Research, Innovation & Impact

Processing and Workflow Methods

BAC has built and maintains several high-throughput, production level, data processing and analysis workflows for other service units on the MU campus that handle common bioinformatics processing needs. These workflows are predominately built using Nextflow to create robust and stable tools utilizing best-practices methods. For researchers who receive data from these workflows, you can find basic information about what processing and/or analysis was done below. If you have questions, please reach out for the latest information.

GTC Processing Workflow

Updated 2021-12-10

All sequencing that comes from the MU GTC is processed through this workflow unless otherwise requested. Raw reads are demultiplexed with bcl-convert (v3.8.2-12-g85770e0b). Reads are then trimmed with fastp version 0.23.1 using default settings. Additional quality control is done by mapping of a sub-sampled portion of the reads to an rRNA reference to check for contamination during sample preparation. This process uses seqtk to sub-sample, minimap2 to map the reads, and samtools stats (v1.14) to determine percentage of reads mapped to a RefSeq rRNA reference. Overall quality control statistics are generated with MultiQC (v1.12).

MUMC Metagenomics Workflow

Updated 2021-12-10

The metagenomics pipelines utilizes the QIIME2 (2021.8.0) metagenomics pipelines. Currently, 16S and ITS amplicon sequencing can be performed with this pipeline, and can be done completely automated for sequencing that is done with the MU GTC, and on-demand for data from other sources. Custom classifiers are built for each analysis type using a naive-bayes model, the 16S classifier is based on the Silva (v.138) 99% reference database, targeted for PE250 reads. The ITS classifier is based on the Unite (v.10.05.2021) 99% reference database.

We recognize that access to sufficient computing resources and informatics expertise is often the rate-limiting step in the type of computationally intense, translational science required for successfully funded proposals due to the cost, time and complexity of the analyses and tools involved. Our team of experts have decades of expertise in developing and implementing best-practices methods in a wide variety of areas of informatics and computational research. We will be happy to work with you to cover those needs and provide a letter of support to help make sure your target funding organization recognizes that you have given proper consideration to these challenges. To request a letter, please complete the Letter of Support Form.

However, we strongly encourage you to reach out and have a brief meeting to discuss your project in-depth as we can’t guarantee outcomes of our support if we are not consulted prior to the submission of your proposal.

It is common for granting agencies to ask for statements of F&E for proposals that will use university services. You can find a general statement of F&E related to BAC below. If you would like to include a more specific statement in your proposal, please reach out to us, and we will be happy to tailor a statement to your project. 

General F&E Statement

BAC serves as a centralized resource for providing expert bioinformatics, analytical and data science consulting and analysis solutions for the MU System as well as public and private industry partners. We offer expertise in high performance compute systems, software, data management and analysis in the primary areas of genomics, statistics and machine learning research. We understand that access to compute resources and informatics expertise is often the rate-limiting step for many researchers in the type of computationally intense approaches demanded of modern biomedical research because of the cost, time, and complexity of the analyses and tools involved. BAC works alongside researchers with the intention of accelerating translational research in these areas by providing consultations on experimental design and analysis using established best practice approaches for sequencing-based projects, traditional statistical analyses, machine learning projects and many other life sciences-based research topics.

Commonly Provided Services

We offer analyses, consultation, and workshops for the following topics, among other services:

• Training and assistance with common scientific programming environments (R, Python, Julia, Nextflow, etc.)

• Parallel and cluster computing assistance

• Scientific application deployment and trouble shooting

• Statistical consulting and analyses

• Custom analysis tool development

• RNA-seq expression analysis, including de novo transcriptome assembly and bulk RNA-seq differential expression

• Single cell RNA-seq workflows and Visium spatial transcriptomic workflows

• Read mapping and variant calling for a variety of resequencing experiments, including RAD-seq, pooled sequencing, and WGS

• Comparative genomics, including whole genome alignment

• Genome assembly and annotation

• Phylogenetic reconstruction and phylogenetic analysis / comparative methods in R

• Methods for metagenomic sequencing and taxonomic classification