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"en": "Abstract Background DNA methylation plays an important role in studying the epigenetics of various biological processes including many diseases. Although differential methylation of individual cytosines can be informative, given that methylation of neighboring CpGs are typically correlated, analysis of differentially methylated regions is often of more interest. Results We have developed a probabilistic method and software, LuxHMM, that uses hidden Markov model (HMM) to segment the genome into regions and a Bayesian regression model, which allows handling of multiple covariates, to infer differential methylation of regions. Moreover, our model includes experimental parameters that describe the underlying biochemistry in bisulfite sequencing and model inference is done using either variational inference for efficient genome-scale analysis or Hamiltonian Monte Carlo (HMC). Conclusions Analyses of real and simulated bisulfite sequencing data demonstrate the competitive performance of LuxHMM compared with other published differential methylation analysis methods."
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"en": "1. Introduction The file “gen_dd_channel.zip” is a package of a wideband multiple-input multiple-output (MIMO) stored radio channel model at 140 GHz in indoor hall, outdoor suburban, residential and urban scenarios. The package consists of 1) measured wideband double-directional multipath data sets estimated from radio channel sounding and processed through measurement-based ray-launching and 2) MATLAB code sets that allows users to generate wideband MIMO radio channels with various antenna array types, e.g., uniform planar and circular arrays at link ends. 2. What does this package do? Outputs of the channel model The MATLAB file “ChannelGeneratorDD_hexax.m” gives the following variables, among others. The .m file also gives optional figures illustrating antennas and radio channel responses. Variables Descriptions CIR MIMO channel impulse responses CFR MIMO channel frequency responses Inputs to the channel model In order for the MATLAB file “ChannelGeneratorDD_hexax.m” to run properly, the following inputs are required. Directory Descriptions data_030123_double_directional_paths Double-directional multipath data, measured and complemented by ray-launching tool, for various cellular sites. User’s parameters When using “ChannelGeneratorDD_hexax.m”, the following choices are available. Features Choices Channel model types for transfer function generation Antenna / beam shapes List of files in the dataset MATLAB codes that implement the channel model The MATLAB files consist of the following files. File and directory names Descriptions readme_100223.txt Readme file; please read it before using the files ChannelGeneratorDD_hexax.m Main code to run; a code to integrate antenna arrays and double-directional path data to derive MIMO radio channels. No need to see/edit other files. gen_pathDD.m, randl.m, randLoc.m Sub-routines used in ChannelGeneratorDD_hexax.m; no need of modifications. Hexa-X channel generator DD_presentation.pdf User manual of ChannelGeneratorDD_hexax.m. Measured multipath data The directory \"data_030123_double_directional_paths\" in the package contains the following files. Filenames Descriptions readme_100223.txt Readme file; please read it before using the files RTdata_[scenario]_[date].mat Containing double-directional multipath parameters at 140 GHz in the specified scenario, estimated from radio channel sounding and ray-tracing. description_of_data_dd_[scenario].pdf Explaining data formats, the measurement site and sample results. References Details of the data set are available in the following two documents: The stored channel models A. Nimr (ed.), \"Hexa-X Deliverable D2.3 Radio models and enabling techniques towards ultra-high data rate links and capacity in 6G,\" April 2023, available: https://hexa-x.eu/deliverables/ @misc{Hexa-XD23, author = {{A. Nimr (ed.)}}, title = {{Hexa-X Deliverable D2.3 Radio models and enabling techniques towards ultra-high data rate links and capacity in 6G}}, year = {2023}, month = {Apr.}, howpublished = {https://hexa-x.eu/deliverables/}, } Derivation of the data, i.e., radio channel sounding and measurement-based ray-launching M. F. de Guzman, P. Koivumäki and K. Haneda,\"Double-directional multipath data at 140 GHz derived from measurement-based ray-tracer,\" in Proc. 95th Veh. Tech. Conf. (VTC2022-Spring), Helsinki, Finland, June 2022. @INPROCEEDINGS{Deguzman22_VTC, author={De Guzman, Mar Francis and Koivumäki, Pasi and Haneda, Katsuyuki}, booktitle={2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)}, title={Double-directional Multipath Data at 140 GHz Derived from Measurement-based Ray-launcher}, year={2022}, volume={}, number={}, pages={1-6}, doi={10.1109/VTC2022-Spring54318.2022.9860818} } Finally, the code “randl.m” are from the following MATLAB Central File Exchange. Hristo Zhivomirov (2023). Generation of Random Numbers with Laplace Distribution (https://www.mathworks.com/matlabcentral/fileexchange/53397-generation-of-random-numbers-with-laplace-distribution) MATLAB Central File Exchange. Retrieved February 15, 2023. Data usage terms Any usage of the data must be upon consent on the following conditions: The file “ChannelGeneratorDD_hexax.m” is owned by OUL. Contact: Dr. Pekka Kyösti, Pekka.Kyosti@oulu.fi. The other files and those in the directories, except for “randl.m”, are owned by AAU. Contact: Mr. Mar Francis de Guzman, francis.deguzman@aalto.fi. When a scientific paper is published that exploits the data and code, please cite this data set; the citation can be downloaded from the zenodo page of this data set."
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