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publications

Dropout Imputation and Batch Effect Correction for Single-Cell RNA-seq Data

Published in Journal of Bio-X, 2019

Recommended citation: Li, Gang, et al. "Dropout imputation and batch effect correction for single-cell RNA sequencing data." Journal of Bio-X Research 2.4 (2019): 169-177. https://journals.lww.com/jbioxresearch/Fulltext/2019/12000/Dropout_imputation_and_batch_effect_correction_for.4.aspx

SMNN: Batch Effect Correction for Single-cell RNA-seq data via Supervised Mutual Nearest Neighbor Detection

Published in Briefings in Bioinformatics, 2020

Recommended citation: Yuchen Yang, Gang Li, Huijun Qian, Kirk C Wilhelmsen, Yin Shen, Yun Li, SMNN: batch effect correction for single-cell RNA-seq data via supervised mutual nearest neighbor detection, Briefings in Bioinformatics , , bbaa097, https://doi.org/10.1093/bib/bbaa097 https://doi.org/10.1101/672261

Deep Fiducial Inference

Published in Stat, 2020

Recommended citation: Li, G, Hannig, J. Deep fiducial inference. Stat. 2020;e308. https://doi.org/10.1002/sta4.308 https://doi.org/10.1002/sta4.308

CUE: CpG impUtation Ensemble for DNA Methylation Levels Across the Human Methylation450 (HM450) and EPIC (HM850) BeadChip Platforms

Published in Epigenetics, 2020

Recommended citation: Gang Li, Laura Raffield, Mark Logue, Mark W. Miller, Hudson P. Santos Jr, T. Michael O’Shea, Rebecca C. Fry & Yun Li (2020) CUE: CpG impUtation ensemble for DNA methylation levels across the human methylation450 (HM450) and EPIC (HM850) BeadChip platforms, Epigenetics, DOI: 10.1080/15592294.2020.1827716 https://doi.org/10.1080/15592294.2020.1827716

iSMNN: Batch Effect Correction for Single-cell RNA-seq data via Iterative Supervised Mutual Nearest Neighbor Refinementn

Published in Briefings in Bioinformatics, 2021

Recommended citation: Yang, Y., Li, G., Xie, Y., Wang, L., Lagler, T. M., Yang, Y., Liu, J., Qian, L., & Li, Y. (2021). iSMNN: batch effect correction for single-cell RNA-seq data via iterative supervised mutual nearest neighbor refinement. Briefings in bioinformatics, bbab122. Advance online publication. https://doi.org/10.1093/bib/bbab122 https://pubmed.ncbi.nlm.nih.gov/33839756/

talks

Across-Platforms Imputation for DNA Methylation Levels

Published: October 18, 2018

Presented at 2018 American Society of Human Genetics Annual Meeting. See more info here. This is a joint work with Prof. Yun Li et. al.

Deep Fiducial Inference and Approximate Fiducial Computation

Published: April 29, 2019

Presented at Sixth Bayesian, Fiducial, and Frequentist (BFF6) Conference on Model Uncertainty. This is a joint work with Prof. Jan Hannig.

(Contributed Talk) Deep Fiducial Inference and Approximate Fiducial Computation

Published: May 15, 2019

Presented at 2019 MUMS Transition Workshop and SPUQ. See my slides on SAMSI website. This is a joint work with Prof. Jan Hannig.

Deep Fiducial Inference and Approximate Fiducial Computation

Published: June 01, 2019

Received Student and Early-Career Travel Award!

(Invited Talk) Ensemble Imputation for DNA Methylation Levels Across Platforms

Published: July 04, 2019

Presented at The 2019 ICSA China Conference. This is a joint work with Prof. Yun Li et. al.

Ensemble Imputation for DNA Methylation Levels Across Platforms

Published: October 16, 2019

Presented at 2019 American Society of Human Genetics Annual Meeting. This is a joint work with Prof. Yun Li et. al.

Ensemble Imputation for DNA Methylation Levels Across Platforms

Published: February 21, 2020

2020 Conference on Statistical Practice. This is a joint work with Prof. Yun Li et. al.

SMNN: Batch Effect Correction for Single-Cell RNA-seq Data via Supervised Mutual Nearest Neighbor Detection

Published: March 23, 2020

Presented at 2020 Eastern North American Region Spring Meeting. This is a joint work with Prof. Yun Li et. al.

SMNN: Batch Effect Correction for Single-Cell RNA-seq Data via Supervised Mutual Nearest Neighbor Detection

Published: August 06, 2020

Presented at 2020 JSM. This is a joint work with Prof. Yun Li et. al.

DeepGWAS to Enhance GWAS Signals for Neuropsychiatric Disorders via Deep Neural Network

Published: October 27, 2020

Presented at 2020 American Society of Human Genetics Annual Meeting. Our abstract has been selected as reviewer’s choice (~10%). This is a joint work with Prof. Yun Li et. al.

Coupling Machine Learning with Genetics and Epigenetics

Published: November 17, 2020

Coupling Machine Learning with Genetics and Epigenetics

Published: November 30, 2020

Coupling Machine Learning with Fiducial Inference and Genetics

Published: March 08, 2021

Gang successfully passed the public oral defense.

Integration of imaging and sequencing data in the context of visual cell sorting

Published: June 29, 2021

Gang presented at UW 4D-Genome Meeting.

Integration of imaging and sequencing data in the context of visual cell sorting

Published: December 10, 2021

Gang presented at 2021 4DN Annual Meeting .

Integration of imaging and sequencing data in the context of visual cell sorting

Published: April 27, 2022

Gang presented at 2022 UW GS postdoctoral seminar.

Integration of imaging and sequencing data in the context of visual cell sorting

Published: May 10, 2022

Gang was invited to give a talk, “Integration of imaging and sequencing data in the context of visual cell sorting”, at 2022 HSPH Program in Quantitative Genomics Seminar.

Integration of imaging and sequencing data in the context of visual cell sorting

Published: June 04, 2022

Gang was invited to give a talk, “Integration of imaging and sequencing data in the context of visual cell sorting”, at The 5th International Conference on Econometrics and Statistics(EcoStat 2022).