The field of immune repertoire profiling has witnessed remarkable advancements in recent years, revolutionizing our understanding of the immune system and its role in various diseases. One of the key techniques to understand this complex mechanism is TCR sequencing. TCR, or T-cell receptor, plays a crucial role in the adaptive immune response by recognizing and binding to specific antigens. By sequencing the TCR repertoire, researchers can gain valuable insights into the diversity and specificity of T-cell populations, leading to the development of novel treatment modalities in infectious diseases, autoimmunity, and immuno-oncology.

Genetic variation can range from changes at the level of single bases to whole-chromosomal aneuploidies. Structural variations (SVs) refer to a large alterations in chromosomal structure, typically encompassing larger than 1 Kbp of DNA. SVs include both balanced changes, such as inversions and some forms of translocations, as well as those that alter DNA copy number through duplications and deletions of chromosomal segments. SVs account for 25% of protein truncating mutations and are 3 times more likely to associate with a genome-wide association study (GWAS) signal than single nucleotide variants (SNVs). SVs contribute to all classes of genetic disease: sporadic development syndromes, Mendelian diseases, complex disorders and infectious diseases, as well as health-related metabolic phenotypes.

Bioinformatics plays a vital role in analyzing complex high-throughput sequencing data, particularly in the realm of single cell research. The ability to analyze and interpret massive amounts of single cell data has revolutionized our understanding of cellular heterogeneity and its implications in various biological processes. The blog explores the capabilities of bioinformatics team at MedGenome in analyzing single cell sequencing data. Here, we explore different types of bioinformatics reports, the importance of data visualization and generation of interactive reports such as differential gene expression analysis, heatmap visualization, interactive tSNE plots with cell type and cluster information.

The advent of single cell sequencing technologies has enabled us to understand and study the complexities of biological systems at a finer resolution. Traditional bulk sequencing methods provide an average representation of gene expression across a population of cells, masking the inherent heterogeneity that exists within a tissue or organism. However, single cell sequencing allows us to capture the maximal transcript diversity in a given cell and allows for a multi-model analysis strategy to generate meaningful insights.

Cite-Seq, short for Cellular Indexing of Transcriptomes and Epitopes by sequencing, is a powerful technology that has revolutionized single-cell sequencing. With its ability to analyze transcriptomes and protein expression at a single-cell level, Cite-Seq has the potential to greatly advance our understanding of cellular heterogeneity and function in biological systems. In this article, we will discuss the workings of Cite-Seq, its current and potential applications in various fields of research, and its limitations.

Single cell sequencing is a cutting-edge technique used in molecular biology that enables the sequencing of the transcriptome of individual cells. In traditional bulk sequencing techniques, RNA is extracted from a large group of cells, and then sequenced as a whole. However, single cell sequencing allows researchers to analyze the genetic material of individual cells, providing a much more detailed and precise understanding of the diversity and heterogeneity of cell populations.

Spatial transcriptomics is a technology that allows the analysis of gene expression patterns within a tissue sample in their spatial context. It enables researchers to obtain a comprehensive and high-resolution view of the transcriptome, the set of all expressed genes, across different regions of the tissue. In traditional transcriptomics, gene expression is measured from homogenized cell populations, which can mask important differences in gene expression between different cell types and regions. Spatial transcriptomics, on the other hand, allows researchers to analyze gene expression patterns in intact tissue sections while retaining their spatial information.

Next-generation sequencing (NGS) data is being increasingly used in clinical diagnosis to identify genetic variation that can be a cause for the disease. A major challenge in using NGS data in a clinical setting is to make the right interpretation because of its huge size and complexity. Also, there are possibilities of technical errors during the sample processing and/or sequencing stage that may be inherent to the kind of sequencing technology used. Therefore, the use of reference standards is of paramount importance to mitigate and minimize these errors.

NGS technologies is at the forefront of Biological Research. They produce enormous data running into gigabases in a single round of sequencing. However, several sequencing artifacts such as read errors (base calling errors and small insertions/deletions), poor quality reads and primer/adaptor contamination are quite common with the NGS data obtained after sequencing. It can impose significant impact on the downstream analysis such as sequence assembly, single nucleotide polymorphisms (SNP) identification and gene expression studies.

Our journey in 2022 was focused on providing the utmost customer experience for the services and solutions that we delivered to you. Along with expanding our portfolio of services and solutions – the tissue dissociation and nuclei isolation services to support our single cell customers, streamlined antibody discovery using high-throughput single B cell receptor sequencing, TSO500 targeted panels for oncology research, single cell and bulk epigenetics assays. We improved our turn-around times on bulk transcriptomics, whole exome and whole genome projects by incorporating automation at multiple project stages and installing new sequencing capacity in 2022. Our sequencing team has delivered high-quality data consistently for a variety of library types throughout the year.