Mimamsia combines both standard pipeline and out-of-the-box approach to arrive at a causative variant

Genetic data analysis is admittedly complex and it combines thorough understanding of the technology used behind, and then addressing the medical aspects related to the findings. In the world of rapidly evolving technology and fast growing information in clinical field, it is challenging to be on top of both. When a clinical diagnosis after Whole Exome Sequencing and particularly Whole Genome Sequencing is negative, one is left stranded if the technology or the missing clinical knowledge holds the clue to the right answer. Often times, one prefers to move ahead and bury the ghosts of failures behind technology and limited understanding of genetics. Mimamsia pursues each negative case with a focus on the limitations in the technology and the overwhelming knowledge that is constantly being acquired.


The VarianT database is growing

Clinically relevant variants added per year in Human Gene Mutation Database (HGMD®) Professional

Based on HGMD Profession release 2018.2

Over last years, information on nearly 20,000 new clinically relevant variants emerged annually in the public literature, based on the information collected by HGMD© Professional alone. This is just the tip of the iceberg, as many variants still remain in the private databases of commercial laboratories that are also increasing. Importantly, this information grows exponentially, that implies, an Exome/Whole Genome case evaluated one year before may not have been assessed with respect to more than 20,000 variants.


More genes are clinically implicated annually

Information on genes (new and updated) added per year in Online Mendelian Inheritance in Man (OMIM®) database

Based on September 2018 release

A human genome encodes roughly 20,000 protein coding genes. As of when the information was compiled (Sept’ 2018), there have been 3,961 genes where a phenotype causing mutation has been described. Not only we are learning over time about roles of new genes in clinical realm, but also about 99% of the genomic regions that does not code for any proteins, and for long has remained a mystery with respect to their exact function. We are only now understanding vaguely what how these regions could be involved in various diseases.


Technology is evolving but each new technology brings its own bias

Rapidly evolving technology allows fast sample to sequencing results. The biases although low, still remain. It is critical to address each of these biases for any unsolved case.

  • sequencing platforms may introduce platform specific errors

  • a 2 dye sequencing chemistry has a different bias than a 4 dye sequencing chemistry over specific sequences

  • different capture kits have their own biases over specific regions

  • tagmentation and sonication present their own inherent biases

  • and the list goes on..


Standard pipeline approaches are tailored to be fast, consistent & effective

Typically, a standard bioinformatics pipeline, including the clinical evaluation is designed to meet the high throughput requirements of a clinical lab to be commercially viable. Even though, they are fast and fairly accurate, there is always a chance that a critical piece information is overlooked at the cost of speed. Biological systems are inherently complex and naturally far away from being perfect. A very simplified example can be

  • a typical variant caller will call approx 98-99% of all the single nucleotide variants with accuracy and consistency in a whole genome. The accuracy drops significantly over in-del variants.

  • one can opt for multiple variant callers, and the overlapping subsets of variants are the most confident ones with high degree of true positives.

Labs typically may focus on these variants over low complexity genomic regions and set their thresholds accordingly to reduce the evaluation burden. In a fast paced clinical environment, high complexity and poor quality regions may be avoided to reduce false positives and thereby avoid the need for hundreds of Sanger confirmation. This in no way implies that these “ignored regions” do not harbor a true mutation. Such an approach allows 97-98% accuracy within a relatively short time, but the missing 2-3% variants get extremely critical once the results turn out to be negative and a different and more tedious approach needs to be adopted to overcome the technical limitations presented by standard pipelines.


KEy FEatures of Our Unique Approach

  • We focus on the WES and WGS clinical cases that have resulted in negative findings, thereby filling the missing gap in the positive diagnosis.

  • The analysis adopts both standard and non-conventional approaches, into genetic regions that may explain the phenotype. A case specific approach is adopted based on the phenotype and the reference population instead of a standard pipeline approach.

  • We query the latest information in the clinical and research field, focus on complex mutations, CNVs, rearrangements, expansions and critically examine the high complexity regions in the genome.

  • Our billing is solely positive outcome-based, hence solution oriented. This allows us to think more from a solution-to-a-patient perspective than from technology perspective.

  • We never stop reviewing unsolved cases with respect to new insights in the field searching for new answers.

  • We reach out to you with an answer, and not wait for you to come to us. Our outcome based invoicing ensures that our success is linked to yours. No request is closed unless we have found the underlying genetic cause behind the phenotype.