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Gene Expression Analysis
Services:
Our basic expression analysis service
involves:
- Experimental data processing
- Normalisation
- Data filtering
- Principal Component Analysis - enables the identification of
outlier samples.
- Statistical analyses to identify differentially expressed
genes
- Annotation of the differentially expressed gene lists with gene
identifiers and functional information.
Source BioScience LifeSciences can provide both additional
and customised services such as:
- Clustering (hierarchical and non-hierarchical) of the gene
expression data.
This groups together genes with similar profiles and discovers
gene relationships.
- Gene ontology analysis.
Assessing the content of differentially expressed gene lists in
terms of their predominant biological themes.
- Inference of biological networks from gene expression
microarray data.
- Gene set enrichment analysis (GSEA) - Evaluates expression
microarray data at the level of gene sets (pathways).
Genotyping Analysis Services:
Our basic genotyping analysis service
involves:
- Experimental data processing
- Data filtering (for example using Hardy-Weinberg equilibrium,
missing genotypes)
- Genotype calling
Source BioScience LifeSciences can provide both additional
and customised services such as:
- Statistical tests for association (using various models, eg:
dominant / recessive) and sample clustering.
- Visualisation and determination of the Linkage Disequilibrium
(LD) structure within the genotype data.
- Identify genes and gather all forms of annotation in the
genomic regions of interest.
- Integrate genotype data with expression data to identify
genomic regions regulating expression.
- Haplotype estimation and haplotype association analysis.
- Genomic structural variation identification, CNV and LOH
analysis from SNP microarray data.
- Perform pathways network-based analyses of associated genes
with Ariadne Pathway Studio.
Biological Pathways
Analysis:
We use the industry leading commercial
software - Ariadne Pathway Studio to provide our customers
with a pathway networks analysis service. Pathway Studio enables
in-depth analysis of any list of interrelated biological data (eg:
expression and SNP microarrays, proteomics and metabolomics
data).
Our pathways analysis service enables
customers to :-
- Retrieve biological meaning from microarray and other high
throughput data sets.
- Discover pathway network relationships within your data in the
context of known pathways.
- Use text mining algorithms to extract network relationships
within PubMed for your data.
- Build dynamic pathway models from your data.
Next
Generation DNA Sequence Analysis:
Our experienced bioinformaticians provide a
comprehensive bioinformatics service for our Illumina Genome
Analyzer (GA) customers, which enable them to utilise all the
applications that are possible with billions of bases of sequence
data per run.
Our basic GA analysis service
involves:-
- Running the Illumina GA pipeline software and customising the
pipeline for the customer's specific experiment.
- The GA pipeline software implements the image analysis, base
calling and sequence alignment steps.
- Generation of sequence reads, base quality scores and quality
control data to be sent to the customer.
- Providing a detailed report to the customer that interprets the
quality control metrics and sequencing run statistics.
Our bioinformatics team also provide additional services for our
Illumina GA customers that include:-
- Sequence polymorphism and structural variation detection for
re-sequencing projects.
- De novo assembly.
- Digital gene expression analysis.
- ChIP-Seq analysis.
- Visualisation of sequence data within a genome browser.
- Bespoke bioinformatics analysis.
Expert Consultative Service
Our bioinformatics experts can make the appropriate
recommendations for the development of your data analyses
throughout your project. This is from the experimental design stage
to ensure adequate statistically robust data is generated, through
to offering guidance on the most appropriate and latest cutting
edge data analyses methods for your experiment data.
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