We are waiting for programmers, biologists and bioinformatics.
Each day of course you will study from 11am ere night
NGS technologies: theory and practice Maria Logacheva Physical principles and technological solutions. Typical data: output size, runtime, read length, paired and strand-assigned reads, error types and rates, etc. Cost-performance. Typical use cases for different platforms
Preprocessing of data Quality control. Trimming, sequencing error correction, digital normalization
De novo genome sequencing Artem Kasianov Choice of platform. Selection of libraries (insert size). Genome assembly. Single-cell sequencing and assembly. Whole genome alignment, synteny blocks. RNA-Seq de novo assembly
Introduction to R and statistics Pavel Mazin Statistical tests, robustness, multiple testing, false discovery rate Dimension reduction. Clustering methods. Regression and ANOVA, discrete distributions, GLM, log-likelihood text. Biological variability (overdispersion)
Statistical analysis of transcriptomic data Pavel Mazin Classification and machine learning methods (linear and quadratic discriminant analysis, support vector machines, neural networks, decision trees. lm/anova; glm/anodev. Data normalization and analysis of gene expression: edgeR, limma, DESeq Analysis of alternative splicing, clustering, interpretations of results (annotation of gene sets, hypergeometric test, GOStat, GSEA etc.)
Раковая Genome resequencing Elena Nabieva, Michail Pyatnitsky NGS in medicine: exome and targeted sequencing. Short-read mapping. SNP and short indel calling. SNP evaluation. Intro to cancer: background, cancer evolution, passenger and driver mutations, analysis of functional subsystems. Cancer genomics: somatic mutations
Epigenetics Methylome. DNAse I analysis. Epigenetics-II: histone modifications
Functional annotation and metagenome analysis Sophia Garushnyants NGS approaches and aims. Assembly and annotation of metagenomes
ChIP-Seq Ivan Kulakovsky Pre-NGS experimental methods to study protein-DNA interaction. Wet-lab + dry-lab workflow overview. Applications: brief overview. Dry-lab details (TF binding): peak calling, motif discovery & finding
Personal project Everybody Instead of homework. Personal project review. Comments and corrects on the big screen. Q&A
Application and Fee
Tuition fees is 30 000 rubles for independent participant, 35 000 rubles for academic staff, 40 000 rubles for corporate participant. All inclusive: residence in Pushchino, meals, transfer from Moscow and back
Application is finished. We will tell about vacant position or the next course date
We will respond you during the day. Maximal number of participants is 16.