Hello everyone.
I am a bioinformatician and researcher in the field of molecular genetics. My background related to work in a clinical genetics laboratory specialized in rare diseases where I worked over the software diagnostic tools helping for medical geneticists. I have been worked there over tasks of genetic diagnostic and NGS data analysis with the application of a broad number of data science/ML methods.

Several months ago I start a community research project that is completely independent from any laboratory. Research aims to make significant steps in solving of problems lie under the hood of clinical genetic diagnostic:

1. Widely used in labs today, NGS methods (Whole Exome/Genome sequencing, Panels) still do not detect a great number of DNA variants that truly existing in patients samples. Especially it relates to indels of equal or more than 20 bp of length, CNV (copy number variants) of sizes less than 1000 bp. CNV more than 1000 bp also has problems;
2. Quality of NGS tests varied between patients - depends on particular sequencing data, varies between laboratories - depends on bioinformatics data processing that each lab implement. Depends on the pace of implementing of all vast amount of new data processing methods emerging in the field every day;
3. On top of the problems mentioned above - the absence of sufficient control over the quality of tests from the side of doctors and patients before selecting of laboratory and after test was conducted. Information published by laboratories about the quality of detection in NGS clinical genetic tests is most often non-detailed, incomplete, limited in access, or sometimes completely absent leading to lack of control or misinterpretation by test users.

    
Preliminary result of research:

As preliminary results, we collect data about 5162 genetic tests from 14 clinical labs from Europe and present it in one place where anybody can compare tests/labs by basic quality parameters. In the future, we plan to expand/elaborate further on our quality parameter list and data ammount.

https://medavar.online/main/index

Details about basic quality parameters of clinical NGS genetic tests and usage of these parameters for selection of lab/test to increase the probability of receiving proper diagnosis explained on https://medavar.online

Further goals of community research:

1. Conduct research to estimate the quality of the data processing step(bioinformatic pipeline) that lies inside a clinical genetic tests. This will provide for every participant a clear understanding of ineffective parts of data processing that was provided for them by laboratories.
2. Conduct bioinformatic reprocessing of patients sequencing data to detect DNA variants that were not detected under their previous tests. New findings can lead to receiving a proper diagnosis for participants.

    
Who can take place in research?

1. Undiagnosed people. Also diagnosed people for independent check/confirmation of current genetic findings.
2. Any rare disease group
3. Those who previously pass through clinical genetic testing(WGS - Whole Genome Sequencing, WES - Whole Exome Sequencing, Genes Panels Tests, i.e. sets of genes)
4. Any country.
5. Participation is free.

    
What is needed from participants?

Every participant needs to get his/her own NGS sequencing data from the laboratory in which he/she conducted a clinical genetic test. Data in the form of FASTQ and/or BAM and/or VCF files. I can help with gathering your data from laboratories by communicating with them.

Please contact me first, I will describe all the necessary details about data requirements.

All data will be processed anonymously and privately with 100% patient ownership, every participant will receive individual results in the form of written reports and all necessary explanations. I will help to answer your questions.

Participation is free.

What end result will be?

1. Report for each patient with detailed explanations about what was done not good enough during data processing inside genetic test and whats need to be done to detect all genetic variants and reduce errors of genetic test. These reports then can be used as the basis for communication/requirements for previous or other laboratories to improve diagnostic.

2. List of newly found mutations that can be further analyzed by any independent laboratory to:

• interpret by influence on symptoms,
• confirm by commonly used methods - Sanger/microarray/PCR/other.
• increase the probability of receiving the proper diagnosis
• confirm current diagnosis independently (if you already have some) with new findings and/or same as previous findings
• lead to proper treatment and/or drug development

Site of project: https://medavar.online
Please feel free to contact me and I will answer all additional questions.

medavar.research@gmail.com

FB Messenger: m.me/Medavar
Whatsapp: https://wa.me/79960015800

Kind regards,
Kirill Terentev