April 12, 2024

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Single-cell database is coming

Single-cell database is coming

Single-cell database is coming.   Disseminate information analysis skills, combined with cutting-edge article innovation. Focus on high-quality personalized drawings and improve the level of article publication. The little master of biographical analysis and drawing is only one short of you-drawing!


Introduction GUIDE 

In recent years, single-cell research has become popular and has been favored by many researchers. The editor has compiled the most comprehensive single-cell online database for everyone so far, which can help you make cell annotation and analysis more accurately, and can also be used for data exploration in the early stage of research.


Single cell database classification

  1. Human Cell Landscape (HCL)
  2. Human Cell Atlas (HCA)
  3. Human Protein Atlas (HPA)
  4. SC2disease
  5. Cell BLAST
  6. CellMarker
  7. PanglaoDB
  8. CancerSEA


Single cell database details

01 Human Cell Landscape

Human Cell Landscape (HCL, http://bis.zju.edu.cn/HCL/ or the mirror address of the National Gene Bank https://db.cngb.org/HCL/)

Single-cell database is coming

HCL is a human cell spectrum platform created by the Zhejiang University team. It contains cells from 60 human tissues and 7 cell lines, spanning embryos and adulthood, and covers eight systems of human cell maps. The results were published in Nature in March 2020. The authors developed the scHCL single cell comparison system to help identify human cell types.

Several major functions are introduced as follows:

  • Landscape:  It can visualize 102 cell types in the human body, group cells, and screen specific tissues or genes.
  • Gallery:  The expression matrix of the single cell of the characteristic organization and the result of gene cluster analysis can be downloaded.
  • Search:  You can select a gene of interest in a specific tissue, and obtain a histogram and tSNE clustering graph of the gene expression.
  • Run-scHCL:   Users are allowed to upload RNA expression matrix (either scRNA or bulk RNA). After running this module, the cell types in the data can be identified, and interactive heat maps and csv file results can be provided.


02 Human Cell Atlas

Human Cell Atlas (HCA, https://data.humancellatlas.org/).

Single-cell database is coming

The Human Cell Atlas (HCA) currently includes 33 tissues, 289 donors, and a total of 450,000 single-cell sequencing data, which can show the cell types, numbers, locations, and relationships among different tissues in the human body. .


03 Human Protein Atlas

Human Protein Atlas (HPA, https://www.proteinatlas.org/humanproteome/celltype).

Single-cell database is coming

This treasure database editor gave you a detailed introduction before, please click here: Please check this treasure database—HPA. And HPA recently launched a new section called “single cell type atlas”, replacing the original “Cell Type”. This section contains single-cell RNA sequencing data from 13 human tissues for a total of 192 cell types. You can search for the number of genes in different cell types, as well as cluster umap maps and expression histograms, and are equipped with immunohistochemical sections and spatial protein expression results.



04 SC2disease

SC2disease (http://easybioai.com/sc2disease/).

Single-cell database is coming

SC2disease includes 29 tissues, 341 cell types, and 25 diseases. Users can obtain the gene expression profile of each cell in each disease state, query the expression changes of the gene of interest in different cell types, search for disease-specific or cell type-specific marker genes, and compare different cell types in disease states and non-disease states Gene expression profile. The results of this database are all manually collected and published in October 2020.


05 Cell Blast

Cell BLAST (https://cblast.gao-lab.org/).

Cell BLAST is a research published in July 2020 that provides a platform for single cell retrieval and annotation. The database covers 27 different tissues, 8 species, and 2,989,582 single-cell data. A set of structured cell type annotations is constructed based on Cell ontology, and deep learning models are used to analyze different data sets. Annotation of cell subpopulations overcomes the batch effect.


06 Cell Marker

CellMarker (http://biocc.hrbmu.edu.cn/CellMarker/).

The Cell Marker database can search for marker genes of different tissues and cell types through manually collected 100,000+ literatures on humans and mice, and provide downloads. It contains a total of 158 human tissues, covering 467 cell types, and 13,605 marker genes. A total of 81 mouse tissues, covering 389 cell types, 9,148 marker genes.


07 PanglaoDB

PanglaoDB (https://panglaodb.se/index.html).

PanglaoDB is a single-cell transcriptome database published in 2019, which collects single-cell data from humans and mice. Contains 4 million+ cells and more than 6000 marker genes, from different tissues and organs. PanglaoDB can be used for cell cluster annotation, and the data can be browsed, analyzed and downloaded online.


08 CancerSEA

CancerSEA (http://biocc.hrbmu.edu.cn/CancerSEA/).

CancerSEA analyzes the different functional states of cancer cells at the single-cell level.

1) CancerSEA provides 14 functional states of 41,900 cancer cells in 25 cancers.
2) CancerSEA can query which type of cancer the gene of interest is related to
3) CancerSEA can query genes (PCG or LncRNA) related to specific functional status.

(source:internet, reference only)

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