Biomarker Benchmark - GSE19804

"Although smoking is the major risk factor for lung cancer, only 7% of female lung cancer patients in Taiwan have a history of cigarette smoking, extremely lower than those in Caucasian females. This report is a comprehensive analysis of the molecular signature of non-smoking female lung cancer in Taiwan."<br>http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19804<br>We have included gene-expression data, the outcome (class) being predicted, and any clinical covariates. When gene-expression data were processed in multiple batches, we have provided batch information. Each data set is organized into a file set, where each contains all pertinent files for an individual dataset. The gene expression files have been normalized using both the SCAN and UPC methods using the SCAN.UPC package in Bioconductor (https://www.bioconductor.org/packages/release/bioc/html/SCAN.UPC.html). We summarized the data at the gene level using the BrainArray resource (http://brainarray.mbni.med.umich.edu/Brainarray/Database/CustomCDF/20.0.0/ensg.asp). We used Ensembl identifiers. The class, clinical, and batch data were hand curated to ensure consistency ("tidy data" formatting). In addition, the data files have been formatted to be imported easily into the ML-Flex machine learning package (http://mlflex.sourceforge.net/).

尽管吸烟是肺癌的主要危险因素，但中国台湾地区仅7%的女性肺癌患者有吸烟史，这一比例远低于高加索女性群体。本报告针对中国台湾地区非吸烟女性肺癌患者的分子特征展开了全面分析。
http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE19804
本数据集包含基因表达数据、待预测的结局（类别）以及所有临床协变量。若基因表达数据经多批次处理，我们已一并提供批次信息。每个数据集均整理为独立文件组，组内包含该数据集的全部相关文件。
基因表达文件已采用Bioconductor的SCAN.UPC软件包，通过SCAN与UPC两种方法完成标准化处理，相关资源链接：https://www.bioconductor.org/packages/release/bioc/html/SCAN.UPC.html。
我们借助BrainArray数据库（http://brainarray.mbni.med.umich.edu/Brainarray/Database/CustomCDF/20.0.0/ensg.asp）在基因水平对数据进行了汇总，并采用Ensembl标识符作为基因标识。
类别、临床及批次数据均经过人工整理，以确保数据一致性，遵循“整洁数据（tidy data）”的格式规范。
此外，所有数据文件均已优化格式，可直接导入ML-Flex机器学习软件包，相关资源链接：http://mlflex.sourceforge.net/。

搜集汇总

背景与挑战

背景概述

该数据集聚焦于台湾非吸烟女性肺癌的分子特征，包含基因表达数据、临床信息和预测类别，数据经过标准化处理并适用于机器学习分析。