Malachi Griffith, Ph.D.

Assistant Professor
Internal Medicine

Molecular Genetics and Genomics Program
Human and Statistical Genetics Program
Computational and Systems Biology Program

  • 314-286-1274

  • 8501

  • The Genome Institute




  • genomics, bioinformatics, data mining, and cancer research

  • Improving our understanding of human disease biology and the development of personalized medicine strategies using genomics and informatics technologies

Research Abstract:

I currently co-lead a bioinformatics lab with my identical twin brother Obi Griffith. Our lab`s research is focused on improving our understanding of cancer biology and the development of personalized medicine strategies using genomics and informatics technologies. We develop bioinformatics and statistical methods for the analysis of high throughput sequence data and identification of biomarkers for diagnostic, prognostic and drug response prediction. In collaboration with our Genomics Tumor Board, we are currently leading analyses of sequence data from the genomes and transcriptomes of patients whose conditions are not well addressed by standard-of-care options. We are also leading the analysis of several large-scale genomics projects to help discover genomic signatures relevant to disease initiation, progression and treatment response. In addition to being an assistant professor of the Department of Medicine, I am an Assistant Director of the McDonnell Genome Institute where our lab is physically located. Finally, I am an instructor for several Bioinformatics workshops delivered annually in various locations including Cold Spring Harbor Laboratories (New York), the Ontario Institute for Cancer Research (Toronto), the University of Edinburgh (Scotland), and Berlin (Germany).

The GriffithLab ( is an interdisciplinary team of biologists, bioinformaticians, computer scientists, and software engineers. Each member of the lab is trained to use computational biology approaches to address research questions relating to cancer biology and precision cancer medicine. We train students and post-docs with a biology background that would like to develop bioinformatics skills. We are equally interested in trainees with a computer science background that would like to apply these skills to studying cancer and improving patient outcomes.

In addition to many ongoing large scale cancer genome/transcriptome data analysis projects, clinical trial data analyses, and Genomics Tumor Board case studies, the Griffith Lab actively develops methods, algorithms and tools to help others perform these analyses. We have made substantial contributions to open source and open access resources for the scientific community including creation of platforms for alternative expression analysis (, regulatory region annotation (, mining drug-gene interactions (, curation of functional mutations (, the clinical interpretation of variants in cancer ( the design of personalized cancer vaccines (, integration of whole genome and RNA-seq data in a regulatory and splicing context (, and GenVisR for genomic data visualization (

We have published over 100 papers with major areas of focus in precision medicine, cancer, genomics, immunogenomics, biomarker discovery, sequence analysis, gene regulation and alternative RNA splicing.

To learn more about past and ongoing projects in the Griffith Lab you can browse the following:

Selected Publications:

Griffith M*Ϯ, Spies NC*, Krysiak K*, McMichael JF, Coffman AC, Danos AM, Ainscough BJ, Ramirez CA, Rieke DT, Kujan L, Barnell EK, Wagner AH, Skidmore ZL, Wollam A, Liu CJ, Jones MR, Bilski RL, Lesurf R, Feng YY, Shah NM, Bonakdar M, Trani L, Matlock M, Ramu A, Campbell KM, Spies GC, Graubert AP, Gangavarapu K, Eldred JM, Larson DE, Walker JR, Good BM, Wu C, Su AI, Dienstmann R, Margolin AA, Tamborero D, Lopez-Bigas N, Jones SJ, Bose R, Spencer DH, Wartman LD, Wilson RK, Mardis ER, Griffith OLϮ. CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat Genet. 2017 Jan 31;49(2):170-174.

Krysiak K, Gomez F, White BS, Matlock M, Miller CA, Trani L, Fronick CC, Fulton RS, Kreisel F, Cashen AF, Carson KR, Berrien-Elliott MM, Bartlett NL, Griffith M, Griffith OL, Fehniger TA. Recurrent somatic mutations affecting B-cell receptor signaling pathway genes in follicular lymphoma. Blood. 2017 Jan 26;129(4):473-483.

Skidmore ZL, Wagner AH, Lesurf R, Campbell KM, Kunisaki J, Griffith OLϮ, Griffith MϮ. GenVisR: Genomic Visualizations in R. Bioinformatics. 2016 Oct 1;32(19):3012-4.

Ainscough BJ, Griffith MϮ, Coffman AC, Wagner AH, Kunisaki J, Choudhary MN, McMichael JF, Fulton RS, Wilson RK, Griffith OLϮ, Mardis ER. DoCM: a database of curated mutations in cancer. Nat Methods. 2016 Sep 29;13(10):806-7.

Griffith M*Ϯ, Griffith OL*, Krysiak K, Skidmore ZL, Christopher MJ, Klco JM, Ramu A, Lamprecht TL, Wagner AH, Campbell KM, Lesurf R, Hundal J, Zhang J, Spies NC, Ainscough BJ, Larson DE, Heath SE, Fronick C, O`Laughlin S, Fulton RS, Magrini V, McGrath S, Smith SM, Miller CA, Maher CA, Payton JE, Walker JR, Eldred JM, Walter MJ, Link DC, Graubert TA, Westervelt P, Kulkarni S, DiPersio JF, Mardis ER, Wilson RK, Ley TJϮ. Comprehensive genomic analysis reveals FLT3 activation and a therapeutic strategy for a patient with relapsed adult B-lymphoblastic leukemia. Exp Hematol. 2016 Jul;44(7):603-13.

Krysiak K, Christopher MJ, Skidmore ZL, Demeter RT, Magrini V, Kunisaki J, O`Laughlin M, Duncavage EJ, Miller CA, Ozenberger BA, Griffith M, Wartman LD, and Griffith OL. A genomic analysis of Philadelphia chromosome-negative AML arising in patients with CML. Blood Cancer J. 2016 Apr 8;6:e413.

Griffith OL*, Griffith M*, Krysiak K*, Magrini V, Ramu A, Skidmore ZL, Kunisaki J, Austin R, McGrath S, Zhang J, Demeter R, Graves T, Eldred JM, Walker J, Larson DE, Maher CA, Lin Y, Chapman W, Mahadevan A, Miksad R, Nasser I, Hanto DW, Mardis ER. A genomic case study of mixed fibrolamellar hepatocellular carcinoma. Ann Oncol. 2016 Jun;27(6):1148-54.

Hundal J, Carreno BM, Petti AA, Linette GP, Griffith OL, Mardis ER, Griffith M. pVAC-Seq: A genome-guided in silico approach to identifying tumor neoantigens. Genome Med. 2016 Jan 29;8(1):11. doi: 10.1186/s13073-016-0264-5.

Wagner AH, Coffman AC, Ainscough BJ, Spies NC, Skidmore ZL, Campbell KM, Krysiak K, Pan D, McMichael JF, Eldred JM, Walker JR, Wilson RK, Mardis ER, Griffith MϮ, Griffith OLϮ. DGIdb 2.0: mining clinically relevant drug-gene interactions. Nucleic Acids Res. 2016 Jan 4;44(D1):D1036-44.

Griffith MϮ, Walker JR, Spies NC, Ainscough BJ, Griffith OLϮ. Informatics for RNA Sequencing: A Web Resource for Analysis on the Cloud. PLoS Comput Biol. 2015 Aug 6;11(8):e1004393.

Last Updated: 8/17/2017 10:55:08 AM

My lab works to overcome the data analysis and interpretation bottleneck for clinical translation of genomic observations.
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