Oct 20-22, 2014 – Next Gen Sequencing Technology and Sequencing Library Prep Workshop: RNA-seq

Next Generation Sequencing (NGS) has revolutionized the way that we address complex biological questions. As sequencing output rapidly increases and experimental scales get bigger, library preparation becomes one of the major bottlenecks for NGS. This course provides a comprehensive hands-on training on how to prepare high quality libraries for Illumina HiSeq2500 and MiSeq sequencing platforms. Participants are encouraged to bring their own total RNA template and, by the end of the course, will have a library ready for NGS sequencing. Lectures will cover the entire workflow including sample QC/QA, as well as the basic principles of NGS technology and consideration for experimental design meeting current publication standards. The course will highlight applications such as mRNA-seq, ChIP-seq, de novo sequencing, re-sequencing, mutation discovery, single cell genomics, and PacBio RSII. A case example of combinatorial usage of NGS technology to meet specific biological goals of sequencing will be explored.

Protocols covered in this course are compatible with multiplexing as well as with the preparation of PCR-free, ribosomal RNA depleted, and strand specific libraries. As sequencing capacities continually increase, automation of library construction is becoming indispensible. We will demonstrate the automation systems IntegenX Apollo 324 (small – medium throughput) and Caliper Sciclone NGS G3 (medium – high throughput). The workshop will maintain a highly interactive environment to maximize communication among attendees as well as with lab instructors. The workshop will conclude with an evaluation of libraries and a discussion session focusing on each participant’s experimental design to help maximize efficiency and output of sequencing experiments. Course materials and lunches will be provided. For more details, contact Lutz Froenicke (lfroenicke@ucdavis.edu).


LC-MS Data processing and Statistics in Metabolomics, February 9-13, 2014

The LC-MS/MS compound identification part will cover the annotation and identification of unknown compounds using MS/MS search and retention time matching.

Course participants will learn about existing MS/MS databases and free and commercial program solutions for MS/MS search as well as compound identifications strategies for high-resolution tandem mass spectral data. Participants will expand the knowledge about the structure and data formats of LC-MS/MS files (mzXML, mzML) and tandem mass spectra (MGF) and learn how to convert and manipulate such data.

The hands-on training will focus on real-world data sets that were acquired with QTOF-MS/MS. Annotation strategies using accurate mass precursor lookup and accurate mass product ion search will be compared and integrated. The concepts of mass spectral scoring and the impact of different search scoring algorithms will be discussed.

The course will allow participants to readily apply the learned objectives to their own datasets and diverse instrumental setups.

The data analysis and interpretation section will cover major topics in statistical analysis, multivariate methods and biochemical pathway mapping. Course participants will be exposed to common approaches for the analysis of high dimensional biological data sets using freely available software and real-world metabolomic data sets.

A combination of presentations, case studies and hands-on analyses will expose the participant to a variety of statistical approaches including multiple hypothesis testing, false discovery rate adjustment, analysis of correlations and power analysis.

Hands on labs will be used to introduce and gain experience using common multivariate data analysis techniques including: clustering, principal component analysis (PCA), partial least squares projection to latent structures (PLS/PLS-DA), multivariate modeling and feature selection. Biological interpretation of statistical and multivariate results will be enhanced using metabolite over representation (ORA) and pathway enrichment analysis (PEA).

The participants will be introduced to the concept of network mapping and get hands on training in the generation of biochemical, structural and mass spectral similarity networks. Overall emphasis will be placed on data visualization and interpretation of results within biological contexts.

More information and updates may be found on the Metabolomics Core website.


*If choosing to pay by credit card, participants must do so here.