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19.05.2022 17:47:56
Workshop: 50.01.011 Amplicon-Seq Data Analyses - Details
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General information

Course name Workshop: 50.01.011 Amplicon-Seq Data Analyses
Subtitle
Course number 50.01.011
Semester Sommersemester 2019
Current number of participants 8
expected number of participants 20
Home institute Institute for Chemistry and Biology of the Marine Environment
Courses type Workshop in category Teaching
First date Thu., 02.05.2019 09:00 - 17:00, Room: (AH231)
Type/Form Workshop
Lehrsprache englisch
ECTS points 1

Course location / Course dates

(AH231) Thursday. 02.05.19 - Friday. 03.05.19 09:00 - 17:00

Comment/Description

for PhD students of the Research training group EcoMol and the Integrated Research
Training Group of the CRC Roseobacter and PhD program 'Environmental Sciences and
Biodiversity’ and PhD students and PostDocs from HIFMB

Analyses of amplicon-based sequencing technologies have become a state-of-the-art method to analyze
microbial communities in many life sciences areas. Also in the marine microbiology sector, this tool is
frequently used to investigate community structures, as well as activities of certain community members. Yet,
analysis of these sequencing data is an active field of research that advances rapidly. For example, the widelyused
clustering-based technique of operational taxonomic units (OTUs) is now competing with amplicon
sequence variants (ASVs), a method that controls sequencing errors instead of clustering by a fixed dissimilarity
threshold. While several bioinformatic platforms have been available for quite a while, workflows and analyses
can now also be documented and tracked and thus increase the reproducibility of analyses. Several recent
scientific reports also highlight the compositional nature of sequence-based data and propose statistical
methods such as log-ratio transformations or variance stabilization transformations instead of using fractions
or rarefaction for normalization purposes prior to correlation analyses.
This workshop aims to bring the participants up to date on recent data analysis possibilities and good-practice
guidelines (e.g. Qiime2 and Dada2), as well as offering a hands-on experience for amplicon (16S or 18S rRNA)
data analyses. Some previous coding skills in R are beneficial.
Planned themes
• denoising amplicon sequences
• taxonomic annotation and biodiversity
• statistics and analyses workflow of sequence data

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