobiology courses are independent modules that can be studied individually, even if they are designed to be part of a whole, coherent, computational analysis educational program.
Please note: live courses are taught in italian, but can be delivered in english if specifically requested by non-Italian participants. All material is in english (slides, scripts, videos and tutorials in the online-platform).
Two training programs will be active during 2018:
– Bio-R Specialization: a set of three courses focused on using “R” for the manipulation and analysis of biological data: R4BM + FunGR + R4BS (in this order as a program or individually).
– NGS focused track: a set of two courses on Next Generation Sequencing (NGS) data analysis.
Discounts are reserved to those taking the entire 3-course Specialization, or for groups of more than 3 if sponsored by the same institution/employer: please enquire.
3 courses (each: 2 weeks online + 2 live days)
R4BM – R for biological data manipulation >> Registrations are now CLOSED. Look for the next edition <<
Introductory course (no previous experience required) on data manipulation focused on life science data (biological data, gene expression, clinical data and similar). The course is highly practical and designed for life science professional (biologists, technicians, clinicians, researchers) with no previous bioinformatics experience. Participants should have the normal skills of computer usage, such as creating and navigating through files and folders, using spreadsheets and word processors; the course will introduce them to the use of the scripting language “R” with “Rstudio”, as long as a number of specific R packages to perform data cleaning, wrangling and reshaping. Basics of data visualization with “ggplot2” and biological gene list annotation will complete the curriculum. Real working life cases will be used as practical examples throughout the lessons.
This course will be useful for all those are in need of the basic semantics of data science because: 1) they are looking for an efficient introduction to R in order to acquire knowledge useful for more advanced R courses; 2) they need to communicate with their fellow bioinformaticians more efficiently; 3) they want to take the road of “data enlightenment” and start a shift in career focusing on data analysis.
Note: even if this course is a basic-R course with biological data examples, its learning outcome can be applied to any domain (finance, banking, social sciences, general data manipulation): so anyone interested in a practical introduction to the use of R for data manipulation is encouraged to participate.
FunGR – Functional genomics with R (Opening soon)
Introductory course (no previous experience required) on methods in functional interpretation of genomics data. The course is highly practical and designed for life science professional (biologists, technicians, clinicians, researchers) and previous bioinformatics experience is not required (but a basic understanding of the R system will help). Participants should have the normal skills of computer usage, such as creating and navigating through files and folders, using spreadsheets and word processors and be familiar with the most common genomics techniques such as RTqPCR, microarrays, sequencing, at least from an experimental design perspective. The course will introduce them to the use of the specific and advanced methods to extract functional and biological knowledge from omics data. Ranking and enrichment methods, gene ontologies, cross annotations, GSEA and/or WGCNA, interaction network and systems biology methods. Specific R packages will be used and a basic introduction to R usage will be also given for those who need it. Other software such as Cytoscape and its plugins will be used beside R. Real working life cases will be used as practical examples throughout the lessons.
This course will be useful for all researchers or life science professionals willing to exploit and better understand their biological data, as well as in need to communicate with their fellow bioinformaticians more efficiently.
R4BS – R for biomedical statistics (opening mid 2018)
Intermediate course (basic knowledge of R will help) on data analysis with a special focus on statistics for life sciences. The course is highly practical and designed for life science professional (biologists, technicians, clinicians, researchers) with little analytical experience: participants should be at ease with the basics of using the scripting software/language R beside having all normal skills of computer usage, such as creating and navigating through files and folders, using spreadsheets and word processors (to those not familiar with R we suggest to take our basic R4BM course). This course will introduce them to the theory and practice of basic to advanced statistical methods used for biomedical data. Distributions, descriptive statistics, hypothesis testing; linear and nonlinear model fitting, correlation; machine learning basics with discriminatory analysis, PCA and clustering; ROC and survival curves, digital biomarkers, Bayesian inference and simulation methods. The statistical scripting software “R” with “Rstudio”, along with a number of specific R packages to perform data analysis will be used.
This course will be useful for all those who want 1) to be more productive and independent with their data analyses; 2) to deeper explore the structure of data, data types, or simply 3) being able to communicate with their fellow biostatistician more efficiently.
NGS-focused training program
2 courses (each: 2 weeks online + 2 live days)
bNGS – Basic NGS & RNAseq. (opening late 2018)
Basic course of Next Generation Sequencing and mRNAseq procedures. The course is both made of theory and practice: it is designed for life science professional (biologists, technicians, clinicians, researchers) without particular bioinformatics experience. Besides normal skills of computer usage, such as creating and navigating through files and folders and using spreadsheets, participants should be familiar with the biological methods used for gene expression such as RTqPCR and microarrays. The course will introduce them to the basic concepts and caveats of next generation sequencing (how it works, coverage, NGS experimental design) and to the underlying statistics. It will then spend the rest of the time analysing a detailed RNAseq protocol through all its steps: base calling, quality control, mapping, counting, quantification, annotation and differential expression at the gene level. Some analytical procedures will be performed using the Galaxy platform (either the public online instance, or our private servers), while a few methods will be experimented live using the statistical scripting software “R” with “Rstudio”, as long as a number of other specific open source software (no previous experience with R or Linux-bash is strictly required, but it would obviously help).
Sequencing de-facto replaced and surpassed microarrays for gene expression applications. This course will be useful for researchers willing to be introduced to simple yet rigorous gene expression analyses by NGS. The ideal participants 1) are looking for a thorough introduction to RNAseq with concepts that can be broadly applied also to other NGS applications (DNAseq, ChIPseq) and 2) they need to work side by side with bioinformaticians delivering NGS results.
xNGS – Exome sequencing for clinical research (opening mid-late 2018)
Introductory course on Exome sequencing and NGS in the clinic. As all our courses, xNGS is a practical course designed for life science professional with a special emphasis on clinicians and biologists doing clinical research. To follow the course participants needs to have common skills of computer usage, such as creating and navigating through files and folders and using spreadsheets, and they should be familiar with the basics of molecular biology of mutations and the underlying statistics. The aim of the course is to practically learn how to discover clinically significant variants using exome sequencing data. From raw files to mapping, variant calling and browsing with genome browsers and dedicated software tools. The main steps of the classic analytical pipeline will be addressed: quality checks, filtering, mapping, variant calling, annotation, ranking.
This course is aimed at biologists, physicians, clinical and life science professionals without a background in data analysis working or 1) willing to directly work with exome sequencing, DNAseq gene panels and 2) willing to learn how to discover new variants, annotate existing ones, filter and compare family genomes.