Field-wide assessment of differential HT-seq from NCBI GEO database

We analyzed the field of expression profiling by high throughput sequencing, or HT-seq, in terms of replicability and reproducibility, using data from the NCBI GEO (Gene Expression Omnibus) repository. Our work puts an upper bound of 62% to field-wide reproducibility, based on the types of files submitted to GEO. Archived dataset contains following files: - output/parsed_suppfiles.csv, p-value histograms, histogram classes, estimated number of true null hypotheses (pi0). - output/document_summaries.csv, document summaries of NCBI GEO series - output/publications.csv, publication info of NCBI GEO series - output/scopus_citedbycount.csv, Scopus citation info of NCBI GEO series - output/single-cell.csv, single cell experiments - spots.csv, NCBI SRA sequencing run metadata - suppfilenames.txt, list of all supplementary file names of NCBI GEO submissions. One filename per row. - suppfilenames_filtered.txt, list of supplementary file names used for downloading files from NCBI GEO. One filename per row.我们针对高通量测序（high throughput sequencing，HT-seq）表达谱分析领域，围绕可复制性与可重现性两个维度开展分析，所用数据源自NCBI GEO（Gene Expression Omnibus，基因表达综合数据库）存储库。本研究基于提交至GEO的文件类型，得出该领域整体可重现性的上限为62%。存档数据集包含以下文件： - output/parsed_suppfiles.csv：包含P值直方图、直方图类别以及真零假设估计数量（pi0） - output/document_summaries.csv：NCBI GEO系列的文档摘要 - output/publications.csv：NCBI GEO系列的文献信息 - output/scopus_citedbycount.csv：NCBI GEO系列的斯高帕斯（Scopus）引用信息 - output/single-cell.csv：单细胞实验相关数据 - spots.csv：NCBI SRA（Sequence Read Archive，序列读取档案）测序运行元数据 - suppfilenames.txt：NCBI GEO提交的所有补充文件名列表，每行包含一个文件名 - suppfilenames_filtered.txt：用于从NCBI GEO下载文件的筛选后补充文件名列表，每行包含一个文件名