CancerMine

This describes the output files for the CancerMine project. These files are loaded directly by the CancerMine viewer. The code for this viewer is available in the CancerMine Github repo if you want to run it independently. Each file is a tab-delimited file with a header, no comments and no quoting. You likely want <strong>cancermine_collated.tsv</strong> if you just want the list of cancer gene roles. If you want the supporting sentences, look at <strong>cancermine_sentences.tsv</strong>. You can use the <em>matching_id</em> column to connect the two files. If you want to dig further and are okay with a higher false positive rate, look at <strong>cancermine_unfiltered.tsv</strong>. <strong>cancermine_collated.tsv:</strong> This contains the cancer gene roles with citation counts supporting them. It contains the normalized cancer and gene names along with IDs for HUGO, Entrez Gene and the Disease Ontology. <strong>cancermine_sentences.tsv:</strong> This contains the supporting sentences for the cancer gene roles in the collated file. Each row is a single supporting sentence for one cancer gene role. This file contains information on the source publication (e.g. journal, publication date, etc), the actual sentence and the cancer gene role extracted. <strong>cancermine_unfiltered.tsv:</strong> This is the raw output of the applyModelsToSentences.py script across all of PubMed, Pubmed Central Open Access and PubMed Central Author Manuscript Collection. It contains every predicted relation with a prediction score above 0.5. So this may contain many false positives. Each row contain information on the publication (e.g. journal, publication date, etc) along with the sentence and the specific cancer gene role extracted (with HUGO, Entrez Gene and Disease Ontology IDs). This file is further processed to create the other two.本说明面向CancerMine项目的输出文件。此类文件可直接供CancerMine查看器加载使用。若需独立运行该查看器，其代码可在CancerMine的GitHub仓库中获取。 所有文件均为带表头的制表符分隔文件，无注释内容且未使用引号包裹字段。若仅需获取癌症基因关联列表，推荐使用**cancermine_collated.tsv**；若需查看支撑性语句，则可查看**cancermine_sentences.tsv**，二者可通过*matching_id*进行关联。若希望进一步深挖数据且可接受较高的假阳性率，可查看**cancermine_unfiltered.tsv**。 **cancermine_collated.tsv**：该文件收录了带有引用计数的癌症基因关联条目，包含标准化后的癌症与基因名称，以及人类基因组组织（HUGO, Human Genome Organization）、Entrez基因数据库（Entrez Gene）及疾病本体论（Disease Ontology）的相关ID。 **cancermine_sentences.tsv**：该文件收录了整理文件中癌症基因关联的支撑性语句，每一行对应一条癌症基因关联的单条支撑语句。文件包含来源出版物的相关信息（如期刊、发表日期等）、原始语句以及提取得到的癌症基因关联信息。 **cancermine_unfiltered.tsv**：该文件为对所有PubMed、PubMed Central开放获取资源及PubMed Central作者手稿合集执行`applyModelsToSentences.py`脚本后的原始输出结果，收录了所有预测得分高于0.5的关联关系，因此可能包含大量假阳性条目。每一行均包含出版物相关信息（如期刊、发表日期等）、语句内容以及提取得到的具体癌症基因关联（包含HUGO、Entrez基因数据库及疾病本体论ID）。该文件经进一步处理后生成了另外两个文件。