Crawford Lab

Key: * co-first authors; † co-senior authors; # corresponding author(s); lab members

Preprint(s):

A. DenAdel, M.L. Ramseier, A. Navia, A.K. Shalek, S. Raghavan, P.S. Winter, A.P. Amini, and L. Crawford#. A knockoff calibration method to avoid over-clustering in single-cell RNA-sequencing. bioRxiv. 2024.03.08.584180. [Preprint] [Software] [Documentation]
C. Nwizu, M. Hughes, M.L. Ramseier, A. Navia, A.K. Shalek, N. Fusi, S. Raghavan†, P.S. Winter†, A.P. Amini†#, and L. Crawford†#. Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data. bioRxiv. 2024.02.11.579839. [Preprint] [Software] [Documentation]
E.T. Winn-Nuñez#, H. Witt, D. Bhaskar, R.Y. Huang, J.S. Reichner, I.Y. Wong, and L. Crawford#. Generative modeling of biological shapes and images using a probabilistic α-shape sampler. bioRxiv. 2024.01.09.574919. [Preprint] [Software]
K.Z. Kedzierska#, L. Crawford†, A.P. Amini†, and A.X. Lu†#. Assessing the limits of zero-shot foundation models in single-cell biology. bioRxiv. 2023.10.16.561085. [Preprint] [Software]
H. Xie, L. Crawford#, and A. Conard#. Multioviz: an interactive platform for in silico perturbation and interrogation of gene regulatory networks. bioRxiv. 2023.10.10.561790. [Preprint] [Software] [Online Tool]
K. Meng#, M. Ji, J. Wang, K. Ding, H. Kirveslahti, A. Eloyan, and L. Crawford. Statistical inference on grayscale images via the Euler-Radon transform. arXiv. 2308.14249. [Preprint] [Software]
S.P. Smith*, G. Darnell*, D. Udwin, A. Harpak, S. Ramachandran†, and L. Crawford†#. Accounting for statistical non-additive interactions enables the recovery of missing heritability from GWAS summary statistics. bioRxiv. 2022.07.21.501001. [Preprint] [Software]
K. Meng#, J. Wang, L. Crawford, and A. Eloyan. Randomness and statistical inference of shapes via the smooth Euler characteristic transform. arXiv. 2204.12699. [Preprint] [Software]
M.C. Turchin#, G. Darnell, L. Crawford#, and S. Ramachandran#. Pathway analysis within multiple human ancestries reveals novel signals for epistasis in complex traits. bioRxiv. 2020.09.24.312421. [Preprint] [Software]
K.E. Ware, S. Gupta, J. Eng, G. Kemeny, B.J. Puviindran, W.C. Foo, L. Crawford, R.G. Almquist, D. Runyambo, B.C. Thomas, M.U. Sheth, A. Agarwal, M. Pierobon, E.F. Petricoin, D.L. Corcoran, J. Freedman, S.R. Patierno, T. Zhang, S. Gregory, Z. Sychev, J.M. Drake, A.J. Armstrong#, and J.A. Somarelli#. Convergent evolution of p38/MAPK activation in hormone resistant prostate cancer mediates pro-survival, immune evasive, and metastatic phenotypes. bioRxiv. 2020.04.22.050385. [Preprint]
J. Ish-Horowicz*, D. Udwin*, K. Scharfstein, S.R. Flaxman, L. Crawford#, and S.L. Filippi#. Interpreting deep neural networks through variable importance. arXiv. 1901.09839. [Preprint] [Software]
L. Crawford# and X. Zhou#. Genome-wide marginal epistatic association mapping in case-control studies. bioRxiv. 374983. [Preprint] [SI] [Software]

2024:

E.T. Winn-Nuñez#, M. Griffin, and L. Crawford# (2024). A simple approach for local and global variable importance in nonlinear regression models. Computational Statistics & Data Analysis. 194: 107914. [PDF] [Link] [SI] [Software]

2023:

H. Adam#, F. Yin, M. Hu, N. Tenenholtz, L. Crawford, L. Mackey, and A. Koenecke (2023). Should I stop or should I go: early stopping with heterogeneous populations. Advances in Neural Processing Systems (NeurIPS). (Spotlight Paper) [Preprint] [Software]
J. Stamp#, A. DenAdel, D. Weinreich, and L. Crawford# (2023). Leveraging the genetic correlation between traits improves the detection of epistasis in genome-wide association studies. G3: Genes, Genomes, Genetics. 13(8): jkad118. [PDF] [Software] [Documentation]
C. Rios-Martinez, N. Bhattacharya, A.P. Amini, L. Crawford, and K.K. Yang# (2023). Deep self-supervised learning for biosynthetic gene cluster detection and product classification. PLOS Computational Biology. 19(5): e1011162. [PDF] [Software]
A. Conard, A. DenAdel, and L. Crawford# (2023). A spectrum of explainable and interpretable machine learning approaches for genomic studies. WIREs Computational Statistics. 15(5): e1617. [PDF] [Link]

2022:

B. Trippe#, B. Huang, E.A. DeBenedictis, B. Coventry, N. Bhattacharya, K.K. Yang, D. Baker, and L. Crawford# (2022). Randomized gates eliminate bias in sort-seq assays. Protein Science. 31(9): e4401. [PDF] [Link]
W. Cheng#, S. Ramachandran, and L. Crawford# (2022). Uncertainty quantification in variable selection for genetic fine-mapping using Bayesian neural networks. iScience. 25(7): 104553. (Spotlight Talk at the 10th RECOMB Satellite on Computational Methods in Genetics) [PDF] [SI] [Software]
W.S. Tang*, G.M. da Silva*, H. Kirveslahti, E. Skeens, B. Feng, T. Sudijono, K.K. Yang, S. Mukherjee, B. Rubenstein†, and L. Crawford†# (2022). A topological data analytic approach for discovering biophysical signatures in protein dynamics. PLOS Computational Biology. 18(5): e1010045. [PDF] [SI] [Software]
S.P. Smith, S. Shahamatdar, W. Cheng, S. Zhang, J. Paik, M. Graff, C. Haiman, T.C. Matise, K.E. North, U. Peters, E. Kenny, C. Gignoux, G. Wojcik, L. Crawford†, and S. Ramachandran†# (2022). Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries. American Journal of Human Genetics. 109: 871-884. [PDF] [Software]

2021:

S. Raghavan*, P.S. Winter*#, A.W. Navia*, H.L. Williams*, A. DenAdel, R.L. Kalekar, J. Galvez-Reyes, K.E. Lowder, J. Galvez-Reyes, R.L. Kalekar, N. Mulugeta, K.S. Kapner, M.S. Raghavan, A.A. Borah, N. Liu, S.A. Väyrynen, A. Dias Costa, R.W.S. Ng, J. Wang, E.K. Hill, D.Y. Ragon, L.K. Brais, A.M. Jaeger, L.F. Spurr, Y.Y. Li, A.D. Cherniack, M.A. Booker, E.F. Cohen, M.Y. Tolstorukov, I. Wakiro, A. Rotem, B.E. Johnson, J.M. McFarland, E.T. Sicinska, T.E. Jacks, R.J. Sullivan, T.E. Clancy, K. Perez, D.A. Rubinson, K. Ng, J.M. Cleary, L. Crawford, S.R. Manalis, J.A. Nowak, B.R. Wolpin†, W.C. Hahn†, A.J. Aguirre†#, and A.K. Shalek†# (2021). Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer. Cell. 184(25): 6119-6137. [PDF] [Link]
M. Kamariza#, L. Crawford#, D. Jones#, and H.K. Finucane# (2021). Misuse of the term "trans-ethnic" in genomics research. Nature Genetics. 50: 1520-1521. [Link] [Editorial]
P. Demetci*, W. Cheng*, G. Darnell, X. Zhou, S. Ramachandran, and L. Crawford# (2021). Multi-scale inference of genetic architecture using biologically annotated neural networks. PLOS Genetics. 17(8): e1009754. [PDF] [SI] [Software]
D.E. Runcie#, J. Qu, H. Cheng, and L. Crawford (2021). Mega-scale linear mixed models for genomic predictions with thousands of traits. Genome Biology. 22: 213. [PDF] [SI] [Software]
B. Wang*, T. Sudijono*, H. Kirveslahti*, T. Gao, D.M. Boyer, S. Mukherjee†, and L. Crawford†# (2021). A statistical pipeline for identifying physical features that differentiate classes of 3D shapes. Annals of Applied Statistics. 15(2): 638-661. [PDF] [SI] [Software]
A.N. Spierer#, J.A. Mossman, S.P. Smith, L. Crawford, S. Ramachandran, and D.M. Rand# (2021). Natural variation in the regulation of neurodevelopmental genes modifies flight performance in Drosophila. PLOS Genetics. 17(3): e1008887. [PDF] [SI] [Software]
B.A. Borden, Y. Baca, J. Xiu, F. Tavora, I. Winer, B.A. Weinberg, A.M. VanderWalde, S. Darabi, W.M. Korn, A.P. Mazar, F.J. Giles, L. Crawford, H. Safran, W.S. El-Deiry, and B.A. Carneiro# (2021). The landscape of glycogen synthase kinase-3 beta (GSK-3b) genomic alterations in cancer. Molecular Cancer Therapeutics. 20(1): 183-190. [Link]

2020:

L. Crawford#, A. Monod#, A.X. Chen, S. Mukherjee, and R. Rabadán (2020). Predicting clinical outcomes in glioblastoma: an application of topological and functional data analysis. Journal of the American Statistical Association. 115(531): 1139-1150. [PDF] [SI] [Software]
J.S. Sadick, L. Crawford, H.C. Cramer, C. Franck, S.A. Liddelow, and E.M. Darling# (2020). Generating cell type-specific protein signatures from non-symptomatic and diseased tissues. Annals of Biomedical Engineering. 48: 2218-2232. [Link]
W. Cheng, S. Ramachandran#, and L. Crawford# (2020). Estimation of non-null SNP effect size distributions enables the detection of enriched genes underlying complex traits. PLOS Genetics. 16(6): e1008855. [PDF] [SI] [Software]
K.H. Lin*, J.C. Rutter*, A. Xie, E.T. Winn, B. Pardieu, R. Dal Bello, Y.R. Ahn, Z. Dai, R.T. Sobhan, G.R. Anderson, K.R. Singleton, A.E. Decker, P.S. Winter, J.W. Locasale, L. Crawford, A. Puissant#, and K.C. Wood# (2020). Using antagonistic pleiotropy to design a chemotherapy-induced evolutionary trap. Nature Genetics. 52: 408-417. [PDF]

2019:

T. Borgovan#, L. Crawford, C. Nwizu, and P. Quesenberry (2019). Stem cells and extracellular vesicles: biological regulators of physiology and disease. American Journal of Physiology-Cell Physiology. 317(2): C155-C166. [PDF]
L. Crawford#, S.R. Flaxman, D.E. Runcie, and M. West (2019). Variable prioritization in nonlinear black box methods: a genetic association case study. Annals of Applied Statistics. 13(2): 958-989. [PDF] [SI] [Software]
A. Monod#, S. Kališnik Verovšek, J.Á. Patiño-Galindo, and L. Crawford (2019). Tropical sufficient statistics for persistent homology. SIAM Journal on Applied Algebra and Geometry. 3(2): 337-371. [PDF] [Software]
D.E. Runcie# and L. Crawford (2019). Fast and general-purpose linear mixed models for genome-wide genetics. PLOS Genetics. 15(2): e1007978. [PDF] [SI] [Software]

2018:

L. Crawford#, K.C. Wood, X. Zhou#, and S. Mukherjee# (2018). Bayesian approximate kernel regression with variable selection. Journal of the American Statistical Association. 113(524): 1710-1721. [PDF] [SI] [Software]
R. Soderquist, L. Crawford, E. Liu, M. Lu, A. Agarwal, G.R. Anderson, K.H. Lin, P.S. Winter, M. Cakir, and K.C. Wood# (2018). Systematic mapping of BCL-2 gene dependencies in cancer reveals molecular determinants of BH3 mimetic sensitivity. Nature Communications. 9(1): 3513. [PDF]

2017:

K.R. Singleton*, L. Crawford*, E. Tsui, H.E. Manchester, O. Maertens, X. Liu, M.V. Liberti, A.N. Magpusao, E.M. Stein, J.P. Tingley, D.T. Frederick, G.M. Boland, K.T. Flaherty, S.J. McCall, C. Krepler, K. Sproesser, M. Herlyn, D.J. Adams, J.W. Locasale, K. Cichowski, S. Mukherjee, and K.C. Wood (2017). Melanoma therapeutic strategies that select against resistance by exploiting MYC-driven evolutionary convergence. Cell Reports. 21(10): 2796-2812. [PDF] [SI]
L. Crawford#, P. Zeng, S. Mukherjee, and X. Zhou# (2017). Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits. PLOS Genetics. 13(7): e1006869. [PDF] [SI] [Software]
G.R. Anderson*, P.S. Winter*, K.H. Lin, D.P. Nussbaum, M. Cakir, E.M. Stein, R. Soderquist, L. Crawford, J.C. Leeds, R. Newcomb, P. Stepp, C. Yip, S.E. Wardell, J.P. Tingley, M. Ali, M. Xu, M. Ryan, S.J. McCall, A. McRee, C.M. Counter, C.J. Der, and K.C. Wood# (2017). A landscape of therapeutic cooperativity in KRAS mutant cancers reveals principles for controlling tumor evolution. Cell Reports. 20(4): 999-1015. [PDF]

2016:

G.R. Anderson, S.E. Wardell, M. Cakir, L. Crawford, J.C. Leeds, D.P. Nussbaum, P.S. Shankar, R.S. Soderquist, E.M. Stein, J.P. Tingley, P.S. Winter, E.K. Zeiser-Misenheimer, H.M. Alley, A. Yllanes, V. Haney, K.L. Blackwell, S.J. McCall, D.P. McDonnell, and K.C. Wood# (2016). PIK3CA mutations enable selective targeting of a breast tumor lineage survival dependency through MTOR-mediated control of MCL-1 translation. Science Translational Medicine. 8: 369ra175. [PDF]

2014-2015:

L. Crawford, V. Ponomarenko#, J. Steinberg, and M. Williams (2014). Accepted elasticity in local arithmetic congruence monoids. Results in Mathematics. 66:227-245. [Link]