Publications
Preprints
Li YJ, Stanojevic S, He B, Jing Z, Huang Q , Kang J, Garmire
LX, Benchmarking Computational Integration Methods for Spatial Transcriptomics Data (preprint)
Liu W, Yang X , Mao Z, Du Y , Lassiter C, AlAkwaa FM, Benny PA, Garmire LX.:
Severe preeclampsia is not associated with significant DNA methylation changes but cell proportion changes in the cord blood - caution on the importance of confounding adjustment.
(preprint)
Xiaotong Yang, , Hailey K Ballard, Aditya D Mahadevan, Ke Xu, David G Garmire, Elizabeth S Langen, Dominick J Lemas, Garmire LX.:
Deep learning-based prognosis models accurately predict the time to delivery among preeclamptic pregnancies using electronic health record
(preprint)
Haoming Zhu, Xiaotong Yang , Wanling Xie, Elizabeth Langen, Ruowang Li, Lana X Gamire.:
Discover overlooked complications after preeclampsia using electronic health records.
(preprint)
Thatchayut Unjitwattana, Qianhui Huang, Yiwen Yang, Youqi Yang, Mengtian Zhou, Yuheng Du, Lana X Garmire .:
Rescue Blood Contamination in scRNA-Seq Data by Originator, a Computational Deciphering Tool using Genetic and Contextual Information.
(preprint)
Yuheng Du, Paula A. Benny, Ryan J. Schlueter, Alexandra Gurary, Annette Lum-Jones, Cameron B Lassiter, Fadhl M. AlAkwaa, Maarit Tiirikainen, Dena Towner, W. Steven Ward, Lana X Garmire .:
Multi-omics Analysis of Umbilical Cord Hematopoietic Stem Cells from a Multi-ethnic Cohort of Hawaii Reveals the Transgenerational Effect of Maternal Pre-Pregnancy Obesity
(preprint)
2024
106. Hailey K Ballard, Xiaotong Yang, Aditya Mahadevan, Dominick J Lemas, Garmire LX.:
Five-Feature Models to Predict Preeclampsia Onset Time From Electronic Health Record Data: Development and Validation Study. JMIR
(link)
105. Chengyi Li,Ryan Clauson, Luke F. Bugada, Fang Ke, Bing He, Zhixin Yu, Hongwei Chen,
Binyamin Jacobovitz, Hongxiang Hu, Polina Chuikov, Brett Dallas Hill, Syed M. Rizvi, Yudong Song,
Kai Sun, Pasieka Axenov, Daniel Huynh, Xinyi Wang, Lana Garmire, Yu Leo Lei, Irina Grigorova,
Fei Wen, Marilia Cascalho, Wei Gao,* and Duxin Sun: Antigen-Clustered Nanovaccine Achieves
Long-Term Tumor Remission by Promoting B/
CD 4 T Cell Crosstalk.
ACS Nano
(link)
104. Lana X. Garmire, Yijun Li, Qianhui Huang, Chuan Xu, Sarah Teichmann, Naftali Kaminski, Matteo Pellegrini, Quan Nguyen, Andrew E. Teschendorff
: Challenges and perspectives in computational deconvolution of genomics data.
Nature Methods
(link)
2023
103. Yadav S, Zhou S, He B, Du Y, Garmire LX. : Deep learning and transfer learning identify breast cancer survival subtypes from single-cell imaging data.
Communications Medicine.2023
(link)
102. Al Ghadban Y, Du Y , Charnock-Jones DS, Garmire LX, Smith GCS, Sovio U.:
Prediction of spontaneous preterm birth using supervised machine learning on metabolomic data: A case-cohort study.
BJOG.2023
(link)
101. Sperotto F, Gutiérrez-Sacristán A, Makwana S, Li X, Rofeberg VN, Cai T, Bourgeois FT, Omenn GS, Hanauer DA, Sáez C, Bonzel CL, Bucholz E, Dionne A, Elias MD, García-Barrio N, González TG, Issitt RW, Kernan KF, Laird-Gion J, Maidlow SE, Mandl KD, Ahooyi TM, Moraleda C, Morris M, Moshal KL, Pedrera-Jiménez M, Shah MA, South AM, Spiridou A, Taylor DM, Verdy G, Visweswaran S, Wang X, Xia Z, Zachariasse JM; Consortium for Clinical Characterization of COVID-19 by EHR (4CE); Newburger JW, Avillach P.:
Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortium.
EClinicalMedicine.2023
(link)
100. Dagliati A, Strasser ZH, Hossein Abad ZS, Klann JG, Wagholikar KB, Mesa R, Visweswaran S, Morris M, Luo Y, Henderson DW, Samayamuthu MJ, Tan BWQ, Verdy G, Omenn GS, Xia Z, Bellazzi R; Consortium for Clinical Characterization of COVID-19 by EHR (4CE),; Murphy SN, Holmes JH, Estiri H; Consortium for Clinical Characterization of COVID-19 by EHR (4CE).:
Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort study.
EClinicalMedicine.2023
(link)
99. Tan BWL, Tan BWQ, Tan ALM, Schriver ER, Gutiérrez-Sacristán A, Das P, Yuan W, Hutch MR, García Barrio N, Pedrera Jimenez M, Abu-El-Rub N, Morris M,
Moal B, Verdy G, Cho K, Ho YL, Patel LP, Dagliati A, Neuraz A, Klann JG, South AM, Visweswaran S, Hanauer DA, Maidlow SE, Liu M, Mowery DL, Batugo A, Makoudjou A,
Tippmann P, Zöller D, Brat GA, Luo Y, Avillach P, Bellazzi R, Chiovato L, Malovini A, Tibollo V, Samayamuthu MJ, Serrano Balazote P, Xia Z, Loh NHW, Chiudinelli L,
Bonzel CL, Hong C, Zhang HG, Weber GM, Kohane IS, Cai T, Omenn GS, Holmes JH, Ngiam KY; Consortium for Clinical Characterization of COVID-19 by EHR (4CE)
: Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study.
eClinicalMedicine.2023
(link)
98. Zhang HG, Honerlaw JP, Maripuri M, Samayamuthu MJ, Beaulieu-Jones BR, Baig HS, L'Yi S, Ho YL, Morris M, Panickan VA, Wang X, Weber GM,
Liao KP, Visweswaran S, Tan BWQ, Yuan W, Gehlenborg N, Muralidhar S, Ramoni RB; Consortium for Clinical Characterization of COVID-19 by EHR (4CE);
Kohane IS, Xia Z, Cho K, Cai T, Brat GA.
: Potential pitfalls in the use of real-world data for studying long COVID. Nature Medicine.2023
(link)
97. Bing He, Yao Xiao, Haodong Liang, Qianhui Huang, Yuheng Du, Yijun Li, David Garmire , Duxin Sun, Lana X Garmire
: ASGARD is A Single-cell Guided Pipeline to Aid Repurposing of Drugs. Nature Communications.2023
(link)
2022
96. Klann JG, Strasser ZH, Hutch MR, Kennedy CJ, Marwaha JS, Morris M, Samayamuthu MJ, Pfaff AC, Estiri H, South AM, Weber GM, Yuan W, Avillach P,
Wagholikar KB, Luo Y; Consortium for Clinical Characterization of COVID-19 by EHR (4CE); Omenn GS, Visweswaran S, Holmes JH, Xia Z, Brat GA,
Murphy SN.
: Distinguishing Admissions Specifically for COVID-19 From Incidental SARS-CoV-2 Admissions: National Retrospective Electronic Health Record Study.
Jounal of Medical Internet Research.2022
(link)
95. Weber GM, Hong C, Xia Z, Palmer NP, Avillach P, L'Yi S, Keller MS, Murphy SN, Gutiérrez-Sacristán A, Bonzel CL, Serret-Larmande A, Neuraz A,
Omenn GS, Visweswaran S, Klann JG, South AM, Loh NHW, Cannataro M, Beaulieu-Jones BK, Bellazzi R, Agapito G, Alessiani M, Aronow BJ, Bell DS,
Benoit V, Bourgeois FT, Chiovato L, Cho K, Dagliati A, DuVall SL, Barrio NG, Hanauer DA, Ho YL, Holmes JH, Issitt RW, Liu M, Luo Y, Lynch KE,
Maidlow SE, Malovini A, Mandl KD, Mao C, Matheny ME, Moore JH, Morris JS, Morris M, Mowery DL, Ngiam KY, Patel LP, Pedrera-Jimenez M, Ramoni RB,
Schriver ER, Schubert P, Balazote PS, Spiridou A, Tan ALM, Tan BWL, Tibollo V, Torti C, Trecarichi EM, Wang X;
Consortium for Clinical Characterization of COVID-19 by EHR (4CE); Kohane IS, Cai T, Brat GA
: International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality. npj Digital Medicine.2022
(link)
94. GTan BWL, Tan BWQ, Tan ALM, Schriver ER, Gutiérrez-Sacristán A, Das P, Yuan W, Hutch MR, García Barrio N, Pedrera Jimenez M, Abu-El-Rub N,
Morris M, Moal B, Verdy G, Cho K, Ho YL, Patel LP, Dagliati A, Neuraz A, Klann JG, South AM, Visweswaran S, Hanauer DA, Maidlow SE, Liu M, Mowery DL,
Batugo A, Makoudjou A, Tippmann P, Zöller D, Brat GA, Luo Y, Avillach P, Bellazzi R, Chiovato L, Malovini A, Tibollo V,
Samayamuthu MJ, Serrano Balazote P, Xia Z, Loh NHW, Chiudinelli L, Bonzel CL, Hong C, Zhang HG, Weber GM, Kohane IS, Cai T, Omenn GS, Holmes JH,
Ngiam KY; Consortium for Clinical Characterization of COVID-19 by EHR (4CE).
: Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study.
eClinicalMedicine.2022
(link)
93. Gutiérrez-Sacristán A, Serret-Larmande A, Hutch MR, Sáez C, Aronow BJ, Bhatnagar S, Bonzel CL, Cai T, Devkota B, Hanauer DA, Loh NHW, Luo Y, Moal B, Ahooyi TM, Njoroge WFM, Omenn GS, Sanchez-Pinto LN, South AM, Sperotto F, Tan ALM, Taylor DM, Verdy G, Visweswaran S, Xia Z, Zahner J, Avillach P, Bourgeois FT; Consortium for Clinical Characterization of COVID-19 by EHR (4CE).
: Hospitalizations Associated With Mental Health Conditions Among Adolescents in the US and France During the COVID-19 Pandemic. JAMA Network Open.2022
(link)
92. Xiaotong Yang, Paula A Benny, Elorri Cervera-Marzal, Biyu Wu, Cameron B Lassiter, Joshua Astern, Lana X Garmire
: Placental telomere length shortening is not associated with severe preeclampsia but the gestational age. Aging (Albany NY).2022
(link)
91. Jintao Xu, Bing He , Kyle Carver ,Debora Vanheyningen, Brian Parkin, Lana X Garmire , Michal A Olszewski, Jane C Deng
: Heterogeneity of neutrophils and inflammatory responses in patients with COVID-19 and healthy controls. Frontiers in Immunology.2022
(link)
90. Badowski C, He B, Garmire LX
: Blood-derived lncRNAs as biomarkers for cancer diagnosis: the Good, the Bad and the Beauty. npj Precision Oncology.2022
(link)
89. Li Y, Stanojevic S, Garmire LX
: Emerging artificial intelligence applications in Spatial Transcriptomics analysis. Computational and Structural Biotechnology Journal.2022
(link)
88. Stefan Stanojevic, Li YJ, Garmire LX
: Computational Methods for Single-Cell Multi-Omics Integration and Alignment. Accepted. Genomics Proteomics and Bioinformatics.
(link)
87. 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)
86.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. Hepatology Communications.2022 (link )
85. Vahed M, , Vahed M, Garmire LX . BML: a versatile web
server for bipartite motif discovery, Briefings in Bioinformatics. (link )
2021
84. Huang Q, Liu Y, Du Y, Garmire LX; Evaluation of Cell Type Annotation R Packages on
Single-cell RNA-seq Data. Genomics Proteomics Bioinformatics
. 2021 (link )
83. Roberts JM, Rich-Edwards JW, McElrath TF, Garmire L, , Myatt L; Global Pregnancy Collaboration.
Subtypes of Preeclampsia: Recognition and Determining
Clinical Usefulness. (link )
82. Bourgeois FT, Gutiérrez-Sacristán A, Keller MS, Liu M, Hong C, Bonzel CL, Tan ALM, Aronow BJ,
Boeker M, Booth J, Cruz Rojo J, Devkota B, García Barrio N, Gehlenborg N, Geva A, Hanauer DA, Hutch MR,
Issitt RW, Klann JG, Luo Y, Mandl KD, Mao C, Moal B, Moshal KL, Murphy SN, Neuraz A, Ngiam KY, Omenn GS,
Patel LP, Jiménez MP, Sebire NJ, Balazote PS, Serret-Larmande A, South AM, Spiridou A, Taylor DM, Tippmann P,
Visweswaran S, Weber GM, Kohane IS, Cai T, Avillach P; Consortium for Clinical Characterization of COVID-19 by EHR (4CE).
International Analysis of Electronic Health Records of Children and Youth Hospitalized
With COVID-19 Infection in 6 Countries. JAMA Network Open. 2021
(link )
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 , DeepProg: an ensemble of deep-learning and machine-learning models for prognosis
prediction using multi-omics data. 2021 ( link )
74. Cherry C, Maestas DR, Han J, ..., Garmire LX , Elisseeff JH,
Computational reconstruction of the signalling networks surrounding implanted biomaterials from single-cell transcriptomics. 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 . Placentas delivered by pre-pregnant obese women have reduced abundance and diversity in
the microbiome. FASEB. ( link)
72. Zhucheng Zhan, Zheng Jing, Bing He , Noshad Hossenei, Maria Westerhoff,
Eun-Young Choi, Lana Garmire . Two-stage Cox-nnet: biologically interpretable neural-network model
for prognosis prediction and its application in liver cancer survival using histopathology and transcriptomic data
(link)
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)