Browsing by Author "Zhang, L."
Now showing 1 - 3 of 3
Results Per Page
Sort Options
- A Bayesian Assignment Method for Ambiguous Bisulfite Short ReadsTran, H.; Wu, X.; Tithi, S.; Sun, M.-A.; Xie, H.; Zhang, L. (PLOS, 2016-03-24)DNA methylation is an epigenetic modification critical for normal development and diseases. The determination of genome-wide DNA methylation at single-nucleotide resolution is made possible by sequencing bisulfite treated DNA with next generation high-throughput sequencing. However, aligning bisulfite short reads to a reference genome remains challenging as only a limited proportion of them (around 50–70%) can be aligned uniquely; a significant proportion, known as multireads, are mapped to multiple locations and thus discarded from downstream analyses, causing financial waste and biased methylation inference. To address this issue, we develop a Bayesian model that assigns multireads to their most likely locations based on the posterior probability derived from information hidden in uniquely aligned reads. Analyses of both simulated data and real hairpin bisulfite sequencing data show that our method can effectively assign approximately 70% of the multireads to their best locations with up to 90% accuracy, leading to a significant increase in the overall mapping efficiency. Moreover, the assignment model shows robust performance with low coverage depth, making it particularly attractive considering the prohibitive cost of bisulfite sequencing. Additionally, results show that longer reads help improve the performance of the assignment model. The assignment model is also robust to varying degrees of methylation and varying sequencing error rates. Finally, incorporating prior knowledge on mutation rate and context specific methylation level into the assignment model increases inference accuracy. The assignment model is implemented in the BAM-ABS package and freely available at https://github.com/zhanglabvt/BAM_ABS.
- Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES)Kopacz, M.; Jacob, D. J.; Fisher, J. A.; Logan, J. A.; Zhang, L.; Megretskaia, I. A.; Yantosca, R. M.; Singh, K.; Henze, Daven K.; Burrows, J. P.; Buchwitz, M.; Khlystova, I.; McMillan, W. W.; Gille, J. C.; Edwards, D. P.; Eldering, A.; Thouret, V.; Nedelec, P. (Copernicus Publications, 2010)We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY, and TES satellite instruments in a full-year (May 2004-April 2005) global inversion of CO sources at 4 degrees x 5 degrees spatial resolution and monthly temporal resolution. The inversion uses the GEOS-Chem chemical transport model (CTM) and its adjoint applied to MOPITT, AIRS, and SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and aircraft (MOZAIC) are used for evaluation of the a posteriori solution. Using GEOS-Chem as a common intercomparison platform shows global consistency between the different satellite datasets and with the in situ data. Differences can be largely explained by different averaging kernels and a priori information. The global CO emission from combustion as constrained in the inversion is 1350 Tg a(-1). This is much higher than current bottom-up emission inventories. A large fraction of the correction results from a seasonal underestimate of CO sources at northern mid-latitudes in winter and suggests a larger-than-expected CO source from vehicle cold starts and residential heating. Implementing this seasonal variation of emissions solves the long-standing problem of models underestimating CO in the northern extratropics in winter-spring. A posteriori emissions also indicate a general underestimation of biomass burning in the GFED2 inventory. However, the tropical biomass burning constraints are not quantitatively consistent across the different datasets.
- Measurement of the B0 lifetime and flavor-oscillation frequency using hadronic decays reconstructed in 2019-2021 Belle II dataAblikim, M.; Achasov, M. N.; Adlarson, P.; Ahmed, S.; Albrecht, M.; Amoroso, A.; An, Q.; Bai, X. H.; Bai, Y.; Bakina, O.; Ferroli, R. Baldini; Balossino, I.; Ban, Y.; Begzsuren, K.; Bennett, J.; Berger, N.; Bertani, M.; Bettoni, D.; Bianchi, F.; Biernat, J.; Bloms, J.; Bortone, A.; Boyko, I.; Briere, R. A.; Cai, H.; Cai, X.; Calcaterra, A.; Cao, G. F.; Cao, N.; Cetin, S. A.; Chang, J. F.; Chang, W. L.; Chelkov, G.; Chen, D. Y.; Chen, G.; Chen, H. S.; Chen, M. L.; Chen, S. J.; Chen, X. R.; Chen, Y. B.; Cheng, W.; Cibinetto, G.; Cossio, F.; Cui, X. F.; Dai, H. L.; Dai, J. P.; Dai, X. C.; Dbeyssi, A.; de Boer, R. B.; Dedovich, D.; Deng, Z. Y.; Denig, A.; Denysenko, I.; Destefanis, M.; De Mori, F.; Ding, Y.; Dong, C.; Dong, J.; Dong, L. Y.; Dong, M. Y.; Du, S. X.; Fang, J.; Fang, S. S.; Fang, Y.; Farinelli, R.; Fava, L.; Feldbauer, F.; Felici, G.; Feng, C. Q.; Fritsch, M.; Fu, C. D.; Fu, Y.; Gao, X. L.; Gao, Y.; Gao, Y.; Gao, Y. G.; Garzia, I.; Gersabeck, E. M.; Gilman, A.; Goetzen, K.; Gong, L.; Gong, W. X.; Gradl, W.; Greco, M.; Gu, L. M.; Gu, M. H.; Gu, S.; Gu, Y. T.; Guan, C. Y.; Guo, A. Q.; Guo, L. B.; Guo, R. P.; Guo, Y. P.; Guskov, A.; Han, S.; Han, T. T.; Han, T. Z.; Hao, X. Q.; Harris, F. A.; He, K. L.; Heinsius, F. H.; Held, T.; Heng, Y. K.; Himmelreich, M.; Holtmann, T.; Hou, Y. R.; Hou, Z. L.; Hu, H. M.; Hu, J. F.; Hu, T.; Hu, Y.; Huang, G. S.; Huang, L. Q.; Huang, X. T.; Huesken, N.; Hussain, T.; Andersson, W. Ikegami; Imoehl, W.; Irshad, M.; Jaeger, S.; Ji, Q.; Ji, Q. P.; Ji, X. B.; Ji, X. L.; Jiang, H. B.; Jiang, X. S.; Jiang, X. Y.; Jiao, J. B.; Jiao, Z.; Jin, S.; Jin, Y.; Johansson, T.; Kalantar-Nayestanaki, N.; Kang, X. S.; Kappert, R.; Kavatsyuk, M.; Ke, B. C.; Keshk, I. K.; Khoukaz, A.; Kiese, P.; Kiuchi, R.; Kliemt, R.; Koch, L.; Kolcu, O. B.; Kopf, B.; Kuemmel, M.; Kuessner, M.; Kupsc, A.; Kurth, M. G.; Kuehn, W.; Lane, J. J.; Lange, J. S.; Larin, P.; Lavezzi, L.; Leithoff, H.; Lellmann, M.; Lenz, T.; Li, C.; Li, C. H.; Li, Cheng; Li, D. M.; Li, F.; Li, G.; Li, H. B.; Li, H. J.; Li, J. L.; Li, J. Q.; Li, Ke; Li, L. K.; Li, Lei; Li, P. L.; Li, P. R.; Li, W. D.; Li, W. G.; Li, X. H.; Li, X. L.; Li, Z. B.; Li, Z. Y.; Liang, H.; Liang, H.; Liang, Y. F.; Liang, Y. T.; Liao, L. Z.; Libby, J.; Lin, C. X.; Liu, B.; Liu, B. J.; Liu, C. X.; Liu, D.; Liu, D. Y.; Liu, F. H.; Liu, Fang; Liu, Feng; Liu, H. B.; Liu, H. M.; Liu, Huanhuan; Liu, Huihui; Liu, J. B.; Liu, J. Y.; Liu, K.; Liu, K. Y.; Liu, Ke; Liu, L.; Liu, L. Y.; Liu, Q.; Liu, S. B.; Liu, T.; Liu, X.; Liu, Y. B.; Liu, Z. A.; Liu, Zhiqing; Long, Y. F.; Lou, X. C.; Lu, H. J.; Lu, J. D.; Lu, J. G.; Lu, X. L.; Lu, Y.; Lu, Y. P.; Luo, C. L.; Luo, M. X.; Luo, P. W.; Luo, T.; Luo, X. L.; Lusso, S.; Lyu, X. R.; Ma, F. C.; Ma, H. L.; Ma, L. L.; Ma, M. M.; Ma, Q. M.; Ma, R. Q.; Ma, R. T.; Ma, X. N.; Ma, X. X.; Ma, X. Y.; Ma, Y. M.; Maas, F. E.; Maggiora, M.; Maldaner, S.; Malde, S.; Malik, Q. A.; Mangoni, A.; Mao, Y. J.; Mao, Z. P.; Marcello, S.; Meng, Z. X.; Messchendorp, J. G.; Mezzadri, G.; Min, T. J.; Mitchell, R. E.; Mo, X. H.; Mo, Y. J.; Muchnoi, N. Yu; Muramatsu, H.; Nakhoul, S.; Nefedov, Y.; Nerling, F.; Nikolaev, I. B.; Ning, Z.; Nisar, S.; Olsen, S. L.; Ouyang, Q.; Pacetti, S.; Pan, Y.; Pan, Y.; Papenbrock, M.; Pathak, A.; Patteri, P.; Pelizaeus, M.; Peng, H. P.; Peters, K.; Pettersson, J.; Ping, J. L.; Ping, R. G.; Pitka, A.; Poling, R.; Prasad, V.; Qi, H.; Qi, M.; Qi, T. Y.; Qian, S.; Qiao, C. F.; Qin, L. Q.; Qin, X. P.; Qin, X. S.; Qin, Z. H.; Qiu, J. F.; Qu, S. Q.; Rashid, K. H.; Ravindran, K.; Redmer, C. F.; Rivetti, A.; Rodin, V.; Rolo, M.; Rong, G.; Rosner, Ch; Rump, M.; Sarantsev, A.; Savrie, M.; Schelhaas, Y.; Schnier, C.; Schoenning, K.; Shan, W.; Shan, X. Y.; Shao, M.; Shen, C. P.; Shen, P. X.; Shen, X. Y.; Shi, H. C.; Shi, R. S.; Shi, X.; Shi, X. D.; Song, J. J.; Song, Q. Q.; Song, Y. X.; Sosio, S.; Spataro, S.; Sui, F. F.; Sun, G. X.; Sun, J. F.; Sun, L.; Sun, S. S.; Sun, T.; Sun, W. Y.; Sun, Y. J.; Sun, Y. K.; Sun, Y. Z.; Sun, Z. T.; Tan, Y. X.; Tang, C. J.; Tang, G. Y.; Thoren, V.; Tsednee, B.; Uman, I.; Wang, B.; Wang, B. L.; Wang, C. W.; Wang, D. Y.; Wang, H. P.; Wang, K.; Wang, L. L.; Wang, M.; Wang, M. Z.; Wang, Meng; Wang, W. P.; Wang, X.; Wang, X. F.; Wang, X. L.; Wang, Y.; Wang, Y.; Wang, Y. D.; Wang, Y. F.; Wang, Y. Q.; Wang, Z.; Wang, Z. Y.; Wang, Ziyi; Wang, Zongyuan; Weber, T.; Wei, D. H.; Weidenkaff, P.; Weidner, F.; Wen, H. W.; Wen, S. P.; White, D. J.; Wiedner, U.; Wilkinson, G.; Wolke, M.; Wollenberg, L.; Wu, J. F.; Wu, L. H.; Wu, L. J.; Wu, Z.; Xia, L.; Xiao, S. Y.; Xiao, Y. J.; Xiao, Z. J.; Xie, Y. G.; Xie, Y. H.; Xing, T. Y.; Xiong, X. A.; Xu, G. F.; Xu, J. J.; Xu, Q. J.; Xu, W.; Xu, X. P.; Yan, L.; Yan, W. B.; Yan, W. C.; Yang, H. J.; Yang, H. X.; Yang, L.; Yang, R. X.; Yang, S. L.; Yang, Y. H.; Yang, Y. X.; Yang, Yifan; Yang, Zhi; Ye, M.; Ye, M. H.; Yin, J. H.; You, Z. Y.; Yu, B. X.; Yu, C. X.; Yu, G.; Yu, J. S.; Yu, T.; Yuan, C. Z.; Yuan, W.; Yuan, X. Q.; Yuan, Y.; Yue, C. X.; Yuncu, A.; Zafar, A. A.; Zeng, Y.; Zhang, B. X.; Zhang, Guangyi; Zhang, H. H.; Zhang, H. Y.; Zhang, J. L.; Zhang, J. Q.; Zhang, J. W.; Zhang, J. Y.; Zhang, J. Z.; Zhang, Jianyu; Zhang, Jiawei; Zhang, L.; Zhang, Lei; Zhang, S.; Zhang, S. F.; Zhang, T. J.; Zhang, X. Y.; Zhang, Y.; Zhang, Y. H.; Zhang, Y. T.; Zhang, Yan; Zhang, Yao; Zhang, Yi; Zhang, Z. H.; Zhang, Z. Y.; Zhao, G.; Zhao, J.; Zhao, J. Y.; Zhao, J. Z.; Zhao, Lei; Zhao, Ling; Zhao, M. G.; Zhao, Q.; Zhao, S. J.; Zhao, Y. B.; Zhao, Z. G.; Zhemchugov, A.; Zheng, B.; Zheng, J. P.; Zheng, Y.; Zheng, Y. H.; Zhong, B.; Zhong, C.; Zhou, L. P.; Zhou, Q.; Zhou, X.; Zhou, X. K.; Zhou, X. R.; Zhu, A. N.; Zhu, J.; Zhu, K.; Zhu, K. J.; Zhu, S. H.; Zhu, W. J.; Zhu, X. L.; Zhu, Y. C.; Zhu, Z. A.; Zou, B. S.; Zou, J. H. (American Physical Society, 2023-05-15)We measure the B0 lifetime and flavor-oscillation frequency using B0→D(∗)-π+ decays collected by the Belle II experiment in asymmetric-energy e+e- collisions produced by the SuperKEKB collider operating at the ϒ(4S) resonance. We fit the decay-time distribution of signal decays, where the initial flavor is determined by identifying the flavor of the other B meson in the event. The results, based on 33000 signal decays reconstructed in a data sample corresponding to 190 fb-1, are τB0=(1.499±0.013±0.008) ps, Δmd=(0.516±0.008±0.005) ps-1, where the first uncertainties are statistical and the second are systematic. These results are consistent with the world-average values.