Publications
Preprints
Yang X, Benny P,..., Garmire LX , Placental telomere length shortening is
not associated with preeclampsia but the gestational age. submitted. ArXiv.
Li YJ, Stanojevic S, He B, Jing Z, Huang Q , Kang J, Garmire
LX, Benchmarking Computational Integration Methods for Spatial Transcriptomics Data (preprint)
He B, Garmire , ASGARD: A Single-cell Guided pipeline to Aid Repurposing of
Drugs (preprint)
Shashank Yadav, Shu Zhou, Bing He, Lana X Garmire ,
Single-cell imaging based prognosis prediction identifies new breast cancer survival subtypes (preprint)
Qianhui Huang, Yijun Li, Chuan Xu, Sarah Teichmann, Naftali Kaminski, Matteo Pellegrini, Quan Nguyen, Andrew E. Teschendorff,
Lana X. Garmire,
Challenges and perspectives in computational deconvolution in genomics data (preprint)
2022
88. Badowski C, He B, Garmire LX
: Blood-derived lncRNAs as biomarkers for cancer diagnosis: the Good, the Bad and the Beauty
(link)
87. Li Y, Stanojevic S, Garmire LX
: Emerging artificial intelligence applications in Spatial Transcriptomics analysis
(link)
86. Stefan Stanojevic, Li YJ, Garmire LX
: Computational Methods for Single-Cell Multi-Omics Integration and Alignment. Accepted. Genomics Proteomics and Bioinformatics.
(link)
85. Xu J, Bing He, Carver K, Vanheyningen D, Parkin B, Garmire LX , Olszewski M
, Deng J.
: ScRNA-Seq study of neutrophils reveals vast heterogeneity and inflammatory responses in severe COVID-19 patients.
Frontiers in Immunology. (link)
84. Yile Chen, Bing He, Yu Liu, Max T. Aung, Zaira Rosario-Pabón, Carmen M.
Vélez-Vega, Akram Alshawabkeh, José F. Cordero, John D. Meeker, Garmire LX .
Maternal plasma lipids are involved in the pathogenesis of preterm birth. Gigascience. (link)
83.Chen VL, Huang Q , Harouaka R, Du Y, Lok AS, Parikh ND, Garmire
LX , Wicha MS. A Dual-Filtration System for Single-Cell Sequencing of Circulating Tumor
Cells and Clusters in HCC. (link )
82. Vahed M, , Vahed M, Garmire LX . BML: a versatile web
server for bipartite motif discovery, Briefings in Bioinformatics. (link )
2021
81. Engström K, Mandakh Y, Garmire L , Masoumi Z, Isaxon C, Malmqvist E,
Erlandsson L, Hansson SR. Early Pregnancy Exposure to Ambient Air Pollution among Late-Onset
Preeclamptic Cases Is Associated with Placental DNA Hypomethylation of Specific Genes and
Slower Placental Maturation. Toxics. 2021. 9(12):338.
(link )
80. Weber GM,..., Consortium For Clinical Characterization Of COVID-19 By EHR (4CE), Kohane
IS, Cai T, South AM, Brat GA.
International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6
Countries: Retrospective Cohort Study. J Med Internet Res. 2021.
(link )
79. Le TT, Gutiérrez-Sacristán A, Son J, Hong C, South AM, Beaulieu-Jones BK, Loh NHW, Luo
Y, Morris M, Ngiam KY, Patel LP, Samayamuthu MJ, Schriver E, Tan ALM, Moore J, Cai T, Omenn
GS, Avillach P, Kohane IS; Consortium for Clinical Characterization of COVID-19 by EHR
(4CE), Visweswaran S, Mowery DL, Xia Z.
Multinational characterization of neurological phenotypes in patients hospitalized with
COVID-19. Sci Rep. 2021.
(link )
78. Estiri H, Strasser ZH, Brat GA, Semenov YR; Consortium for Characterization of COVID-19
by EHR (4CE), Patel CJ, Murphy SN. Evolving phenotypes of non-hospitalized patients that
indicate long COVID. BMC Med. 2021
(link )
77. He B , Liu Y, , Maurya MR, Benny P, Lassiter C, Li
H ,
Subraminiam S, Garmire LX . The maternal blood lipidome is indicative of
the pathogenesis of severe preeclampsia. J Lipid Res
. 2021 Sep 18;100118. (link)
76. Garmire D, Zhu X, Mantravadi A, Huang Q, Yunits B, Liu Y, Wolfgruber T, Poirion
O, Zhao T, Arisdakessian C, Stanojevic S, Garmire LX .
GranatumX: A community engaging, modularized and flexible software environment for
single-cell analysis. Proteomics, Genomics and Bioinformatics( link )
75. Piorion O, Chaudhary K, Huang S, Garmire LX , Multi-omics-based
pan-cancer
prognosis prediction using an ensemble of deep-learning and machine-learning models. Genome
Medicine. 2021 ( link )
74. Cherry C, Maestas DR, Han J, ..., Garmire LX , Elisseeff JH,
Intercellular signaling dynamics from a single cell atlas of the biomaterials response.
Nature Biomedical Engineering. 2021
( link )
73. Paula A Benny, Fadhl M. Al-Akwaa , Corbin Dirkx, Ryan J.
Schlueter, Thomas K. Wolfgruber, Ingrid Y. Chern , Suzie Hoops, Dan Knights,
Lana X. Garmire . Placenta microbiome diversity is associated with maternal
pre-pregnancy obesity and placenta biogeography. FASEB. ( link)
72. Zhucheng Zhan, Zheng Jing, Bing He , Noshad Hossenei, Maria Westerhoff,
Eun-Young Choi, Lana Garmire . Two-stage biologically interpretable
neural-network models for liver cancer prognosis prediction using histopathology and
transcriptomic data. Accepted. Nucleic Acid Research: Genomics and Bioinformatics.
(preprint)
71. Alakwaa F, Garmire LX , Savelieff MG. Correction to "Bioinformatics
Analysis of Metabolomics Data Unveils Association of Metabolic Signatures with Methylation
in Breast Cancer". J Proteome Res
.
( link )
70. Wang Di, He Kevin, Garmire LX . Cox-nnet v2.0:
improved
neural-network based survival prediction extended to large-scale EMR dataset.
Bioinformatics.
(link)
69. Fang X, Liu Y, Ren Z, Du Y, Huang Q, Garmire LX. Lilikoi V2.0: a deep
learning-enabled, personalized pathway-based R package for diagnosis and prognosis
predictions using metabolomics data. Gigascience. 10(1):giaa162. doi:
10.1093/gigascience/giaa162.
( link )
68. Garmire LX . Mentorship is not co-authorship: a revisit to mentorship.
Genome Biology. 22(1):2.
( link )
2020
67. Brito JJ, Li J, Moore JH, Greene CS, Nogoy NA, $Garmire LX , $Mangul
S.Corrigendum to:
Recommendations to enhance rigor and reproducibility in biomedical research. Gigascience.
2020.
( link )
66. Li H, Huang SJ, Liu Y, Garmire LX , Single Cell Transcriptome Research
in
Human Placenta, Reproduction. (link)
65. He Bing, Garmire LX . Prediction of repurposed drugs for treating lung
injury in COVID-19. F1000 Research. 9:609 ( link )
64. Huang QH, Liu Y, Du Y, Garmire LX , Evaluation of cell type
deconvolution R
packages on single cell RNA-seq data, accepted, Genomics, Proteomics and Bioinformatics.
(preprint)
63. Brito JJ, Li J, Moore JH, Greene CS, Nogoy NA, $Garmire LX , $Mangul
S.
Recommendations to enhance rigor and reproducibility in biomedical research. Gigascience.
2020.
9(6) ( link
)
62. Du Y, Huang Q, Arisdakessian C, Garmire L , evaluation of STAR and
Kallisto
aligners on single cell RNA-Seq data, G3.
( link )
61. Schlueter, RJ, Al-Akwaa FM, Benny PA, Gurary A, Xie G, Jia W, Chun X, Chern I,
Garmire L, Metabolomics profile of cord blood is associated with maternal
pre-pregnant
obesity in a multi-ethnic cohort, Journal of Proteome Research. 19(4):1361-1374
( link )
60. Chen B, Garmire LX , Calvisi BF,...,Chen X, Harnessing Big 'Omics' Data
and AI for Drug Discovery in Hepatocellular Carcinoma, Nature Reviews. Gastroenterology &
Hepatology. 17(4):238-251 (
link )
59. Benny PA, Alakwaa FM, Schlueter RJ, Lassiter CB, Garmire LX . A review
of omics approaches to study preeclampsia. Placenta. 2020. 92:17-27. (
link )
58.Liu QZ, Ha MJ, Bhattacharyya R, Garmire L , Baladandayuthapani V,
Network-Based Matching of Patients and Targeted Therapies for Precision Oncology. Pacific
Symposium on Biocomputing 2020 ( link
)
2019
57. Garmire L , From Hawaii to PECASE, tips of success from a female
bioinformatician. Genome Biology.20(1):271. (
link )
56. Garmire LX , Guo-cheng Yuan, Rong Fan, Gene Yeo, John Quackenbush,
Single
Cell Analysis, what is in the future?
( link )
55. J Olender, BD Wang, K Nguyen, T Ching , C Samtal, Y JI, J Rim,
L
Garmire , P Latham, NH Lee, Identification and cloning of a novel FGF3 splice
variant
involved in Arfican American prostate cancer disparities, Molecular Cancer Research, ( link )
54. Zhu X, Garmire LX , Book chapters: chapter 19: Data analysis in Single
Cell
Omics. Single-cell Omics, Vol. 1 (Elsevier)
53. The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell
Resolution, Dev. Cell, 2019 (
link )
52. Benny P, Yamasato K, ..., Ching T, Garmire
LX, Berry M, Towner D, Evaluation of a maternal cardiovascular gene array in early
on-set preeclampia in a dominantly Asian cohort. PLoS One. (
link )
51. Arisdakessian C, Poirion O, Yunits B, Zhu X, Garmire LX . DeepImpute: an
accurate, fast and scalable deep neural network method to impute single-cell RNA-Seq data.
Genome Biology. 20(1):211.
(
link)
2018
50. Stein-O' Brien, Arora R, Culhane AC, Favorov A, Garmire LX , Greene C,
Goff
LA, Li Y, Ngom A, Yanxun Xu Y, Fertig EJ. Entering the matrix: factorization uncovers
knowledge
from omics. Trands in Genetics. 34(10):790-805.
( link)
49. Alakwaa F, Huang S, Yunits B and Garmire LX . Lilikoi: an R package for
personalized pathway-based classification modeling using metabolomics data. Gigascience.
7(12).
( link)
48. Ching T, Zhu X, Garmire LX. Cox-nnet: an artificial neural network Cox
regression for prognosis prediction, PLoS Comp Biol. (
link )
47. Chaudhary K, Lu L, Poirion O, Garmire LX , Multi-modal meta-analysis of
1494
hepatocellular carcinoma samples reveals vast impacts of consensus driver genes on
phenotypes.
Clinical Cancer Research (IF=10.2) (
link)
46. Poirion O, Zhu X,
Ching T, Garmire L Using Single Nucleotide Variations of
Single-Cell RNA-Seq to identify tumor Subpopulation and Genotype-phenotype Links. Nature
Communications. 20;9(1):4892. (
link)
45. Poirion O, Chaudhary K, Garmire LX , Deep Learning data integration for
better risk stratification models of bladder cancer. AMIA Jt Summits Transl Sci Proc. 2018
May
18;2017:197-206
2017
44. Ortega M, Poirion O, Zhu X, Huang SJ , Sebra R, Garmire
LX , Using Single-Cell Multiple Omics Approaches to Resolve Tumor Heterogeneity.
Clinical and Translational Medicine (Springer). 2017. 6(1):46
(
link)
43. Ching T, Garmire LX , Pan-cancer analysis of expressed single nucleotide
variants in long inter-genic non-coding RNA. Pac Symp Biocomput. 2018;23:512-523.
(
link )
42. Al-Akwaa F, Chaudhary K, Garmire LX , Deep learning predicts estrogen
receptor status in breast cancer metabolomics data. Journal of Proteome Research.
(link)
41. Huang SJ, Chaudhary K,
Garmire LX, More is better: recent progress in multi-omics data
integration,
accepted, Frontiers in Genetics. (link)
40. Zhu X, Wolfgruber T,
Tasato A, Arisdakessian C, Garmie D, Garmire LX, Granatum:
A
graphical single cell RNA-Seq analysis pipeline for genomics scientists, Genome Medicine,
9(1):108. (
link)
39. Chaudhary K, Poirion O,
Lu L, Garmire LX, Deep Learning based multi-omics
integration
robustly predicts survivals in liver cancer. Clinical Cancer Research (
link)
38. Wang BD, Ceniccola K, Hwang S, Andrawis R, Horvath A, Freeman JA, Knapp S, Ching
T, Garmire
LX, Pate lV, Garcia-Blanco MA, Patierno SR, Lee NH, Aberrant Alternative Splicing
in
African American Prostate Cancer: novel driver of tumor aggressiveness and drug resistance,
accepted, Nature Communications.
37. Han B, Park HK, Wang H, Panneerselvam J, Shen Y, Zhang J, Li L, Lee YH, Su M, Ching
T, Garmire LX , Jia W, Yu H, Fei P, HDBR1 Modulates U2 snRNP Function to Maintain
RNA
Populations, Contributing to the Suppression of Human Cancer Development, accepted,
Oncogene.
36. Greene CS, Garmire LX , Gilbert JA, Ritchie DR, Hunt L, Celebrate
parasites, accepted, Nature Genetics. (
link)
35. Feng N, Wang Y, Zheng M, Yu X, Lin H, Ma RN, Shi O, Zheng X, Gao M, Yu H, Garmire
L, Qian B. Genome-wide analysis of DNA methylation and their associations with long
noncoding RNA/mRNA expression in non-small-cell lung cancer. Accepted, Epigenomics. (
link)
2016
34. Yang J, Tanaka Y, Seay M, Li Z, Jin JQ, Garmire L,
Zhu X , Euskirchen G, Synder M, Li W, Park IH, Pan X, Weissman SM. Single cell
transcriptomics reveals unanticipated features of early hematopoietic precursors. Nucleic
Acids
Research (2016). (
link)
33. Zhu X, Ching T, Pan X, Weissman S,
Garmire LX. Detecting heterogeneity in single-cell RNA-Seq data by
non-negative
matrix factorization, PeerJ 5:e2888 (
link)
32. Garmire LX, Gliske S, Nguyen QC, Chen JH, Nemati S, VAN Horn JD, Moore
JH,
Shreffler C, Dunn M. The training of next generation data scientists in biomedicine. Pac
Symp
Biocomput. 2016;22:640-645. (
link)
31. Feng N§, Ching T§, Wang Y, Liu B, Lin H,Shi O,Zhang X, Yao Y, Hua L,
Zheng
X, Gao M, Yu H#, Garmire LX
#, Qian B#. Analysis of Microarray Data on Gene Expression and Methylation to
Identify
Long Non-coding RNAs in Non-small Cell Lung Cancer. Scientific Reports 6 (2016). (#:
co-corresponding authors) (
link)
30. Lu L, McCurdy S, Huang S,
Zhu X, Peplowska K, Tiirikainen M, Boisvert WA,
Garmire LX, Time Series miRNA-mRNA integrated analysis reveals critical
miRNAs
and targets in macrophage polarization. Scientific Reports 6 (2016). (
link)
29. Poirion A§, Zhu X§, Ching T, Garmire LX Single-Cell Transcriptomics
Bioinformatics and Computational Challenges,7:163.Frontiers in Genetics (2016). (
link)
28. Huang S*, Kou L*, Furuya H, Yu CH, Kattan M, Goodison S, Garmire
LX, Rosser CJ, A nomogram derived by combination of demographic and biomarker data
improves the non-invasive evaluation of patients at risk for bladder cancer, accepted,
Cancer
Epidemiology, Biomarkers and Prevention, 2016 Jul 6. pii: cebp.0260.
(
link)
27. Wei R, De Vivo I, Huang S,
Zhu X, Risch, H, Moore JH, Yu H, Garmire
LX, Meta-dimensional data integration identifies critical pathways for
susceptibility, tumorigenesis and progression of endometrial cancer, Oncotarget,
2016
Jul 9. doi: 10.18632/oncotarget.10509. (
link)
26. Ching T, Peplowska K, Huang S, Zhu
X , Shen Y, Molnar J, Yu H, Tiirikainen M, Fogelgren B, Fan R, Garmire
LX . Pan-cancer analyses reveal a panel of biologically and clinically relevant
lincRNAs for tumour diagnosis, subtyping and prognosis, 2016, 7:62-72, EBioMedicine. (
link)
25. Huang S, Chong N, Lewis NE, Jia W, Xie G,
Garmire LX. Novel personalized pathway-based metabolomics models reveal key
metabolic pathways for breast cancer diagnosis, 8(1):34, Genome Medicine (2016). (
link)
2015
24. Ching T, Masaki J, Weirather J, Garmire LX
. Non-coding yet non-trivial: a review on the genomics of long intergenic non-coding
RNAs,
8:44. doi: 10.1186/s13040-015-0075-z, BioData Mining. (
link)
23. Xie G, Zhou B, Zhao Y, Qiu Y, Zhao X, Garmire LX
, Yu H, Yen Y, Jia W, Lowered circulating aspartate is a metabolic feature of human
breast
cancer,Oncotarget, 6 (32), 33369-81. (
link)
22. Li J, Ching T,
Huang S, Garmire LX, Using Epigenomics Data to Predict
Differential Gene Expression in Lung Cancer, BMC Bioinformatics. 2015;16 Suppl 5:S10 (
link)
21. Ching T, Ha J,Song MA, Tiirikainen M, Molnar J Berry M, Towner D,
Garmire
LX, Genome-scale hypomethylation in the cord blood cells associated with early
onset
preeclampsia, Clinical Epigenetics. 2015 Mar 13;7(1):21. (
link)
20. Gagliani N, Iseppon A, Vesely CA, Brockmann L, Palm NW, Zeote MR, Licona-Limon P, Paiva
R,
Ching T, Zi X, Fan R, Garmire L, Geginat J, Stockinger B,
Esplugues E, Huber S, Flavell R, Th17 cells transdifferentiate into regulatory T cells
during
resolution of inflammation, Nature. 2015 Apr 29. doi: 10.1038/nature14452. (
link)
2014
19. Menor M, Ching T, Garmire D, Zhu X,
Garmire
LX, mirMark: a site-level and UTR-level classifier for miRNA target prediction.
Genome Biology. Oct 25;15(10):500. (
link)
18. Han L, Zi XY, Garmire LX, Pan XH, Weissman SM, Fan R, Co-detection and
sequencing of genes and transcripts from the same single cells enabled by a microfluidics
platform, Sci Rep. Sep 26;4:6485. doi: 10.1038/srep06485. (
link)
17. Ching T, Huang S,
Garmire LX: power analysis and sample size estimation for RNA-Seq
differential
expression, RNA. 2014 Sep 22. [Epub ahead of print]. (
link)
16. Huang S, Yee C, Ching T, Yu H, Garmire
LX,
A novel model to combine clinical and pathway-based transcriptomic information for the
prognosis
prediction of breast cancer, PLOS Computational Biology. Sep 18;10(9):e1003851. (
link)
15. Ching T,Song MA, Tiirikainen M, Berry M, Towner D, Garmire
LX, Global hypermehtylation coupled with promoter hypomethylation in the
chorioamniotic
membranes of early onset preeclampsia. Mol. Hum. Reprod. Sep;20(9):885-904. (
link)
2013
14. Garmire LX, Subramaniam S. The poor performance of TMM on microRNA-Seq.
RNA
19, 735-6 (2013). PMCID: PMC3683907. (
link)
13. Hadd AG, Houghton J, Choudhary A, Sah S, Chen L, Marko AC, Sanford T, Buddavarapu K,
Krosting
J, Garmire LX, Wylie D, Shinde R, Beaudenon S, Alexander EK, Mambo E, Adai
AT,
Latham GJ. Targeted, high-depth, next-generation sequencing of cancer genes in
formalin-fixed,
paraffin-embedded and fine-needle aspiration tumor specimens. J Mol Diagn 15, 234-47 (2013).
(
link)
Pre-Garmire Group time. 2012 and earlier
12. Colas A, McKeithan W, Cunningham T, Bushway P, Garmire
LX, Duester G, Subramaniam S, Mercola M, Whole genome microRNA screening identifies
let-7 And mir-18 as regulators of germ layer formation during early embryogenesis, Genes
&
Development 26, 2567-79 (2012).PMCID: PMC3521625. (
link)
11. Wu Y, Garmire LX, Fan R, Dynamic analysis of intercellular signaling
reveals
a mechanistic transition in tumor microenvironment, Integrative Biology,(Camb) 4, 1478-86
(2012).PMCID: PMC3502715. (
link)
10. Nathan S*, Garmire LX*, McDonald J, Norihito S, Reichart D, Heudobler D,
Raetz CR, Murphy RC, Merril AH, Brown A, Dennis EA, Li AC, Fahy E, Subramaniam S,
Quehenberger
O, Russell DW, and Glass CK, Regulated accumulation of desmosterol integrates macrophage
lipid
metabolism and inflammatory responses. Cell 151, 138-52 (2012) (*: equal contribution).
PMCID:
PMC3464914. (
link)
9. Garmire LX, Subramaniam S. Evaluation of microRNA-Seq normalization
methods.
RNA 18, 1279-1288 (2012). PMCID: PMC3358649. (
link)
8. Garmire LX, Garmire DG, Huang W, Yao J, Glass CK, Subramaniam S. A global
clustering approach to identify intergenic non-coding RNA, with application in mouse
macrophages. PLoS ONE 6(9):e24051 (2011). PMCID: PMC3184070. (
link)
7. Wang KC, Garmire LX, Young A, Nguyen P, Trinh A, Subramaniam S, Wang NP,
Shyy
J, Li J, Chien S, Role of miR-23b in flow-regulation of microRNA signature and cell growth
in
endothelial Cells, Proc Natl Acad Sci U S A 107, 3234-9 (2010). PMCID: PMC2840325. (
link)
6. Garmire LX, Shen ZX, Briggs S, Yeo G, Glass CK, Subramaniam S, Regulatory
Network of microRNAs in RAW 264.7 Macrophage Cells. Proceedings of 32nd International
Conference
of the IEEE Eng Med Biol Soc 6198-201 (2010). (
link)
5. Garmire LX, Hunt CA, In silico methods for unraveling the mechanistic
complexities of intestinal absorption: metabolism-efflux transport interactions. Drug Metab
Dispos 36,1414-24 (2008). PMC, in process. (
link)
4. Garmire LX, Garmire DG, Hunt CA, An in silico transwell device for drug
transport and drug-drug interaction studies. Pharmaceutical Research 24, 2171-86 (2007).
Featured Article. (
link)
3. Garmire LX, Mechanistic study of enzyme-efflux transporter relations
using in
silico devices. Lecture Notes in Engineering and Computer Science 2167, 34-39 (2007). (
link)
2. Grant MR, Hunt CA, Xia L*, Fata JM, Bissell MJ, Modeling mammary gland
morphogenesis as a reaction-diffusion process, Proceedings of the 26th Annual International
Conference of the IEEE EMBS, San Francisco, CA, USA September 1-5 (2004) (*: Maiden name). (
link)
1. Fan T, Xia L*, Han Y. Mitochondrion and apoptosis. Acta Biochica et
Biophysica Sinica 33, 7-12 (2001) (*: Maiden name). (
link)