This group is a host for research into the use of high performance computing (HPC) for primary genomics analyses, such as alignment, variant calling, genome assembly, and RNASeq. By its nature, this research is highly collaborative. Every member of our team is affiliated with multiple departments or campus initiatives. The student participants in this group serve as a bond between the campus faculty using computational genomics analyses in their research, and the NCSA experts in HPC, storage, networking, databases, etc. Together we enable the use of advanced computing infrastructure in computational genomics. Explore this page to find out who is involved, how we are connected, and what projects are currently ongoing.
Senior Research Scientist, National Center for Supercomputing Applications
Research Assistant Professor, Institute of Genomic Biology
217-300-0568
Current Projects | ||
B.S. Molecular and Cellular Biology (2016) M.S. Bioinformatics (2018) Department of Crop Sciences, UIUC CompGen fellow advised by Dr. Matthew Hudson | Mutation profiles of cancerMr. Weber is developing machine learning methods to effectively stratify cancers http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0167047 | |
B.S. Crop Science (2016) Plant Biotechnology, Molecular Biology M.S. Bioinformatics (2018) Department of Crop Sciences, UIUC Graduate Fellow in the College of ACES advised by Dr. Matthew Hudson | Genomic variant calling by assemblyMr. K is focusing on a method to detect genomic variants by assembly. He is employing the software Cortex-var, which constructs de-novo genome assembly on multiple | |
Jennie Zermeno B.S. Integrative Biology (2017) | Benchmarking performance and accuracy of genomic variant calling softwareJennie and Tiffany collaborate to document our efforts in benchmarking variant calling on HPC systems. We have run variant calling experiments on 500 genomes in parallel, on Blue Waters, We have also tested a number of alternative software, such as Isaac, Genalice, Sentieon, Tiffany is documenting the pros and cons of each of these excellent approaches in a separate manuscript. Bioinformatics in the CloudJennie is investigating the issues of portability, reproducibility and scaling of bioinformatics workflows Validation and benchmarking on ParFu - a parallel file packaging utilityTiffany is also involved in testing and benchmarking of ParFu, | |
Tiffany Li B.S. Integrative Biology (2018) minor in Computer Science | ||
B.S. Biochemistry (2014) M.S. Bioinformatics (2016) Bioinformatics specialist and research programmer at NCSA | NCSA IndustryJacob and Ryan collaborate to support the biomedical partners in NCSA Industry program. They provide a complementary mix of expertise in computing (Ryan) and bioinformatics data analysis (Jacob) | |
Ryan Chui B.S. Biochemistry (2016) M.S. Bioinformatics (2017) | ||
Aishwarya Raj B.S. Biochemistry (2019) minor in Bioinformatics | Evolution of molecular networks and persistence of organismsConstruct and compare gene, metabolic and signaling networks from organisms across the tree of life. The goal of the project is to provide support for the general framework of persistence strategies. It postulates that persistence is achieved by biological systems via a tradeoff of traits that serve either | |
Ellen Nie B.S. Computer Science (2018) | Big data network transfers for genomicsEllen is benchmarking the network transfers of genomic data across multiple sites. Validation of Sentieon - the fast alternative to GATKEllen is also collaborating with OICR to validate the speed and accuracy of the new software Convert Java-based GWAS code for SparkIn a project described below (Accurate and scalable GWAS algorithms) we are improving performance of We would like to deploy this Java code on Spark, to see if the necessary performance gains could be obtained. A successful student applicant will use Java Spark API to adapt the current code for a Spark platform that |
Former Group Members | ||
Angela Chen M.S. Statistics (2017) Department of Statistics, UIUC CompGen fellow advised by Dr. Alexander Lipka | Accurate and scalable GWAS algorithmsAngela and Khory collaborated to improve the scalability and parallelization of the statistical software Angela wrote a manuscript to demonstrate that her new stepwise epistatic model selection Khory provided the expertise in computer science to convert this Java code into C++ and parallelize | |
Khory Wagner advised by Dr. Vologymyr Kindratenko | ||
Nainika Roy B.S. Molecular and Cellular Biology (2017) minor in Informatics and Chemistry SPIN fellow | Data formats and data structures in computational genomics | |
Junyu Li B.S. Molecular and Cellular Biology (2017) minor in Computer Science SPIN fellow | Genomic variant calling by assemblyJunyu worked with Mr. K in an interdisciplinary team, providing the expertise in math and computer | |
Noah Flynn B.S. Bioengineering, Mathematics (2017) minor in computer science SPIN fellow | Evolution of molecular networks and persistence of organisms |
Dr. Matthew Hudson Bioinformatics Crop Science | HPCBio, Carver Biotechnology Center | |
Computer Science | NCSA Scientific Software and ApplicationsPortable variant calling workflow in Swift | |
Azza Ahmed Computer Science advised by Dr. Faisal Fadlelmola | ||
H3Africa Consortium
| ||
Morgan Taschuk Bioinformatics | OICR
| |
Paul Hatton
| University of Birmingham |
They are employing the software Cortex-var, which constructs de-novo genome assembly on multiple sequencing samples, and then compares the resultant de Bruijn graphs to detect where they diverge, indicating a potential variant. This could be a good method for detecting novel variants, especially repeats and complex rearrangements in complex genomes, such as polyploid plants and cancer. Junyu and Mr. K work as an interdisciplinary team. Junyu provides the expertise in math and computer science to automate the Cortex-var workflow and interpret the algorithm. Mr. K is using his strong background in genomics to interpret, clean-up and validate the output.
This group is a host for research into the use of high performance computing (HPC) for primary genomics analyses, such as alignment, variant calling, genome assembly, and RNASeq. By its nature, this research is highly collaborative. Every member of our team is affiliated with multiple departments or campus initiatives. The student participants in this group serve as a bond between the campus faculty using computational genomics analyses in their research, and the NCSA experts in HPC, storage, networking, databases, etc. Together we enable the use of advanced computing infrastructure in computational genomics. Explore this page to find out who is involved, how we are connected, and what projects are currently ongoing.
Senior Research Scientist, National Center for Supercomputing Applications
Research Assistant Professor, Institute of Genomic Biology
217-300-0568
Current Projects | ||
B.S. Molecular and Cellular Biology (2016) M.S. Bioinformatics (2018) Department of Crop Sciences, UIUC CompGen fellow advised by Dr. Matthew Hudson | Mutation profiles of cancerMr. Weber is developing machine learning methods to effectively stratify cancers http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0167047 | |
B.S. Crop Science (2016) Plant Biotechnology, Molecular Biology M.S. Bioinformatics (2018) Department of Crop Sciences, UIUC Graduate Fellow in the College of ACES advised by Dr. Matthew Hudson | Genomic variant calling by assemblyMr. K is focusing on a method to detect genomic variants by assembly. He is employing the software Cortex-var, which constructs de-novo genome assembly on multiple sequencing samples, and then compares the resultant de Bruijn graphs to detect where they diverge, indicating a potential variant. This could be a good method for detecting novel variants, especially repeats and complex rearrangements in complex genomes, such as polyploid plants and cancer. Mr. K is using his strong background in genomics to interpret, clean-up and validate the output. | |
Jennie Zermeno B.S. Integrative Biology (2017) | Benchmarking performance and accuracy of genomic variant calling softwareJennie and Tiffany collaborate to document our efforts in benchmarking variant calling on HPC systems. We have run variant calling experiments on 500 genomes in parallel, on Blue Waters, We have also tested a number of alternative software, such as Isaac, Genalice, Sentieon, Tiffany is documenting the pros and cons of each of these excellent approaches in a separate manuscript. Bioinformatics in the CloudJennie is investigating the issues of portability, reproducibility and scaling of bioinformatics workflows Validation and benchmarking on ParFu - a parallel file packaging utilityTiffany is also involved in testing and benchmarking of ParFu, | |
Tiffany Li B.S. Integrative Biology (2018) minor in Computer Science | ||
B.S. Biochemistry (2014) M.S. Bioinformatics (2016) Bioinformatics specialist and research programmer at NCSA | NCSA IndustryJacob and Ryan collaborate to support the biomedical partners in NCSA Industry program. They provide a complementary mix of expertise in computing (Ryan) and bioinformatics data analysis (Jacob) | |
Ryan Chui B.S. Biochemistry (2016) M.S. Bioinformatics (2017) | ||
Aishwarya Raj B.S. Biochemistry (2019) minor in Bioinformatics | Evolution of molecular networks and persistence of organismsConstruct and compare gene, metabolic and signaling networks from organisms across the tree of life. The goal of the project is to provide support for the general framework of persistence strategies. It postulates that persistence is achieved by biological systems via a tradeoff of traits that serve either | |
Ellen Nie B.S. Computer Science (2018) | Big data network transfers for genomicsEllen is benchmarking the network transfers of genomic data across multiple sites. Validation of Sentieon - the fast alternative to GATKEllen is also collaborating with OICR to validate the speed and accuracy of the new software Convert Java-based GWAS code for SparkIn a project described below (Accurate and scalable GWAS algorithms) we are improving performance of We would like to deploy this Java code on Spark, to see if the necessary performance gains could be obtained. A successful student applicant will use Java Spark API to adapt the current code for a Spark platform that |
Former Group Members | ||
Angela Chen M.S. Statistics (2017) Department of Statistics, UIUC CompGen fellow advised by Dr. Alexander Lipka | Accurate and scalable GWAS algorithmsAngela and Khory are collaborating to improve the scalability and parallelization Angela is writing a manuscript to demonstrate that her new stepwise epistatic model selection procedure Khory is providing the expertise in computer science to convert this Java code | |
Khory Wagner advised by Dr. Vologymyr Kindratenko | ||
Nainika Roy B.S. Molecular and Cellular Biology (2017) minor in Informatics and Chemistry SPIN fellow | Data formats and data structures in computational genomics | |
Junyu Li B.S. Molecular and Cellular Biology (2017) minor in Computer Science SPIN fellow | Genomic variant calling by assemblyJunyu worked with Mr. K in an interdisciplinary team, providing the expertise in math and computer science to automate the Cortex-var workflow and interpret the algorithm. | |
Noah Flynn B.S. Bioengineering, Mathematics (2017) minor in computer science SPIN fellow | Evolution of molecular networks and persistence of organisms |
Dr. Matthew Hudson Bioinformatics Crop Science | HPCBio, Carver Biotechnology Center | |
Computer Science | NCSA Scientific Software and ApplicationsPortable variant calling workflow in Swift | |
Azza Ahmed Computer Science advised by Dr. Faisal Fadlelmola | ||
H3Africa Consortium
| ||
Morgan Taschuk Bioinformatics | OICR
| |
Paul Hatton
| University of Birmingham |
They are employing the software Cortex-var, which constructs de-novo genome assembly on multiple sequencing samples, and then compares the resultant de Bruijn graphs to detect where they diverge, indicating a potential variant. This could be a good method for detecting novel variants, especially repeats and complex rearrangements in complex genomes, such as polyploid plants and cancer. Junyu and Mr. K work as an interdisciplinary team. Junyu provides the expertise in math and computer science to automate the Cortex-var workflow and interpret the algorithm. Mr. K is using his strong background in genomics to interpret, clean-up and validate the output.