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1. High Fidelity Text-to-Speech Via Discrete Tokens Using Token Transducer and Group Masked Language Model

Author

Lee, Joun Yeop, Jeong, Myeonghun, Kim, Minchan, Lee, Ji-Hyun, Cho, Hoon-Young, and Kim, Nam Soo

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

We propose a novel two-stage text-to-speech (TTS) framework with two types of discrete tokens, i.e., semantic and acoustic tokens, for high-fidelity speech synthesis. It features two core components: the Interpreting module, which processes text and a speech prompt into semantic tokens focusing on linguistic contents and alignment, and the Speaking module, which captures the timbre of the target voice to generate acoustic tokens from semantic tokens, enriching speech reconstruction. The Interpreting stage employs a transducer for its robustness in aligning text to speech. In contrast, the Speaking stage utilizes a Conformer-based architecture integrated with a Grouped Masked Language Model (G-MLM) to boost computational efficiency. Our experiments verify that this innovative structure surpasses the conventional models in the zero-shot scenario in terms of speech quality and speaker similarity., Comment: Accepted by Interspeech2024

Published
2024

2. A Determinants-of-Fertility Ontology for Detecting Future Signals of Fertility Issues From Social Media Data: Development of an Ontology

Author

Lee, Ji-Hyun, Park, Hyeoun-Ae, and Song, Tae-Min

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundSouth Korea has the lowest fertility rate in the world despite considerable governmental efforts to boost it. Increasing the fertility rate and achieving the desired outcomes of any implemented policies requires reliable data on the ongoing trends in fertility and preparations for the future based on these trends. ObjectiveThe aims of this study were to (1) develop a determinants-of-fertility ontology with terminology for collecting and analyzing social media data; (2) determine the description logics, content coverage, and structural and representational layers of the ontology; and (3) use the ontology to detect future signals of fertility issues. MethodsAn ontology was developed using the Ontology Development 101 methodology. The domain and scope of the ontology were defined by compiling a list of competency questions. The terms were collected from Korean government reports, Korea’s Basic Plan for Low Fertility and Aging Society, a national survey about marriage and childbirth, and social media postings on fertility issues. The classes and their hierarchy were defined using a top-down approach based on an ecological model. The internal structure of classes was defined using the entity-attribute-value model. The description logics of the ontology were evaluated using Protégé (version 5.5.0), and the content coverage was evaluated by comparing concepts extracted from social media posts with the list of ontology classes. The structural and representational layers of the ontology were evaluated by experts. Social media data were collected from 183 online channels between January 1, 2011, and June 30, 2015. To detect future signals of fertility issues, 2 classes of the ontology, the socioeconomic and cultural environment, and public policy, were identified as keywords. A keyword issue map was constructed, and the defined keywords were mapped to identify future signals. R software (version 3.5.2) was used to mine for future signals. ResultsA determinants-of-fertility ontology comprised 236 classes and terminology comprised 1464 synonyms of the 236 classes. Concept classes in the ontology were found to be coherently and consistently defined. The ontology included more than 90% of the concepts that appeared in social media posts on fertility policies. Average scores for all of the criteria for structural and representations layers exceeded 4 on a 5-point scale. Violence and abuse (socioeconomic and cultural factor) and flexible working arrangement (fertility policy) were weak signals, suggesting that they could increase rapidly in the future. ConclusionsThe determinants-of-fertility ontology developed in this study can be used as a framework for collecting and analyzing social media data on fertility issues and detecting future signals of fertility issues. The future signals identified in this study will be useful for policy makers who are developing policy responses to low fertility.

Published
2021
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3. Latent Filling: Latent Space Data Augmentation for Zero-shot Speech Synthesis

Author

Bae, Jae-Sung, Lee, Joun Yeop, Lee, Ji-Hyun, Mun, Seongkyu, Kang, Taehwa, Cho, Hoon-Young, and Kim, Chanwoo

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Previous works in zero-shot text-to-speech (ZS-TTS) have attempted to enhance its systems by enlarging the training data through crowd-sourcing or augmenting existing speech data. However, the use of low-quality data has led to a decline in the overall system performance. To avoid such degradation, instead of directly augmenting the input data, we propose a latent filling (LF) method that adopts simple but effective latent space data augmentation in the speaker embedding space of the ZS-TTS system. By incorporating a consistency loss, LF can be seamlessly integrated into existing ZS-TTS systems without the need for additional training stages. Experimental results show that LF significantly improves speaker similarity while preserving speech quality., Comment: Accepted to ICASSP 2024

Published
2023

16. Analysis of Urban Visitor's Walkability Based On Mobile Data: The Case of Daejeon, Korea

Author

Chang, Mi, Lee, Gi-bbeum, and Lee, Ji-Hyun

Subjects
Computer Science - Social and Information Networks
Abstract

The walkability of destinations plays a decisive role in obtaining a sense of place for urban visitors. For an improved walkability-based visit experience, the city structure is analyzed by dividing it into small units, starting with the destination. However, existing studies focus on the walkability of residents by administrative district and use limited contextual information and structural analysis tools. Therefore, this study aims to structurally understand walkability through network analysis with mobile-based visitor data collected from 822 point-of-interest (POI) in Daejeon. In this paper, the actual walking distance between 95,817 cells with visitors and POI is measured to calculate the edge weight and the influence of cells on POI. We analyze the POI-cell network through edge weight, extract nine communities, understand the city context through POI analysis and derive the following findings. Firstly, it is possible to determine the potential demand by the visitor's walkability-based division. Second, our walkability measurement method follows a bottom-up approach, starting with a small unit cell, understanding the entire city as a community extraction model, and possibly extending to other cities in Korea. Third, POI-centered structural analysis is possible using the number of visitors and distance in the proposed network analysis method.

Published
2022

19. GC-TTS: Few-shot Speaker Adaptation with Geometric Constraints

Author

Kim, Ji-Hoon, Lee, Sang-Hoon, Lee, Ji-Hyun, Jung, Hong-Gyu, and Lee, Seong-Whan

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Machine Learning, Computer Science - Sound
Abstract

Few-shot speaker adaptation is a specific Text-to-Speech (TTS) system that aims to reproduce a novel speaker's voice with a few training data. While numerous attempts have been made to the few-shot speaker adaptation system, there is still a gap in terms of speaker similarity to the target speaker depending on the amount of data. To bridge the gap, we propose GC-TTS which achieves high-quality speaker adaptation with significantly improved speaker similarity. Specifically, we leverage two geometric constraints to learn discriminative speaker representations. Here, a TTS model is pre-trained for base speakers with a sufficient amount of data, and then fine-tuned for novel speakers on a few minutes of data with two geometric constraints. Two geometric constraints enable the model to extract discriminative speaker embeddings from limited data, which leads to the synthesis of intelligible speech. We discuss and verify the effectiveness of GC-TTS by comparing it with popular and essential methods. The experimental results demonstrate that GC-TTS generates high-quality speech from only a few minutes of training data, outperforming standard techniques in terms of speaker similarity to the target speaker., Comment: Accepted paper in IEEE International Conference on Systems, Man, and Cybernetics (SMC 2021)

Published
2021

21. Safety and efficacy of a novel anti-CD19 chimeric antigen receptor T cell product targeting a membrane-proximal domain of CD19 with fast on- and off-rates against non-Hodgkin lymphoma: a first-in-human study

Author

Zhang, Yunlin, Patel, Ruchi P., Kim, Ki Hyun, Cho, Hyungwoo, Jo, Jae-Cheol, Jeong, Seong Hyun, Oh, Sung Yong, Choi, Yoon Seok, Kim, Sung Hyun, Lee, Ji Hyun, Angelos, Mathew, Guruprasad, Puneeth, Cohen, Ivan, Ugwuanyi, Ositadimma, Lee, Yong Gu, Pajarillo, Raymone, Cho, Jong Hyun, Carturan, Alberto, Paruzzo, Luca, Ghilardi, Guido, Wang, Michael, Kim, Soohwan, Kim, Sung-Min, Lee, Hyun-Jong, Park, Ji-Ho, Cui, Leiguang, Lee, Tae Bum, Hwang, In-Sik, Lee, Young-Ha, Lee, Yong-Jun, Porazzi, Patrizia, Liu, Dongfang, Lee, Yoon, Kim, Jong-Hoon, Lee, Jong-Seo, Yoon, Dok Hyun, Chung, Junho, and Ruella, Marco

Published
2023
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28. Real-world data of long-term survival in patients with T-cell lymphoma who underwent stem cell transplantation

Author

Baek, Dong Won, Moon, Joon Ho, Lee, Jae Hoon, Kang, Ka-Won, Lee, Ho Sup, Eom, Hyeon-Seok, Lee, Enuyoung, Lee, Ji Hyun, Lee, Jeong-Ok, Park, Seong Kyu, Kim, Seok Jin, Yoo, Keon Hee, Yoon, Sung-Soo, Koh, Youngil, Kang, Hyoung Jin, Won, Jong-Ho, Lyu, Chuhl Joo, Hahn, Seung Min, Lee, Jung-Hee, Park, Joon Seong, Jo, Jae-Cheol, Mun, Yeung-Chul, Yang, Deok-Hwan, Song, Ga-Young, Lim, Sung-Nam, and Sohn, Sang Kyun

Published
2023
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31. Fre-GAN: Adversarial Frequency-consistent Audio Synthesis

Author

Kim, Ji-Hoon, Lee, Sang-Hoon, Lee, Ji-Hyun, and Lee, Seong-Whan

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Machine Learning
Abstract

Although recent works on neural vocoder have improved the quality of synthesized audio, there still exists a gap between generated and ground-truth audio in frequency space. This difference leads to spectral artifacts such as hissing noise or reverberation, and thus degrades the sample quality. In this paper, we propose Fre-GAN which achieves frequency-consistent audio synthesis with highly improved generation quality. Specifically, we first present resolution-connected generator and resolution-wise discriminators, which help learn various scales of spectral distributions over multiple frequency bands. Additionally, to reproduce high-frequency components accurately, we leverage discrete wavelet transform in the discriminators. From our experiments, Fre-GAN achieves high-fidelity waveform generation with a gap of only 0.03 MOS compared to ground-truth audio while outperforming standard models in quality., Comment: Accepted paper in Interspeech 2021

Published
2021

33. A Simulation Study Evaluating Phase I Clinical Trial Designs for Combinational Agents

Author

Wang, Shu and Lee, Ji-Hyun

Subjects
Statistics - Applications, Statistics - Other Statistics
Abstract

Nowadays, more and more clinical trials choose combinational agents as the intervention to achieve better therapeutic responses. However, dose-finding for combinational agents is much more complicated than single agent as the full order of combination dose toxicity is unknown. Therefore, regular phase I designs are not able to identify the maximum tolerated dose (MTD) of combinational agents. Motivated by such needs, plenty of novel phase I clinical trial designs for combinational agents were proposed. With so many available designs, research that compare their performances, explore parameters' impacts, and provide recommendations is very limited. Therefore, we conducted a simulation study to evaluate multiple phase I designs that proposed to identify single MTD for combinational agents under various scenarios. We also explored influences of different design parameters. In the end, we summarized the pros and cons of each design, and provided a general guideline in design selection., Comment: Journal of Applied Statistics (2022)

Published
2021
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34. Prior antibiotic administration disrupts anti-PD-1 responses in advanced gastric cancer by altering the gut microbiome and systemic immune response

Author

Kim, Chang Gon, Koh, June-Young, Shin, Su-Jin, Shin, Ji-Hee, Hong, Moonki, Chung, Hyun Cheol, Rha, Sun Young, Kim, Hyo Song, Lee, Choong-Kun, Lee, Ji Hyun, Han, Yejeong, Kim, Hyoyong, Che, Xiumei, Yun, Un-Jung, Kim, Hyunki, Kim, Jee Hung, Lee, Seo Young, Park, Su Kyoung, Park, Sejung, Kim, Hyunwook, Ahn, Jin Young, Jeung, Hei-Cheul, Lee, Jeong Seok, Nam, Young-Do, and Jung, Minkyu

Published
2023
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36. Treat-to-target versus high-intensity statin treatment in patients with or without diabetes mellitus: a pre-specified analysis from the LODESTAR trial

Author

Hong, Myeong-Ki, Choi, Donghoon, Ko, Young-Guk, Kim, Byeong-Keuk, Kim, Jung-Sun, Ahn, Chul-Min, Hong, Sung-Jin, Lee, Seung-Jun, Lee, Yong-Joon, Hong, Bum-Kee, Kwon, Hyuck Moon, Kim, Jong-Youn, Min, Pil Ki, Yoon, Young Won, Lee, Byoung Kwon, Rim, Se-Joong, Choi, Eui-Young, CholKang, Woong, Oh, Pyung Chun, Lee, Jong-Young, Lee, Jin-Bae, Kim, Kee Sik, Choi, Ji Yong, Ryu, Jae Kean, Hong, Seung Pyo, Kim, Chang Yeon, Yang, Tae-Hyun, Cho, Hyung-Jin, Yoon, Junghan, Ahn, Min-Soo, Ahn, Sung Gyun, Lee, Jun-Won, Son, Jung-Woo, Jang, Yangsoo, Yoon, Hyuck-Jun, Lee, Cheol Hyun, Hwang, Jongmin, Cho, Yun-Kyeong, Hur, Seung-Ho, Han, Seongwook, Nam, Chang-Wook, Kim, Hyoungseop, Park, Hyoung-Seob, Kim, In-Cheol, Cho, Yun-Hyeong, Jeong, Hyeon-Ju, Kim, Jin-Ho, Lim, Chewan, Suh, Yongsung, Hwang, Eui Seok, Lee, Ji Hyun, Lee, Sung Yun, Kwon, Sung Uk, Kim, Song-Yi, Park, Keun-Ho, Ki, Hyun Kuk, and Kang, Woong Chol

Published
2023
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37. Deep-Learning-Based Whole-Lung and Lung-Lesion Quantification Despite Inconsistent Ground Truth: Application to Computerized Tomography in SARS-CoV-2 Nonhuman Primate Models

Author

Reza, Syed M.S., Chu, Winston T., Homayounieh, Fatemeh, Blain, Maxim, Firouzabadi, Fatemeh D., Anari, Pouria Y., Lee, Ji Hyun, Worwa, Gabriella, Finch, Courtney L., Kuhn, Jens H., Malayeri, Ashkan, Crozier, Ian, Wood, Bradford J., Feuerstein, Irwin M., and Solomon, Jeffrey

Published
2023
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39. Age- and sex-related features of atherosclerosis from coronary computed tomography angiography in patients prior to acute coronary syndrome: results from the ICONIC study

Author

Conte, Edoardo, Dwivedi, Aeshita, Mushtaq, Saima, Pontone, Gianluca, Lin, Fay Y, Hollenberg, Emma J, Lee, Sang-Eun, Bax, Jeroen, Cademartiri, Filippo, Chinnaiyan, Kavitha, Chow, Benjamin JW, Cury, Ricardo C, Feuchtner, Gudrun, Hadamitzky, Martin, Kim, Yong-Jin, Baggiano, Andrea, Leipsic, Jonathon, Maffei, Erica, Marques, Hugo, Plank, Fabian, Raff, Gilbert L, van Rosendael, Alexander R, Villines, Todd C, Weirich, Harald G, Al’Aref, Subhi J, Baskaran, Lohendran, Cho, Iksung, Danad, Ibrahim, Han, Donghee, Heo, Ran, Lee, Ji Hyun, Stuijfzand, Wijnand J, Gransar, Heidi, Lu, Yao, Sung, Ji Min, Park, Hyung-Bok, Al-Mallah, Mouaz H, de Araújo Gonçalves, Pedro, Berman, Daniel S, Budoff, Matthew J, Samady, Habib, Shaw, Leslee J, Stone, Peter H, Virmani, Renu, Narula, Jagat, Min, James K, Chang, Hyuk-Jae, and Andreini, Daniele

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Heart Disease, Atherosclerosis, Biomedical Imaging, Aging, Clinical Research, Heart Disease - Coronary Heart Disease, Cardiovascular, Acute Coronary Syndrome, Aged, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Female, Humans, Male, Plaque, Atherosclerotic, atherosclerosis, gender medicine, cardiac CT, high-risk plaque features, CCTA, Cardiovascular medicine and haematology
Abstract

AimsAlthough there is increasing evidence supporting coronary atherosclerosis evaluation by coronary computed tomography angiography (CCTA), no data are available on age and sex differences for quantitative plaque features. The aim of this study was to investigate sex and age differences in both qualitative and quantitative atherosclerotic features from CCTA prior to acute coronary syndrome (ACS).Methods and resultsWithin the ICONIC study, in which 234 patients with subsequent ACS were propensity matched 1:1 with 234 non-event controls, our current subanalysis included only the ACS cases. Both qualitative and quantitative advance plaque analysis by CCTA were performed by a core laboratory. In 129 cases, culprit lesions identified by invasive coronary angiography at the time of ACS were co-registered to baseline CCTA precursor lesions. The study population was then divided into subgroups according to sex and age (

Published
2021

40. Extracellular vesicles derived from macrophages display glycyl‐tRNA synthetase 1 and exhibit anti‐cancer activity

Author

Goughnour, Peter C, Park, Min Chul, Kim, Sang Bum, Jun, Sangmi, Yang, Won Suk, Chae, Sehyun, Cho, Seongmin, Song, Chihong, Lee, Ji‐Hyun, Hyun, Jae Kyung, Kim, Byung Gyu, Hwang, Daehee, Jung, Hyun Suk, Gho, Yong Song, and Kim, Sunghoon

Subjects
Biochemistry and Cell Biology, Biological Sciences, Cancer, Prevention, Animals, Apoptosis, Carcinogenesis, Cell Line, Tumor, Extracellular Vesicles, Glycine-tRNA Ligase, Macrophages, Mice, Neoplasms, RAW 264.7 Cells, Tumor Suppressor Proteins, extracellular vesicles, glycyl‐tRNA synthetase 1, macrophage, palmitoylation, tumour microenvironment, Biochemistry and cell biology
Abstract

Glycyl-tRNA synthetase 1 (GARS1), a cytosolic enzyme secreted from macrophages, promotes apoptosis in cancer cells. However, the mechanism underlying GARS1 secretion has not been elucidated. Here, we report that GARS1 is secreted through unique extracellular vesicles (EVs) with a hydrodynamic diameter of 20-58 nm (mean diameter: 36.9 nm) and a buoyant density of 1.13-1.17 g/ml. GARS1 was anchored to the surface of these EVs through palmitoylated C390 residue. Proteomic analysis identified 164 proteins that were uniquely enriched in the GARS1-containing EVs (GARS1-EVs). Among the identified factors, insulin-like growth factor II receptor, and vimentin also contributed to the anti-cancer activity of GARS1-EVs. This study identified the unique secretory vesicles containing GARS1 and various intracellular factors that are involved in the immunological defence response against tumorigenesis.

Published
2020

44. A Boosted Ensemble Algorithm for Determination of Plaque Stability in High-Risk Patients on Coronary CTA

Author

Al'Aref, Subhi J, Singh, Gurpreet, Choi, Jeong W, Xu, Zhuoran, Maliakal, Gabriel, van Rosendael, Alexander R, Lee, Benjamin C, Fatima, Zahra, Andreini, Daniele, Bax, Jeroen J, Cademartiri, Filippo, Chinnaiyan, Kavitha, Chow, Benjamin JW, Conte, Edoardo, Cury, Ricardo C, Feuchtner, Gudruf, Hadamitzky, Martin, Kim, Yong-Jin, Lee, Sang-Eun, Leipsic, Jonathon A, Maffei, Erica, Marques, Hugo, Plank, Fabian, Pontone, Gianluca, Raff, Gilbert L, Villines, Todd C, Weirich, Harald G, Cho, Iksung, Danad, Ibrahim, Han, Donghee, Heo, Ran, Lee, Ji Hyun, Rizvi, Asim, Stuijfzand, Wijnand J, Gransar, Heidi, Lu, Yao, Sung, Ji Min, Park, Hyung-Bok, Berman, Daniel S, Budoff, Matthew J, Samady, Habib, Stone, Peter H, Virmani, Renu, Narula, Jagat, Chang, Hyuk-Jae, Lin, Fay Y, Baskaran, Lohendran, Shaw, Leslee J, and Min, James K

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Cardiovascular, Clinical Research, Heart Disease, Heart Disease - Coronary Heart Disease, Atherosclerosis, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Algorithms, Case-Control Studies, Computed Tomography Angiography, Coronary Angiography, Coronary Artery Disease, Coronary Stenosis, Humans, Plaque, Atherosclerotic, Predictive Value of Tests, Severity of Illness Index, acute coronary syndrome, coronary computed tomography angiography, diameter stenosis, machine learning, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

ObjectivesThis study sought to identify culprit lesion (CL) precursors among acute coronary syndrome (ACS) patients based on qualitative and quantitative computed tomography-based plaque characteristics.BackgroundCoronary computed tomography angiography (CTA) has been validated for patient-level prediction of ACS. However, the applicability of coronary CTA to CL assessment is not known.MethodsUtilizing the ICONIC (Incident COroNary Syndromes Identified by Computed Tomography) study, a nested case-control study of 468 patients with baseline coronary CTA, the study included ACS patients with invasive coronary angiography-adjudicated CLs that could be aligned to CL precursors on baseline coronary CTA. Separate blinded core laboratories adjudicated CLs and performed atherosclerotic plaque evaluation. Thereafter, the study used a boosted ensemble algorithm (XGBoost) to develop a predictive model of CLs. Data were randomly split into a training set (80%) and a test set (20%). The area under the receiver-operating characteristic curve of this model was compared with that of diameter stenosis (model 1), high-risk plaque features (model 2), and lesion-level features of CL precursors from the ICONIC study (model 3). Thereafter, the machine learning (ML) model was applied to 234 non-ACS patients with 864 lesions to determine model performance for CL exclusion.ResultsCL precursors were identified by both coronary angiography and baseline coronary CTA in 124 of 234 (53.0%) patients, with a total of 582 lesions (containing 124 CLs) included in the analysis. The ML model demonstrated significantly higher area under the receiver-operating characteristic curve for discriminating CL precursors (0.774; 95% confidence interval [CI]: 0.758 to 0.790) compared with model 1 (0.599; 95% CI: 0.599 to 0.599; p

Published
2020

46. Superior outcomes and high-risk features with carfilzomib, lenalidomide, and dexamethasone combination therapy for patients with relapsed and refractory multiple myeloma: Results of the multicenter KMMWP2201 study

Author

Lee, Ji Hyun, primary, Choi, Jimin, additional, Min, Chang-Ki, additional, Park, Sung-Soo, additional, Jo, Jae-Cheol, additional, Lee, Yoo Jin, additional, Kim, Jin Seok, additional, Eom, Hyeon-Seok, additional, Jung, Jongheon, additional, Moon, Joon Ho, additional, Cho, Hee Jeong, additional, Lee, Myung-won, additional, Yoon, Sung-Soo, additional, Byun, Ja Min, additional, Lee, Jae Hoon, additional, Lee, Je-Jung, additional, Jung, Sung-Hoon, additional, Shin, Ho-Jin, additional, Kim, Do Young, additional, Yi, Jun Ho, additional, Lee, Seung-Shin, additional, Do, Young Rok, additional, Yoon, Dok Hyun, additional, Cho, Hyungwoo, additional, Lee, Won Sik, additional, Lee, Ho Sup, additional, Uhm, Jieun, additional, Kim, Hyo Jung, additional, Jang, Hee Ryeong, additional, Kim, Sung-Hyun, additional, and Kim, Kihyun, additional

Published
2024
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47. Triglyceride-Catabolizing Lactiplantibacillus plantarum GBCC_F0227 Shows an Anti-Obesity Effect in a High-Fat-Diet-Induced C57BL/6 Mouse Obesity Model

Author

Kim, Jinwook, primary, Jeon, Seong-Gak, additional, Kwak, Min-Jung, additional, Park, So-Jung, additional, Hong, Heeji, additional, Choi, Seon-Bin, additional, Lee, Ji-Hyun, additional, Kim, So-Woo, additional, Kim, A-Ram, additional, Park, Young-Kyu, additional, Kim, Byung Kwon, additional, and Yang, Bo-Gie, additional

Published
2024
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50. Accurate and Efficient Estimation of Small P-values with the Cross-Entropy Method: Applications in Genomic Data Analysis

Author

Shi, Yang, Wang, Mengqiao, Shi, Weiping, Lee, Ji-Hyun, Kang, Huining, and Jiang, Hui

Subjects
Statistics - Applications
Abstract

$\textbf{Motivation:}$ Small $p$-values are often required to be accurately estimated in large-scale genomic studies for the adjustment of multiple hypothesis tests and the ranking of genomic features based on their statistical significance. For those complicated test statistics whose cumulative distribution functions are analytically intractable, existing methods usually do not work well with small $p$-values due to lack of accuracy or computational restrictions. We propose a general approach for accurately and efficiently estimating small $p$-values for a broad range of complicated test statistics based on the principle of the cross-entropy method and Markov chain Monte Carlo sampling techniques. $\textbf{Results:}$ We evaluate the performance of the proposed algorithm through simulations and demonstrate its application to three real-world examples in genomic studies. The results show that our approach can accurately evaluate small to extremely small $p$-values (e.g. $10^{-6}$ to $10^{-100}$). The proposed algorithm is helpful for the improvement of some existing test procedures and the development of new test procedures in genomic studies., Comment: 34 pages, 1 figure, 4 tables

Published
2018
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