The possibilities in biological and sequencing data analysis are ever-expanding. The correct analysis and integration of biological data is becoming a hurdle in many research projects. Our expertise in pipeline development and automation, data integration, and structural biology data analysis allows us to provide bioinformatics services of the highest standard. We provide data analysis services for data generated by a wide range of sequencing platforms. We use cutting-edge bioinformatics algorithms and pipelines to provide you with high-quality, publication-ready figures.
Our bioinformatics staff consists of infrastructure for biological analysis that is a combination of custom-built and open-source software. Our bioinformatics services take your raw next-or third-generation data and provide you with comprehensive figures customized for your research purposes as well as personalized data interpretation support. GenomeBeans full range of bioinformatics services could be an ideal solution for you. We specialize in customizing the bioinformatics pipeline for your specific projects. We support companies, institutions and research groups by turning ideas into project plans and implementing them, thereby making full use of your data.
GenomeBeans provides statistical and bioinformatics data analysis services that help our customers explain large amounts of data generated by sequencing experiments.
The GenomeBeans consultants combine great expertise in bioinformatics with excellent communication and project management skills. In addition, during each project, our consultants have the support of the entire GenomeBeans team and experts. If desired, we ensures close collaboration, easy communication and regular follow-up meetings between the customer, the consultant, and the GenomeBeans experts ensure total customer satisfaction.
Bulk transcriptomics is an application next-generation sequencing to reveal the presence and quantity of RNA in a biological sample at a given moment, and analyzing continuously changing cellular transcriptome.
The bulk RNA-seq pipeline can be used for both replicated and non-replicated, de novo or reference based, paired-ended or single-ended, and strand-specific or non-strand-specific RNA-seq librarie?s. It measures the abundance of resulting data and can be interpreted in multiple ways: first, in terms of transcriptional activity; and second, in terms of analysis stability. Bulk RNA-seq experiments are specifically designed to gather information about cell transcriptome.
Single cell sequencing examines the sequence information from individual RNA cells with optimized next-generation sequencing technologies, providing a higher resolution of cellular differences and a better understanding of the function of an individual cell in the context of its microenvironment.
Transcription can also be studied at individual cells by Single-cell transcriptomics. It is a recently developed technique that allows the analysis of the transcriptome with respect to individual cell. With single-cell transcriptomics, a specific cell type might be overexpressed in the sample. Single-cell transcriptomic techniques have been used to characterize rare cell populations such as circulating tumour cells, cancer stem cells in solid tumors, and embryonic stem cells in mammalian blastocysts.
It is the process of determining the whole DNA sequence of an organism's at a single time. This entails sequencing of an organism's chromosomal DNA as well as DNA contained in the mitochondria whether it is somatic genomics or germline genomics.
It provide the raw nucleotide sequence of an individual organism's DNA at a single point in time. Further analysis must be performed to provide the biological or medical meaning of this sequence, such as how this knowledge can be used to help prevent disease.
Variation is the difference in DNA sequences between individuals within a population. Variation occurs in germ cells, and also in somatic cells. Variant calling is the process by which we identify variants from sequence data.
The workflow in variant calling includes analysis and identification of variants associated with a specific trait or population. It also provides us with a standardized framework to describe variants. Carry out whole genome or whole exome sequencing to create fastq files. Align the sequences to a reference genome, creating BAM files. Identify where the aligned reads differ from the reference genome and write to a VCF file.
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