T19 – Analy­sis of Compo­si­tio­nal Micro­bio­me Data

Tag, Uhrzeit, Dauer

Donners­tag, 9–18 Uhr, 8h

Ange­bo­te­ne Sprache



Since the deve­lo­p­ment of modern next-generation sequen­cing (NGS) tech­ni­ques, coll­ec­ting data to descri­be micro­bi­al commu­ni­ties has beco­me more effi­ci­ent, and an incre­asing number of studies stri­ve to inves­ti­ga­te the inter­ac­tion of bacte­ri­al commu­ni­ties colo­ni­zing the human body with health and dise­a­se of the host. Repro­du­ci­bi­li­ty, howe­ver, remains a major issue in micro­bio­me rese­arch. Hete­ro­gen­ei­ty arises not only from biolo­gi­cal varia­ti­ons, but also from the complex natu­re of micro­bio­me data, such as compo­si­tio­na­li­ty, high-dimensionality and zero-inflation, and the chal­lenges to adequa­te­ly accom­mo­da­te for those charac­te­ristics in the study design and statis­ti­cal analy­ses. The aim of this tuto­ri­al is to equip all parti­ci­pan­ts with the neces­sa­ry skills and tools to inter­pret and criti­cal­ly ques­ti­on the results of micro­bio­me studies, to be able to perform their own basic micro­bio­me analy­ses and to be able to criti­cal­ly revi­se the assump­ti­ons and the possi­ble advan­ta­ges and disad­van­ta­ges of common and novel metho­do­lo­gy. The tuto­ri­al will be a combi­na­ti­on of mini lectures to intro­du­ce the core concepts of micro­bio­me rese­arch and hands-on tuto­ri­als to rein­force and apply the concepts cover­ed. After comple­ting the cour­se, the parti­ci­pan­ts will (1) have a basic under­stan­ding of the micro­bio­me data coll­ec­tion process cove­ring ampli­con sequen­cing and shot­gun meta­ge­no­mics, bioin­for­ma­tics proces­sing, clus­te­ring into opera­tio­nal taxo­no­mic units (OTUs) or ampli­con sequence vari­ants (ASVs) and taxo­no­mic clas­si­fi­ca­ti­on and anno­ta­ti­on. The parti­ci­pan­ts will be able to (2) import micro­bio­me data into common data formats (phylo­seq / Tree­Sum­ma­ri­zedEx­pe­ri­ment) in R, apply common data trans­for­ma­ti­ons (rela­ti­ve abun­dan­ces, log-ratio trans­for­ma­ti­ons) and to (3) calcu­la­te and under­stand the most wide­ly appli­ed ecolo­gi­cal para­me­ters such as alpha (i.e., Shan­non diver­si­ty) and beta diver­si­ty (i.e., Bray-Curtis dissi­mi­la­ri­ty). The parti­ci­pan­ts will further (4) under­stand the concepts of diffe­ren­ti­al abun­dance analy­ses and will be able to perform diffe­ren­ti­al abundance

Fach­li­che Voraussetzungen 

For this tuto­ri­al, you will need a basic under­stan­ding of R to follow along. The tuto­ri­al will cover all neces­sa­ry concepts and provi­de examp­les for you to learn from.

Tech­ni­sche Voraussetzungen

To parti­ci­pa­te in this tuto­ri­al, you will need a laptop with the latest versi­on of R and R Studio instal­led. In addi­ti­on, make sure to install the follo­wing packa­ges to follow along with the analy­ses: tidy­ver­se, phylo­seq, mia, MiaViz, vegan and micro­bio­me. If you encoun­ter any diffi­cul­ties with these prepa­ra­ti­ons, plea­se don’t hesi­ta­te to cont­act the orga­ni­zers for assistance.


Sven Klei­ne Bardenhorst


Insti­tut für Epide­mio­lo­gie und Sozi­al­me­di­zin, Univer­si­tät Müns­ter, Münster


klei­ne­ba [at] uni-muenster.de

Zusätzliche Referentin

Nico­le Rübsa­men, PhD


Insti­tut für Epide­mio­lo­gie und Sozi­al­me­di­zin, Univer­si­tät Müns­ter, Münster