Need GATK experts to help with GATK-as-a-service? Hire Experfy freelance GATK experts capable of leveraging the GATK best practices that provide step-by-step recommendations for performing variant discovery analysis in high-throughput sequencing (HTS) data. They are very well aware of key principles of the processing and analysis steps required to go from raw reads coming off the sequencing machine, all the way to an appropriately filtered variant callset that can be used in downstream analyses. Our GATK experts can tailor different best practices workflows to particular applications depending on the type of variation of interest and the technology employed. Further, they can work on cutting-edge analysis methods and software, real big data and a mission that matters.
Hire Experfy vetted freelance GATK experts capable of applying their knowledge and skills in biostatistics and genomics to analyze genome-wide genetic variation and RNA-seq as well as organize these large datasets and assist in the set-up of analytic pipelines for statistical analyses, production of graphs and tables as well as bioinformatics annotation.
Investigator at Lieber Institute for Brain Development
US | Baltimore, MD
My greatest strength is leveraging data analytics to find concrete solutions for problems that individuals or companies want to solve. I often serve as the interface between data generators and higher-level management, which has created a useful combination of technical knowledge and skills with bigger picture thinking towards the future. I received my PhD in Epidemiology with a concentration in Human Genetics and a concurent Masters of Health Sciences in Bioinformatics from Johns Hopkins University in 2011. I am currently the lead Biostatistician at a non-profit research institute in Baltimore, overseeing a small team and collaborating with diverse research groups throughout the institute. My specialities include:
- the design, analysis, and interpretation of large-scale genomic studies relating to human health and disease
- analyzing clinical population-level data by linking multiple sources of data
My research and professional experience is most relevant to pharmaceutical and health care industries, but may also be relevant to insurance and financial industries.
US | Princeton, NJ
1) Experienced with statistical modeling/analysis in the context of large scale and complex problems
2) Comprehensive practical and theoretical knowledge of machine learning techniques
3) Strong algorithmic skills and hands-on software development experience
4) Proficiency with R, Java, C/C++, Perl, SQL, Shell, Python, Unix/Linux, AWS
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