Lexogen Bioinformatics Service
Next-generation sequencing (NGS) technologies are invaluable in academic research, biotechnology, biomedical and clinical research, and the pharmaceutical industry. As NGS technologies rapidly expand and develop, it is imperative to correctly interpret increasingly complex data sets and relate them to biological functions. More than ever, it is necessary to approach NGS data analysis with tailored and creative data analysis workflows to extract the most from the datasets obtained.
Our team consists of genomic data analysis experts with experience in various NGS data analysis pipelines who are passionate about developing novel, customized workflows and solutions while keeping biology at the forefront.
We speak your language, so focus on your research and leave the data analysis to us.
Benefits
- Individual approach: We approach your data with full dedication to extract all the valuable information and make sure you get the most from your experiments.
- Customization and Development: We tailor and/or develop data analysis pipelines to meet your project needs.
- Proficiency: We are genomics data analysis experts with experience in diverse data analysis pipelines and approaches.
- Data Protection: We operate under the European Union Regulation - GDPR, follow ISO27001 principles, and employ various measures to ensure the highest level of data security.
- Continuous support: You will benefit from our expertise before, during and also after the project is completed. We are always there for you.
Our Portfolio
We have extensive experience in handling diverse genomic data analysis pipelines, including various types of RNA-Seq data analysis, DNA-Seq data analysis or epigenetics. Indeed, we can adapt and customize pipelines specifically to your project needs or even develop a new data analysis pipeline for you.
Not sure which approach is the best to analyze your data, or none of the applications listed fit your goals? Get in touch with us at services@lexogen.com to schedule a free consultation!
Differential Gene Expression analysis
Differential Gene Expression analysis, also known as DGE analysis is used to identify changes in gene expression levels between different biological conditions, such as different genotypes, treated and untreated samples, or in disease-related research. Differentially expressed genes provide valuable insights into the underlying drivers and affected processes of studied phenotypes.
Functional enrichment analysis
Functional enrichment analysis transforms a list of differentially expressed genes into meaningful biological insights. It helps to understand pathways and processes underlying studied phenotypes.
Transcriptome assembly
Transcriptome assembly is a process of de novo transcriptome reconstruction directly from RNA-Seq reads. This method is often employed to study non-model organisms for which no reliable genome or transcriptome assembly exists.
Small RNA data analysis
Small RNAs (sRNAs) are short non-coding RNA molecules, typically ranging in size from 20 to 200 nucleotides. sRNAs play a crucial role in regulating gene expression and are involved in essential cellular processes such as mRNA turnover, translational regulation, and chromatin compaction. microRNAs (miRNAs) are the most extensively studied, and their aberrant expressions have been reported in various diseases, particularly cancer. miRNA-Seq analysis includes differential gene expression analysis of mature and premature miRNAs, discovery of new miRNAs and analysis of verified and predicted miRNA targets.
Alternative splicing analysis
Alternative splicing is a process that gives rise to several different transcripts from a single gene, thus enhancing transcriptome and, consequently, proteome diversity. Alternative splicing is cell-type and developmental stage-specific. Abnormal splicing variants or altered isoform levels have been connected to various diseases and cancers. Alternative splicing analysis involves the detection and quantification of new and known isoforms and the evaluation of new splicing events.
Circular RNA analysis
Circular RNAs (circRNAs) are single-stranded RNAs that form covalently closed loops. While the biological function of most circRNAs remains unclear, they have been found to act as transcriptional regulators and microRNA sponges and even have the ability to code proteins. Moreover, circRNAs exhibit unique expression signatures and have been linked to various diseases, suggesting their potential as diagnostic biomarkers and therapeutic targets.
Alternative polyA site analysis
Alternative polyadenylation (APA) leads to the generation of multiple matured mRNA molecules with variable 3′ ends originating from a single gene. As a key posttranscriptional regulation, APA widely affects RNA metabolism including mRNA maturation, RNA stability, cellular RNA decay and protein diversification. Consequently, APA plays a significant role in various cellular processes and its dysregulation has been described in cancer.
Internal priming filtering
3′ end targeting libraries predominantly rely on oligo dT primers, which can mis-prime in A-rich regions located across the genome. Internal priming filter helps to identify and retain reads that genuinely originate at the 3′ end polyA sites.
Shape-Seq
Shape-Seq (selective 2′-hydroxyl acylation analyzed by primer extension sequencing) is a technique that allows researchers to study RNA structure. In Shape-Seq, RNA molecules are selectively modified in a structure-dependent manner and these modifications induce mutations in the cDNA during the reverse transcription. Consequently, analysis of the mutation profile in Shape-Seq data provides insights into the structural features of RNA.
ChIP-Seq
ChIP-seq (Chromatin Immunoprecipitation followed by sequencing) is a technique used to investigate protein-DNA interactions on a genome-wide scale. In ChIP-seq protocol, DNA is co-immunoprecipitated with the protein of interest using an antibody specific to that protein. The isolated DNA is then fragmented and subjected to Next-Generation Sequencing (NGS), which allows for the global detection of the protein-DNA binding sites. Thus ChIP-Seq provides valuable insights into gene regulation, biological pathways and their deregulation, which often leads to diseases.
ATAC-Seq
ATAC-Seq (Assay for Transposase-Accessible Chromatin with sequencing) is a technique that is used to detect accessible chromatin landscapes associated with certain cell types. Hyperactive Tn5 transposase enzyme fragments DNA and simultaneously adds sequencing adapter preferably in open chromatin regions, that are more accessible for Tn5 binding. These regions typically correspond to regulatory elements such as promoters, enhancers, and transcription factor binding sites. Thus, ATAC-Seq data provides valuable insights into gene regulation in complex biological processes and diseases.
Germline and somatic variant calling
Variant calling is a method for the detection of changes in DNA, ranging from single nucleotide polymorphism (SNPs) to larger rearrangements like insertions and deletions. Germline variants impact all cells in the body, including germ cells, and can be passed on to the next generation. In contrast, somatic mutations occur in somatic cells during an individual’s lifetime and are not passed on to offspring. Accurate identification of these variants is essential for understanding the genetic basis of diseases, enabling the development of targeted therapies, and advancing personalized medicine.
Single-cell RNA-Seq Analysis (10x and proprietary Luthor technology)
Single‐cell RNA sequencing (scRNA‐seq) is the leading technique for studying transcriptome heterogeneity within individual cells. It enables cell characterization at the transcriptome level, identification of rare but functionally significant cell populations, and addresses complex experimental questions that bulk analysis cannot answer. We offer analysis of several scRNA-Seq data types, including 10x and our proprietary Luthor technology. scRNA-Seq data analysis can be used for cell-type clustering, marker identification, trajectory analysis, and many other types of analysis.
SLAMseq data analysis
SLAMseq (thiol (SH)Linked Alkylation for the Metabolic Sequencing of RNA) enables transcriptome-wide analysis of RNA synthesis and turnover by measuring nascent RNA expression and transcript stability. SLAMseq combines the labeling of newly synthesized RNA transcripts with RNA-Seq readout. SLAMseq technique can be coupled with whole transcriptome sequencing or 3’ mRNA-Seq for cost-efficient, high-throughput screening setups. SLAMseq data allows transcript half-live estimation and analysis of differential RNA production or decay. Thus SLAMseq is a great tool for studying the effects of fast-acting drugs or drug candidates on RNA kinetics.
Whole-exome and whole-genome sequencing
Whole-exome sequencing (WES) is a targeted sequencing approach that focuses on analyzing protein-coding regions of the genome, known as the exome. This method provides valuable insights into the genetic basis of diseases, facilitates the identification of pathogenic mutations, and supports personalized medicine approaches. Since the exome represents only about 1-2% of the entire genome, WES is more cost-effective compared to whole-genome sequencing (WGS). On the other hand, WGS is the method of choice when a comprehensive analysis of the entire genome is required, including coding and non-coding regions, as well as mitochondrial and chloroplast DNA, or for identification of novel genomic variants.
De-novo genome assembly
De-novo genome assembly is used for organisms without known genome references or for organisms with highly dynamic genomes. The process usually begins with assembling short reads into longer sequences – contigs that are subsequently organized into scaffolds and, in the end, into chromosomes.
Primer design for rRNA depletion
Total RNA is comprised of large amounts of ribosomal RNA (rRNA) which can make up between ~80 – 98 % of all RNA molecules in a sample. rRNA depletion removes these undesired transcripts to access transcripts of interest. If you work with less common species and struggle with rRNA depletion for your RNA-Seq experiment, we offer the primer design using our proprietary advanced algorithm.
None of the enlisted analyses fit your needs? Consult with us at services@lexogen.com for Custom Data Analysis.
Data output
Depends on your project.
All data outputs will be outlined in the offer you will receive from us after Introductory Consultations.
Working with us
Introductory Consultations & Project Planning
We start with an introductory consultation. This is an opportunity to get to know each other, and that we understand your research questions and get to the heart of your project. Only then can we select and design data analysis workflow and deliverables that best meet your needs. Based on this initial consultation we will plan the project, and as a result, you will receive a list of deliverables, along with cost and timeline information for project completion.
Project Initiation & Data Transfer
After you send us the purchase order, we start the project and wait for your data! You can choose from several options for data transfer, including FTP server transfer, cloud bucket sharing or a hard drive shipment.
Data Analysis, Delivery of Results & Report
Upon completion of the data analysis, we will generate a report based on all deliverables, and send you results data and the report, including detailed methodology, using your preferred data transfer method.
Discussion & Conclusion Meeting
We want to make sure that you have a clear understanding of the provided results and that they meet your expectations. Therefore, we will review the results and the report together and answer any questions or concerns you may have.
Follow-up Support
We provide follow-up support for your current or future projects, even after our collaboration is completed. We are here for you if you have any questions or need additional assistance!
