SC2disease: a manually curated database of single-cell transcriptome for human diseases.
SC2disease: a manually curated database of single-cell transcriptome for human diseases.
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SC2disease：手动管理的人类疾病单细胞转录组数据库。
DOI：
10.1093/nar/gkaa838
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发表时间：
2021-01-08
影响因子：
14.9
通讯作者：
Peng J
中科院分区：
文献类型：
--
作者：
Zhao T;Lyu S;Lu G;Juan L;Zeng X;Wei Z;Hao J;Peng J
SC2disease (http://easybioai.com/sc2disease/) 是一个手动管理的数据库，旨在为不同疾病的各种细胞类型的基因表达谱提供全面且准确的资源。随着单细胞 RNA 测序 (scRNA-seq) 技术的发展，通过在细胞水平上分析跨细胞类型的转录组，揭示不同组织与不同疾病的细胞异质性已变得可行。特别是，比较不同细胞类型之间的基因表达谱并识别各种疾病中的细胞类型特异性基因，为解决生物学和医学问题提供了新的可能性。然而，人类疾病在细胞水平上的基因表达谱的系统性、层次化和庞大的数据库却很缺乏。因此，我们回顾了2020年3月之前使用scRNA-seq研究人类样本疾病的文献，并开发了SC2disease数据库来总结不同疾病、组织和细胞类型的所有数据。 SC2disease 记录了 946 481 个条目，对应于 341 种细胞类型、29 种组织和 25 种疾病。 SC2disease 数据库中的每个条目都包含不同细胞类型、组织和疾病相关健康状况之间差异表达基因的比较。此外，我们通过统一的流程重新分析基因表达矩阵，以提高不同研究之间的可比性。对于每种疾病，我们还将细胞类型特异性基因与全基因组关联研究 (GWAS) 中确定的先导单核苷酸多态性 (SNP) 的相应基因进行比较，以暗示性状的细胞类型特异性。
SC2disease (http://easybioai.com/sc2disease/) is a manually curated database that aims to provide a comprehensive and accurate resource of gene expression profiles in various cell types for different diseases. With the development of single-cell RNA sequencing (scRNA-seq) technologies, uncovering cellular heterogeneity of different tissues for different diseases has become feasible by profiling transcriptomes across cell types at the cellular level. In particular, comparing gene expression profiles between different cell types and identifying cell-type-specific genes in various diseases offers new possibilities to address biological and medical questions. However, systematic, hierarchical and vast databases of gene expression profiles in human diseases at the cellular level are lacking. Thus, we reviewed the literature prior to March 2020 for studies which used scRNA-seq to study diseases with human samples, and developed the SC2disease database to summarize all the data by different diseases, tissues and cell types. SC2disease documents 946 481 entries, corresponding to 341 cell types, 29 tissues and 25 diseases. Each entry in the SC2disease database contains comparisons of differentially expressed genes between different cell types, tissues and disease-related health status. Furthermore, we reanalyzed gene expression matrix by unified pipeline to improve the comparability between different studies. For each disease, we also compare cell-type-specific genes with the corresponding genes of lead single nucleotide polymorphisms (SNPs) identified in genome-wide association studies (GWAS) to implicate cell type specificity of the traits.
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DOI：
10.1126/science.aad0501
发表时间：
2016-04-08
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Tirosh I;Izar B;Prakadan SM;Wadsworth MH 2nd;Treacy D;Trombetta JJ;Rotem A;Rodman C;Lian C;Murphy G;Fallahi-Sichani M;Dutton-Regester K;Lin JR;Cohen O;Shah P;Lu D;Genshaft AS;Hughes TK;Ziegler CG;Kazer SW;Gaillard A;Kolb KE;Villani AC;Johannessen CM;Andreev AY;Van Allen EM;Bertagnolli M;Sorger PK;Sullivan RJ;Flaherty KT;Frederick DT;Jané-Valbuena J;Yoon CH;Rozenblatt-Rosen O;Shalek AK;Regev A;Garraway LA
通讯作者：
Garraway LA
CancerSEA：癌症单细胞状态图谱
影响因子：
14.9
作者：
Yuan H;Yan M;Zhang G;Liu W;Deng C;Liao G;Xu L;Luo T;Yan H;Long Z;Shi A;Zhao T;Xiao Y;Li X
通讯作者：
Li X
影响因子：
14.9
作者：
Buniello, Annalisa;MacArthur, Jacqueline A. L.;Parkinson, Helen
通讯作者：
Parkinson, Helen
影响因子：
3.7
作者：
Wang, Zishuai;Feng, Xikang;Li, Shuai Cheng
通讯作者：
Li, Shuai Cheng
影响因子：
12.3
作者：
Kim KT;Lee HW;Lee HO;Song HJ;Jeong da E;Shin S;Kim H;Shin Y;Nam DH;Jeong BC;Kirsch DG;Joo KM;Park WY
通讯作者：
Park WY