ARCHS4: Massive Mining of Publicly Available RNA Sequencing Data

摘要 许多使用散装和单细胞rna-seq的癌症相关独立研究仍然处于重复使用状态，原因是 它们的可查找性、可访问性、互操作性和可重用性较低。这些研究的数据可以在 基因表达总括(GEO)，但它主要是以原始FASTQ文件的形式提供的，元数据不统一 注释。虽然一些研究提供了对齐的读取文件，但这些文件是非统一处理的。这 缺点是很难跨研究和与额外的外部数据查询和集成这些数据。 为了弥合目前存在于rna-seq数据生成和rna-seq数据处理之间的差距以及 重用后，我们开发了资源ALL RNA-SEQ和CHIP-SEQ样本和签名搜索(ARCHS4)。 ARCHS4提供来自地球观测组织的经过处理的RNA-seq数据，以支持回溯性数据分析和再利用。 ARCHS4迎合了具有不同计算专业水平的用户，并已被用于 许多事后分析和项目。这些目标远远不止为癌症研究人员提供直接的 通过基于网络的用户界面访问RNA-seq数据。我们计划将其他转录组数据 利用深度学习进入RNA-seq-like图谱，鉴定人类RNA-seq样本中的致病序列， 从RNA-SEQ读数中识别较短的变体，根据共表达数据预测基因功能，包括 用小分子调控长的非编码RNA的表达，最重要的是，使用 ARCHS4性价比高的基础设施，继续为社会提供免费的FASTQ对准服务。

SUMMARY Many cancer-related independent studies that employ bulk and single cell RNA-seq remain under reused due to their lower findability, accessibility, interoperability, and reusability. The data from these studies can be found in the Gene Expression Omnibus (GEO) but it is provided mostly as raw FASTQ files with non-uniform metadata annotations. While some studies provide aligned reads files, these are processed non-uniformly. This shortcoming makes it difficult to query and integrate this data across studies and with additional external data. To bridge the gap that currently exists between RNA-seq data generation and RNA-seq data processing and reuse, we developed the resource All RNA-seq and ChIP-Seq Sample and Signature Search (ARCHS4). ARCHS4 provides processed RNA-seq data from GEO to support retrospective data analyses and reuse. ARCHS4 caters to users with different levels of computational expertise and has been already employed for many post-hoc analyses and projects. The goals go far beyond just providing cancer researchers with direct access to RNA-seq data through a web-based user interface. We plan to transform other transcriptomics data into RNA-seq-like profiles with Deep Learning, identify pathogenic sequences in human RNA-seq samples, identify short variants from RNA-seq reads, predict gene function from co-expression data including ways to modulate the expression of long non-coding RNAs with small molecules, and most importantly, using the ARCHS4 cost-effective infrastructure, continue to provide a free FASTQ alignment service to the community.