Multiple-omics technologies to obtain a comprehensive readout of
a particular biological system. Multi-omics studies require a rigorous
computational processing and analysis, which are the cornerstones that enable
the subsequent data integration and biological interpretation. In this course
we will cover metagenomics, RNA-seq and metabolomics data analysis with the aim
of retrieving molecular identities from raw data.
The aim of this course is to cover the main basics of multi-omics analysis, from
raw data to pathway analysis.
Multi-omics studies involve
the integration of different -omics technologies to obtain a comprehensive
readout of a particular biological system. Multi-omics studies require a
rigorous computational processing and analysis, which are the cornerstones that
enable the subsequent data integration and biological interpretation. In this
course we will cover metagenomics, RNA-seq and metabolomics data analysis with
the aim of retrieving molecular identities from raw data. The course will also
include hands-on sessions on the use of software like Qiime or XCMS, and
processing workflows in R. Particularly, and with an ever-growing research
community, metabolomics is in high demand by biologists and clinicians thanks
to its unique ability to pinpoint molecular mechanism. This is why the morning
session of the course will cover all the metabolomics workflow steps, ranging
from peak peaking to metabolite annotation and identification, using
state-of-the-art computational software and spectral databases.
