Bioinformatics

Primary data processing transforms the raw data generated by the sequencing instruments into quality-scored nucleotide sequences (FASTQ format), a requirement for further processing of the data. Additionally, a QC report and checksum files to verify the file integrity of transferred data are generated. This step is an integral part when the sequencing service of the NGS platform at HMGU is used.

User fees & service usage: Included in sequencing service of NGS platform

We offer basic processing of single cell and bulk sequencing data for different platforms and technologies including re-processing of published/public datasets. The computational pipelines perform all necessary steps (e.g. alignment, peak calling, feature counting etc.) required for tertiary analyses and generate a QC report. Please see Computational Pipelines for details.

User fees: Per project depending on the number of samples processed

Service usage: Requests can be submitted to us by using the request forms that are available from here.

Customized analysis is tailored to an individual project and can only be done in close collaboration with the customer. At the beginning of each custom analysis we will schedule a mandatory consultation session to discuss the project in detail as well as possible analysis strategies, milestones and expected results. After accepting the written agreement and provision of a valid payment source we will schedule the work. Customers can expect updates in interim meetings and will  also obtain interim reports and a final report with the results. Upon completion of the project the users will receive all data (pipelines, processed data, analysis code) that were generated for the project.

User fees: Scope and costs will be defined in the proposal and listed in an offer which needs to be accepted by the user.

Service usage: Please contact us to schedule a meeting to discuss the project and setup the proposal.

Together with our colleagues from CF Statistical consulting we reularly run a Data Analysis cafe.  In these sessions we offer consulting e.g around experimental design (prior to start of a project), analysis and computational implementation questions with our users. For more regular consultation we offer Mentoring see separate tab).

User fees: Initial consulting (1h) is free for HMGU members, afterwards hourly billed.

Service usage: Please visit the Data Analysis Café or contact us to schedule a meeting.

This is an extension of a single consultation meeting for those that need more regular supervision while doing the analysis themselves. A platform staff member meets regularly (e.g. once a week for 1h) for with the user. A short proposal will be created with the contents of the mentoring.
User fees: Initial consulting (1h) is free for HMGU members, afterwards billed hourly.
Service usage: Please contact us to schedule a meeting for creating the mentoring proposal.

Helholtz Munich scientist wishing more in depth learning in bioinformatics and NGS-analysis will be embedded into the Bioinformatics team for a limited time (e.g. 3-6 Monate). Scientists will obtain continuous support from core team members for their project, but will also contribute to other projects in the platform. Prerequisits for the service are basic skills in R, Linux-opeatring systems (+ Bash-Scripting) und ideally Python.

User fee: monthly rate, please contact us for more detail

Please note: This service can only be made available when core workload allows.

Our mission is to provide state-of-the-art transferrable, reusable and reproducible bioinformatics analysis pipelines for various next generation sequencing (NGS) applications. The platform wants to always keep up and offer service for the latest research developments. Therefore, we collaborate with PhD students and Postdocs who work on genomics projects and develop new computational pipelines and methods. Researchers profit from the platform's knowledge base and learn best practices on how to develop reusable and transferable workflows. Once developed, the workflows are then offered by the platform as a service to its user base.
User fees and service usage: free for HMGU members, please contact us for capacity and details

Galaxy pipelines

For users with no experience in bioinformatics and just starting with the analysis of NGS data we recommend taking our courses where we provide computational pipelines developed for Galaxy to process RNA-Seq and ChIP-Seq data. Galaxy is a web based platform and does not require the use of command line tools. The Galaxy pipelines are also available from here if you want to use the pipelines on your own using Galaxy.

Advanced computational pipelines

For the following NGS technologies, computational pipelines were established and are available for platform users and projects. These pipelines are developed using workflow frameworks such as Nextflow [1] or Snakemake [2] and are executed on the compute cluster. The usage is best suited for trained users with bioinformatic background and knowledge of Linux and command line usage.

The computational pipelines can be used through our Platform services.

Further information for users regarding the usage of the pipelines is available from here. Please let us know if you are interested in a NGS technology that is not listed so far.

Bulk sequencing:

• RNA-Seq & miRNA-Seq
• ChIP-Seq
• ATAC-Seq
• WGS variant calling

Single cell sequencing:

• 10x-RNA-Seq
• 10x-ATAC-Seq
• 10x-Visum (Spatial Transcriptomics)
• 10x-VDJ (Immune Profiling)
• 10x-Feature-Barcoding
• 10x-Multiome (ATAC-seq + RNA-Seq)
• Drop-Seq
• Smart-Seq
• Single cell variant calling
• Genetic de-multiplexing of barcoded single cell data

References

[1] https://www.nextflow.io
[2] https://snakemake.readthedocs.io/en/stable/

Our courses for RNA-Seq and ChIP-Seq aim to cover the full analysis process end-to-end from reads to results. For our courses we use the publicly available open-source web based Galaxy platform. Galaxy provides a wealth of tools and computational resources for processing data from various omics technologies and allows to build automated workflows.

RNA-Seq course:

Differential gene expression analysis using RNA-Seq data and the Galaxy platform

Your profit: This course covers topics regarding experimental design, introduction and considerations for NGS sequencing, hands on sessions to get from raw sequencing data to count matrices using the Galaxy[1] platform, QCs for RNA-Seq data, sample visualizations, statistical analyses using R and the DESeq2 package[2] and the creation of reports using RStudio and R Markdown[3]. You will create an integrated report using RStudio and R Markdown [3] and have the opportunity to analyze your own data or a published dataset of interest.

References
[1] https://galaxyproject.org
[2] Love, Michael I., Wolfgang Huber, and Simon Anders. 2014. “Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.” Genome Biology 15 (12):550. http://dx.doi.org/10.1186/s13059-014-0550-8.
[3] https://rstudio.com/, https://rmarkdown.rstudio.com

Topics

• Fundamentals of RNA-seq analysis
• Processing of RNA-seq data using Galaxy
• Visualization of sequencing data and analysis of RNA-Seq data
• Integrated RNA-Seq data analysis with R and RStudio

Methods: Presentations, Hands-on sessions and exercises, Homework assignment, Q&A sessions

Mode: During the Corona-pandemic the course is held as an online course

Requirements: Introduction to R and RMarkdown or equivalent courses/experience

Duration: 2 Days
Language: English
Dates and Application: You can check the current dates and whether the courses are already fully booked here*. External customers are welcome if capacity allows. Please apply via the forms of theHR Development department*.

* Links marked with * are only available for Helmholtz Munich staff.

CHIP-seq course:

Differential protein binding to DNA using ChIP-Seq data and the Galaxy platform

Your profit: This course covers topics regarding experimental design of ChIP-Seq experiments, introduction and considerations for NGS sequencing, hands on sessions to get from raw sequencing data to peaks using the Galaxy platform [1], QCs, sample visualizations and the statistical analyses of differential protein binding to DNA using R and the DiffBind package [2]. You will create an integrated report using RStudio and R Markdown [3] and have the opportunity to analyze your own data or a published dataset of interest.

References
[1] galaxyproject.org
[2] Ross-Innes CS et al. (2012). Differential estrogen receptor binding is associated with clinical outcome in breast cancer. Nature, 481(7381): 389–393. dx.doi.org/10.1038/nature10730
[3]rstudio.com,https://rmarkdown.rstudio.com

Topics

• Fundamentals of ChIP-seq analysis
• Processing of ChIP-seq data using Galaxy
• Visualization of sequencing data and analysis of ChIP-Seq data with DiffBind
• Integrated ChIP-Seq data analysis with R and RStudio

Methods: Presentations, Hands-on sessions and exercises, Homework assignments, Q&A sessions

Mode: During the Corona-pandemic the course is held as an online course

Requirements: Introduction to R and RMarkdown or equivalent courses/experience
Duration: 2 Days
Language: English
Dates and Application: You can check the current dates and whether the courses are already fully booked here*. External customers are welcome if capacity allows. Please apply via the forms of the HR Development department*. * Links marked with * are only available for Helmholtz Munich staff.