CD Genomics proprietary GenSeqTM Technology provides Genomic Data Analysis service. We have extensive experience in helping solve a wide variety of bioinformatics problems.
What Is Genome Data Analysis?
Genome data analysis encompasses the intricate process of scrutinizing and interpreting the vast repository of genetic information nestled within an organism's genome. The genome, comprising the entirety of DNA, spanning both coding and non-coding regions, constitutes an individual's genetic blueprint. To unravel the hidden insights embedded in genomic data, sophisticated bioinformatics tools and computational techniques are harnessed, facilitating the extraction of meaningful knowledge.
The fundamental objective of genome data analysis revolves around delving into diverse aspects of the genome, including the identification of genes, regulatory elements, and functional components. Moreover, it entails comprehending genetic variations and exploring genetic relationships within populations and individuals. The significance of genome data analysis extends across a wide array of research disciplines, encompassing genomics, genetics, personalized medicine, evolutionary biology, and biotechnology.
Numerous essential tasks constitute the landscape of genome data analysis:
Sequence Alignment: A pivotal process that involves comparing and aligning DNA sequences with reference genomes to reveal both similarities and dissimilarities.
Variant Calling: The discernment and annotation of genetic variations, such as single nucleotide polymorphisms (SNPs) and insertions/deletions (indels).
Gene Expression Analysis: Unraveling the intricacies of gene expression patterns across different tissues or under varying conditions.
Functional Annotation: Illuminating the roles and functions of genes and regulatory elements to unravel their biological significance.
Comparative Genomics: Uniting genomes of distinct species in a comparative framework to study evolutionary relationships and identify conserved regions.
Epigenetic Analysis: Investigating DNA and histone modifications to comprehend gene regulation and decipher epigenetic changes.
Metagenomics: Exploring genetic material from intricate microbial communities to discern and characterize diverse species.
Pathway Analysis: Scrutinizing interactions between genes and proteins to gain insight into biological pathways and intricate networks.
Altogether, genome data analysis assumes an indispensible role in decoding the genetic information inscribed within an organism's DNA. Its significance extends far and wide, invigorating the advancement of our knowledge in genetics and biology. Moreover, it finds practical applications across diverse domains, including medical diagnostics, drug development, and agricultural research.
Our Genomic Data Analysis Service Package
With sequencing technologies now producing millions of high quality reads per run, working with sequence data has become a significant obstacle for many researchers. At CD Genomics, we have staff of dedicated bioinformaticians with extensive experience in overcoming these and a variety of other challenges that researchers face every day. We offer the following genomic data analysis services:
De Novo Sequencing Data Analysis
De novo sequencing can be used to sequence uncharacterized genomes if there is no available reference sequence or known genomes if significant variations are expected.
The general strategy of de novo sequencing analysis is to align and merge short fragments derived from a much longer DNA sequence in order to reconstruct the original sequence. de novo sequencing projects usually take multiple libraries and multiple rounds of finishing to get a complete genome sequence.
With our de novo Sequencing Data Analysis service, we are able to provide:
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Generation of high-quality reference genome assemblies
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Structural and functional annotation of genes
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Identification and phylogenetic analysis of gene families (i.e. R-genes)
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Prediction of biosynthetic
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Pathways
Once the genome of an organism has been sequenced and assembled, genes must be identified in order to understand the functional content of the genome. For this reason gene prediction and annotation are among the most important steps of a genomic project. The goal of annotation is to identify the key features of the genome, in particular protein-coding genes and their products.
We are able to use data coming from de novo or resequencing projects to perform gene predictions, small and large non coding RNA annotation, identification of specific gene and protein families and pathways.
Genome Resequencing Data Analysis
Once you have the reference sequence for an organism, you can utilize next-generation sequencing to perform comparative sequencing or resequencing to characterize the genetic variations in individuals of the same species or between related species.
With our Genome Resequencing Data Analysis service, we are able to provide:
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Identification of small structural variations (SVs) such as SNPs and DIPs;
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Identification of large SVs like deletions, insertions, duplications, inversions, genomic rearrangements, Copy Number Variations (CNV) and Presence Absence Variations (PAV);
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Genome consensus reconstruction;
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Genome Wide Association Studies (GWAS);
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High-throughput genotyping;
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Molecular evolution studies.
Due to high sequencing and data management costs associated with whole genome resequencing, Targeted Resequencing provides a time- and cost-effective alternative. Targeted Resequencing, including Exome Sequencing, primarily focuses on detecting SNP and small Indels.
With our Targeted & Exome Sequencing Data Analysis service, we are able to provide:
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Identification of small structural variations (SVs) such as SNPs and DIPs;
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Identification of large SVs like deletions, insertions, duplications, inversions, genomic rearrangements, Copy Number Variations (CNV) and Presence Absence Variations (PAV);
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Genome Wide Association Studies (GWAS);
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High-throughput genotyping;
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High-throughput development of molecular markers;
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Molecular evolution studies.
Metagenomics is the study of genomes contained within an entire microbial community. Metagenomic sequencing focuses on microbial community diversity analysis, gene composition and function, as well as metabolic pathways associated with the specific environment.
With our Metagenomic Sequencing Data Analysis service, we are able to provide:
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Analysis of species composition and abundance
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Genome components analysis
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Generate non-redundant gene catalog
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Gene functional annotations
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Comparative analysis among samples
Analysis Cases:
For Research Use Only. Not for use in diagnostic procedures.
Sample Submission Guidelines
