Bioinformatics tools immunology

Seurat aims to enable users to identify and interpret sources of heterogeneity from single-cell transcriptomic measurements, and to integrate diverse types of single-cell data. Cell Ranger: Cell Ranger is a set of analysis pipelines that process Chromium single-cell RNA-seq output to align reads, generate feature-barcode matrices and perform clustering and gene expression analysis.

Deseq2: An R package to estimate variance-mean dependence in count data from high-throughput sequencing assays and test for differential expression based on a model using the negative binomial distribution.

Hepatitis C virus and HIV are rapidly mutating viruses. They have adopted evolutionary strategies that allow escape from the host immune response via genomic mutations. Recent advances in high-throughput sequencing are reshaping the field of immune-virology of viral infections, as these allow fast and cheap generation of genomic data.

Leung et al. Using next generation sequencing data from longitudinal analysis of HCV viral genomes during a single HCV infection, along with antigen specific T-cell responses detected from the same subject, the authors prove the applicability of these tools in the context of primary HCV infection. The proposed pipeline is a freely accessible collection of tools see the paper for details.

Kenn et al. They draw on a well-known target function for clustering and first show mathematically that the assignment of atoms to clusters has to be crisp, not fuzzy, as hitherto assumed, proving that this method reduces the computational load of clustering drastically, demonstrating results for several biomolecules relevant in immunoinformatics.

In the paper by R. Ribarics et al. In the paper, they discuss the variability of spline models underlying the geometric analysis with varying polynomial degrees of the splines. HIV represents a widespread viral infection without cure. Drug treatment has transformed HIV disease into a treatable long-term infection. However, the appearance of mutations within the viral genome reduces the susceptibility of HIV to drugs.

In the paper contributed by M. Haering et al. Their results indicate that early therapy initiation within 2 years after infection is critical to delay AIDS progression. National Center for Biotechnology Information , U. Biomed Res Int. Predicting post-translational modifications Post-translational modifications of a protein can include phosphorylation, glycosylation, ubiquitination, methylation, and lipidation amongst many others.

Figure 2. Table 2 A representative collection of bioinformatic tools for post-translational modification PTM prediction. Identifying conserved motifs Some regions of a gene are more susceptible to the accumulation of mutational change over evolutionary time than others and protection from change is largely due to the biological importance of such a region Figure 3.

Figure 4. Table 3 Summary of publicly available software for the modeling of macromolecular structures. Along with. Python script plugins For download on all major platforms Pettersen et al. Great introductory animation at URL Web applet Protein structural predictions However, even if an experimentally verified protein structure such as those in PDB does not exist for a protein of interest, predictions as to the potential secondary structure of a protein can still be made based on the primary protein sequence.

Figure 5. Table 4 Tools for the prediction of secondary structure characteristics. Figure 6. Genetic Variation Analysis of single-nucleotide polymorphism The most common type of variation within the human genome are single-nucleotide polymorphisms SNPs , which occur, on average, every base pairs Table 5 Publicly available single-nucleotide polymorphism SNP databases.

Displays information on phenoytpes, genes, regions, or markers based on SNPs Web applet Fredman et al. Displays summary information regarding isoforms, SNPs, and other features of genes or proteins Web applet Flicek et al.

Figure 7. Figure 8. Further Analyses What has been covered here represents the basic knowledge upon which most bioinformatic analyses will be conducted. Concluding Remarks In our opinion, bioinformatics is a methodology that is under-utilized in immunological studies. Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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