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Genome Data Analysis


Solutions and Services to manage and analyze genomic data

Our Solution | Benefits | The TCS Advantage | A Collaborative Project

Download Brochure:  Genome Data Analysis  (PDF, 361 KB)

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In an ongoing attempt to identify the genetic cause of human diseases, and assist the development of specialized treatments and, potentially, personalized cures, researchers globally are engaged in DNA analysis. With significant inroads made into DNA sequencing and annotation technology, researchers are focusing on variant calling and interpretation – the analysis of DNA sequence anomalies or variations. The process though, is encumbered by the many manual steps required to assemble raw data sequences, create DNA annotations and root out false negatives and errors in variant call data. Manual sample preparation processes, delays caused by batching samples for costefficient runs, and the speed and quality of data analysis, are the other challenges enterprises face.

Our Solution

Working with the Center for Computational Biology at the University of California, Berkeley, TCS has developed solutions for the rapid interpretation of genome variation data. Our Genome Data Analysis solution, a pipeline for the automated execution of genome sequence analysis, includes open source and TCS developed software, and is complemented by our algorithms for the efficient archival of genomics data.

With a rich set of variant annotations that integrate data from several sources, support for end to end data querying and workflow management, and the ability to represent analyzed data interactively, the Genome Commons Navigator is intended for use by the larger scientific community to promote continuous testing, validation, and refinement of the solution. The Genome Commons Navigator, an extensible infrastructure that allows investigators to efficiently collect and analyze an individual's genomic data as well as compare the genomic data of multiple individuals. It can be provided either as a Business Process as a Service (BPaaS) or Software as a Service (SaaS).

We offer the following:

NGS data analysis: End-to-end analysis of data from multiple human genome samples to identify disease causing mutations using a variety of inheritance models, including:

  • Primary analysis - Mapping raw reads and quality scoring
  • Secondary analysis - Alignment /assembly, marking duplicates, realigning around INDELS, base quality recalibration and variant calling, using different approaches and choosing a consensus best set
  • Tertiary analysis - Gene/ protein annotation; region/ gene inheritance models, gene/ protein function based single/multiple sample analysis, exploratory analysis

NGS data storage and archival: Algorithms to efficiently store and archive NGS datasets.

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With our Genome Commons Navigator and archival algorithm's ability to rapidly analyze, efficiently store and manage, genetic data, you:

  • Identify better targets for drug discovery
  • Re-position existing drugs for new indications
  • Check directly for desired phenotypic response with a large number of drug candidates
  • Determine the right medication and right dosage

By leveraging our services and software pipelines for genome analysis, you:

  • Exchange and manage genetics data easily based on developed standards and ontologies
  • Send lab results in different formats, compatible with different platforms
  • Deploy the solution to best address your organization’s needs, with the flexibility of choosing the service or software model
  • Scale up on a need basis, harnessing our services and HPC infrastructure
  • Realize significantly higher genome data storage and transmission cost savings when compared with other popular compression algorithms

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The TCS Advantage

TCS' joint research project with the University of California focused on the building of a robust software platform for identifying the genetic basis of diseases and inherited traits to improve patient care. We deliver this through:

  • Cutting edge, cost effective innovation: Our solution is an amalgamation of computer science, experimental biology, and model systems from UC Berkeley's Center for Computational Biology and our IT, global delivery, and consulting services. An accurate and extremely cost effective solution, it has been benchmarked and has yielded results that match with the results expected of the gold standard.
  • Updated and relevant knowledge: In addition to creating, maintaining and improving the platform, we regularly update it with new genomics algorithms. Our Genome Commons Navigator allows the addition of follow-on plug-in modules by UC Berkeley scientists and the broader scientific community to ensure that the platform reflects current knowledge in genomics research
  • Comprehensive and cost effective solution: Our end to end solution, from the software perspective, includes a pipeline for the automated execution of exome and whole genome sequence data starting from the mapping of raw reads to the calling of variants. With extensive data annotation, it supports in-depth analysis that spans the complete workflow - data quality, sample tracking and downstream genotype, phenotype, and pedigree analysis.

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A Collaborative Project

The State of California’s TREC program screens infants to identify Severe Combined Immunodeficiency (SCID). SCID is caused by defects in genes which have few or absent T cells. This can prove fatal for newborns, as they succumb to infections. Though their immunity is compromised, infants with SCID appear healthy, further complicating the task of identifying them before they catch infections.

Two infants were identified by California TREC newborn screening program. Though clinically well, the infants had low immunity response. Whole exome sequencing was performed to identify variations in genomes that were leading to this rare disease. Sequencing of the genome was performed at UC labs and TCS analyzed the exome data using the Genome Commons Navigator.

Our solution filtered genome variants against a list of genes associated with T cell development. This exercise helped find two damaging heterozygous Ataxia telangiectasia mutated (ATM) mutations. This information was used to educate the families about this condition as well as ensure that all future medical treatment would be planned taking into account the infant’s ATM mutations. Genome Commons Navigator helped in proactively detecting an abnormal gene in these infants and has allowed for appropriate care against the possible complications.

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Download Brochure:  Genome Data Analysis  (PDF, 361 KB)

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