Lung tumor discrimination by deep neural network model CanDo via DNA methylation in bronchial lavage

The dataset includes raw data from targeted methylation sequencing, as well as the count data and codes used in constructing and validating the CanDo model.
Raw data.rar archive contains raw data generated by next-generation sequencing platforms in this study, formatted as FASTQ. These data are organized within subdirectories named after each patient's ID.
Extended Data 1.xlsx (EXdata1) includes targeted methylation detection results for 118 patients.
Extended Data 2.xlsx (EXdata2) displays the calculated average methylation level of each gene for the 118 patients.
Extended Data 3.xlsx (EXdata3) includes targeted methylation detection results for 33 patients in a strictly unbiased validation cohort.
Extended Data 4.xlsx (EXdata4) exhibits the calculated average methylation level of each gene for the 33 patients in the validation cohort.
Code.docx contains all the code utilized in constructing and validating the CanDo model.

本数据集包含靶向甲基化测序原始数据，以及构建与验证CanDo模型所用的计数数据与代码。其中，"Raw data.rar"压缩归档包含本研究中下一代测序（next-generation sequencing）平台生成的原始数据，格式为FASTQ。此类数据以每位患者的ID为名创建子目录进行组织存储。"Extended Data 1.xlsx (EXdata1)"收录了118例患者的靶向甲基化检测结果。"Extended Data 2.xlsx (EXdata2)"展示了118例患者各基因的平均甲基化水平计算结果。"Extended Data 3.xlsx (EXdata3)"包含了严格无偏验证队列中33例患者的靶向甲基化检测结果。"Extended Data 4.xlsx (EXdata4)"呈现了该验证队列中33例患者各基因的平均甲基化水平计算结果。"Code.docx"包含了构建与验证CanDo模型所需的全部代码。