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:

1. Generation of high-quality reference genome assemblies
2. Structural and functional annotation of genes
3. Identification and phylogenetic analysis of gene families (i.e. R-genes)
4. Prediction of biosynthetic
5. Pathways

Annotation and Gene Prediction

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:

1. Identification of small structural variations (SVs) such as SNPs and DIPs;
2. Identification of large SVs like deletions, insertions, duplications, inversions, genomic rearrangements, Copy Number Variations (CNV) and Presence Absence Variations (PAV);
3. Genome consensus reconstruction;
4. Genome Wide Association Studies (GWAS);
5. High-throughput genotyping;
6. Molecular evolution studies.

Targeted & Exome Sequencing Data Analysis

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:

1. Identification of small structural variations (SVs) such as SNPs and DIPs;
2. Identification of large SVs like deletions, insertions, duplications, inversions, genomic rearrangements, Copy Number Variations (CNV) and Presence Absence Variations (PAV);
3. Genome Wide Association Studies (GWAS);
4. High-throughput genotyping;
5. High-throughput development of molecular markers;
6. Molecular evolution studies.

Metagenomic Sequencing Data Analysis

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:

1. Analysis of species composition and abundance
2. Genome components analysis
3. Generate non-redundant gene catalog
4. Gene functional annotations
5. Comparative analysis among samples