This is a crush course on a complete, standard RNA-Seq data analysis. It includes quality control and filtering, read mapping, ab initio and de novo transcriptome assembly, estimation of gene expression values, differential expression analysis, small RNA identification and even more. We provide ready-to-use solutions and pipelines so that each participant should be able to perform similar tasks himself.
This is an introductory course for anyone whose aim is to learn how to deal with large-scale RNA-Seq data and to obtain biologically relevant insights. It is tailored for those who work in the fields of biotechnology, molecular biology, bioinformatics, or any other biological sciences, yet anyone can participate. Prior knowledge of NGS data analysis is not essential, however it is advised that the participants know basics of molecular biology, such as what is splicing, splicing isoform, transcriptome, gene expression etc. Also, no programming skills are required.
Upon completion of the workshop, the participants should know about RNA-Seq data sources, their formats, and be able to perform data quality control, read mapping to reference sequences, estimate gene/transcript expression values, and perform differential expression analysis, including interpretation of obtained results. The participants will also learn about transcriptome assembly methods and small RNA analysis and should be able to apply analytical pipelines in their own projects. Also, much emphasis will be put on data visualization, plotting, interpretation, and troubleshooting.
Fig. 1. Visualizing NGS data in a genome browser. Here, we show transcriptome assembly and the corresponding read mapping results together.
Fig. 2. Visualizing NGS data in a genome browser a Sashimi plot.
Fig. 3. A KEGG pathway analysis for differentially expressed microRNAs.
Fig. 4. A quality control for BAM files: inspecting genome coverage.
Fig. 5. Clustering of differentially expressed genes between test and control samples.
Fig. 6. MA plot, one of essential diagnostic plots for differential expression analysis.
No programming skills are required. Also, prior knowledge of NGS data analysis is not essential, however it’s advised that the participants know basics of molecular biology, such as what is splicing, splicing isoform, transcriptome, gene expression etc.
This module introduces a Linux operating system, a powerful – yet often discouraging – environment for bioinformatics applications, such as NGS data processing. We will learn about commands that help working on huge datasets, including search and browsing of NGS-related data. We will learn basics of scripting and exercise various commands that enable automatization and control of data flow during a bioinformatics application. After a single day you should feel quite comfortable using this operating system and be well prepared for the following bioinformatics applications.
This is an introductory course to NGS data processing: starting with raw sequencing results in a FASTQ format, through different methods for data quality check, filtering, adapter trimming and read mapping to finally assemble a transcriptome. In a single day, you will learn a complete, functional pipeline for NGS application. Additionally, NGS-related formats, databases and knowledge bases will be discussed.
Alternative approaches for RNA-Seq data processing will be discussed and excercised, including estimation of gene and transcript expression levels, and differential expression analysis – all this using two or three alternative approaches. Ab initio (with mapping to genome) and de novo (genome-independent) transcriptome assembly will be performed, followed by basic annotation of the results. Essential diagnostic plots and quality checks will be done. Also, smallRNA-Seq data analysis will be introduced, including identification of microRNAs and short read annotation.
We have been on the market since July 2013 and since then we have organized dozens of bioinformatics workshops with almost one thousand of participants altogether. We have completed a number of NGS projects for our customers, which included model and non-model organisms, from bacteria to human. We are a part of consortium aiming at development of personalized medicine services for diagnosis and therapy of lung cancer. We are also conducting academic research in the area of genomics and transcriptomics, which provides us with expertise on standard and up-to-date bioinformatics solutions.
Data Scientist at ideas4biology; an university adjunct
Research interests: molecular functions of long noncoding RNAs and small regulatory RNAs; evolution of gene structures
The cost of participation in the workshop (4 days) is EUR 599. We provide teaching materials, computers with appropriate software, certificate of participation, coffee and lunch breaks. You might, however, choose to participate only in one or two parts of the workshop, as they constitute complete and independent units.
For persons coming from the same institution, as well as for those who register to another workshop from our offer a 10% discount applies. You can save EUR 151 by attending the whole workshop. To make sure the above reductions are effective, please leave a comment during registration.
Payment should be transferred to the following bank account:
IBAN number EUR: 83 2490 0005 0000 4600 6031 7315 SWIFT code: ALBPPLPW
Transfer title should contain your full name. Please make sure the transfer is effective at least one day before the workshop.
Course language: English
Data used throughout the workshop will be made downloadable to all participants,
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