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Data Analysis

WHOLE-EXOME SEQUENCING DATA ANALYSIS

Exons make up about 1.5% of the total genome in humans. Despite the low proportion of exons, these protein coding regions harbour up to 85% of disease-associated variations. Sequencing of exonic regions yields highly relevant genetic variants such as single nucleotide variations (SNVs), small insertions and deletions and structural aberrations that can help to determine the molecular landscape of human disorders.

WES Workflow

To determine acquired variants that distinguish disease conditions from normal conditions, a test and a control sample (i.e. tumor and germline sample) are required for the analysis. Our data analysis pipeline comprises base calling (i.e. creation of fastq files), quality control and alignment of sequenced reads to the reference genome. Subsequent variant calling yields somatic mutations in VCF format which contains, among others, information about the genomic position, allele frequency and annotations of public databases regarding known disease-promoting effects of the identified variations. In addition, copy number analysis is performed to identify structural genomic variations like amplifications or deletions within exonic regions.

SINGLE-CELL RNA SEQUENCING DATA ANALYSIS

2D-clustering of identified cell types of a published human PBMC dataset (10X Genomics).

Single-cell RNA sequencing (scRNA-seq) is a powerful technique to uncover the heterogeneous composition of a given tissue on the cellular level and to reveal the contribution of diverse cell populations to the tissue’s complex expression pattern. ScRNA-seq is also applied to dissect the trajectories of different cell lineages in various states of differentiation or development.

State-of-the-art analysis of scRNA-seq comprises doublet detection, normalization, dimension reduction by principal component analysis (PCA) and clustering using different methods (i.e. tSNE or UMAP). Cell types are identified by integrating clustering and gene expression data with subsequent evaluation of the expression profiles of known marker genes.

3D-clustering of identified cell types of a published human PBMC dataset (10X Genomics).

In addition, immune cell profiling can be performed using the 10x GenomicsTM V(D)J enrichment technology to uncover a sample’s lymphocyte repertoire. In detail, T cell diversity is determined by identifying full-length α and β chain sequences of T-cell receptors whereas B cell diversity is revealed by identifying full-length light and heavy chain antibody sequences.

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