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Cole Trapnell

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For the American television producer, see Coles Trapnell.
Cole Trapnell
Cole Trapnell
Cole Trapnell at the Intelligent Systems for Molecular Biology (ISMB) conference in 2018
Born
Bruce Colston Trapnell Jr.

1982 (age 42–43)[3]
Alma materUniversity of Maryland, College Park (BS, PhD)
Known for
AwardsOverton Prize (2018)
Scientific career
FieldsTranscriptomics
Cell differentiation
Non-coding RNA[1]
InstitutionsUniversity of Washington
Harvard University[2]
ThesisTranscript assembly and abundance estimation with high-throughput RNA sequencing (2010)
Doctoral advisorSteven Salzberg
Lior Pachter
Websitewww.gs.washington.edu/faculty/trapnell.htm

Bruce Colston Trapnell Jr. (born 1982)[3] is an assistant professor in the Department of Genome Sciences at the University of Washington.[1] He is known for developing influential open-source software tools for transcriptomics, particularly for RNA-Seq and single-cell RNA-Seq data analysis. His work has been central to the fields of gene expression analysis and cellular differentiation. He was awarded the Overton Prize by the International Society for Computational Biology (ISCB) for “outstanding accomplishment in the early to mid stage of his career” in 2018.[2]

Education and career

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Trapnell received dual B.S. degrees in Computer Science and Mathematics from the University of Maryland, College Park in 2005. He continued at Maryland for his doctoral studies, earning a Ph.D. in Computer Science in 2010. During his graduate work, he was jointly advised by Steven Salzberg at the University of Maryland and Lior Pachter at the University of California, Berkeley.[5][2]

Following his Ph.D., Trapnell was a postdoctoral fellow in John Rinn's lab at Harvard University in the Department of Stem Cell and Regenerative Biology. During this time, he augmented his computational work with experimental biology training.[5] In 2014, he joined the faculty at the University of Washington's Department of Genome Sciences.[6] He is also a scientific co-director of the Seattle Hub for Synthetic Biology and an investigator at the Allen Discovery Center for Cell Lineage Tracing.[7]

Research and contributions

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Trapnell's research focuses on developing computational and genomic technologies to study how cells make fate decisions during development and disease. His lab combines experimental and computational approaches to dissect gene regulatory networks.[5]

RNA-Seq analysis tools

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During his graduate studies, Trapnell developed several foundational tools for analyzing RNA-Seq data. He was the principal author of TopHat, a program for aligning RNA-Seq reads to a genome to identify splice junctions,[8] and Cufflinks, which assembles and quantifies gene and transcript abundances from aligned reads.[9]

As a postdoctoral fellow and later in his own lab, Trapnell pioneered the concept of pseudotemporal ordering, or "pseudotime," a method for ordering single cells along a developmental trajectory based on their gene expression profiles.[10] This approach allows researchers to study dynamic biological processes, like cell differentiation, from a static snapshot of single-cell data.[11] His lab developed the software package Monocle to implement these trajectory inference analyses.[12]

References

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  1. ^ a b Cole Trapnell publications indexed by Google Scholar Edit this at Wikidata
  2. ^ a b c Fogg, Christiana N.; Kovats, Diane E.; Shamir, Ron (2018). "2018 ISCB Overton Prize awarded to Cole Trapnell". PLOS Computational Biology. 14 (6): e1006163. Bibcode:2018PLSCB..14E6163F. doi:10.1371/journal.pcbi.1006163. ISSN 1553-7358. PMC 5991640. PMID 29879112.
  3. ^ a b Trapnell, Bruce C. (Bruce Colston), 1982 at Library of Congress
  4. ^ Langmead, Ben; Cole Trapnell; Mihai Pop; Steven L Salzberg (2009). "Ultrafast and memory-efficient alignment of short DNA sequences to the human genome". Genome Biology. 10 (3): 10:R25. doi:10.1186/gb-2009-10-3-r25. PMC 2690996. PMID 19261174.
  5. ^ a b c "Cole Trapnell". Department of Genome Sciences. University of Washington. Retrieved 15 July 2024.
  6. ^ "Cole Trapnell". Allen Institute. Retrieved 15 July 2024.
  7. ^ "Q&A with Dr. Cole Trapnell on the Seattle Hub for Synthetic Biology". Brotman Baty Institute. 30 January 2024. Retrieved 15 July 2024.
  8. ^ Trapnell, Cole; Pachter, Lior; Salzberg, Steven L. (1 May 2009). "TopHat: discovering splice junctions with RNA-Seq". Bioinformatics. 25 (9): 1105–1111. doi:10.1093/bioinformatics/btp120. PMC 2672628. PMID 19289445.
  9. ^ Trapnell, Cole; Roberts, Adam; Goff, Loyal; Pertea, Geo; Kim, Daehwan; Kelley, David R; Pimentel, Harold; Salzberg, Steven L; Rinn, John L; Pachter, Lior (2012). "Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks". Nature Protocols. 7 (3). Springer Science and Business Media LLC: 562–578. doi:10.1038/nprot.2012.016. ISSN 1754-2189. PMC 3334321. Retrieved July 15, 2025.
  10. ^ Trapnell, Cole; Cacchiarelli, Davide; Grimsby, Jonna; Pokharel, Prapti; Li, Shuqiang; Morse, Michael; Lennon, Niall J; Livak, Kenneth J; Mikkelsen, Tarjei S; Rinn, John L (March 23, 2014). "The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells". Nature Biotechnology. 32 (4). Springer Science and Business Media LLC: 381–386. doi:10.1038/nbt.2859. ISSN 1087-0156. PMC 4122333. Retrieved July 15, 2025.
  11. ^ Trapnell, Cole (2015). "Defining cell types and states with single-cell genomics" (PDF). Genome Research. 25 (10). Cold Spring Harbor Laboratory: 1491–1498. doi:10.1101/gr.190595.115. ISSN 1088-9051. Retrieved July 15, 2025.
  12. ^ Flynn, Emily; Almonte-Loya, Ana; Fragiadakis, Gabriela K. (2023-08-10). "Single-Cell Multiomics". Annual Review of Biomedical Data Science.
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