Check in other modules:
ToolboxAD ToolboxAD provides commonly used bioinformatic tools with integrated datasets.
Inhouse Tools
Transfer gene all sorts of Gene IDs with ease.
Principle component analysis with clinical information.
Gene or gene set associated pathway analysis.
External Tools
Mine gene modules with highly correlated expression profiles across sample cohorts.
A single-cell RNA-Seq database for Alzheimer's Disease.
Check RNA expressions in different cell types in brain.
A webserver to estimate cell-/sample-wise metabolic fluxome by using scRNA-seq or general transcriptomics data.
Step 1: choose dataset
Dataset Available for GSEA:
Please scroll down to see more.
Place mouse on left buttons for dataset description.
Dataset: GSE33000
Description: DLPFC (BA9) brain tissues of AD patients, HD patients and non-demented controls samples were obtained from Harvard Brain tissue resource center (HBTRC). Post-mortem interval (PMI) was 17.8+8.3 hours (mean ± standard deviation), sample pH was 6.4±0.3 and RNA integrity number (RIN) was 6.8±0.8 for the average sample in the overall cohort.
Type: microarray
Date: 10/14/2011
More DetailsDataset: GSE44772
Description: Autopsied tissues from dorsolateral prefrontal cortex (PFC), visual cortex (VC) and cerebellum (CR) in brains of LOAD patients, and non-demented healthy controls, collected through the Harvard Brain Tissue Resource Center (HBTRC), were profiled on a custom-made Agilent 44K array (GPL4372_1).
Type: microarray
Date: 3/1/2013
More DetailsDataset: GSE48350
Description: This dataset contains microarray data from normal controls (aged 20-99 yrs) and Alzheimer's disease cases, from 4 brain regions: hippocampus, entorhinal cortex, superior frontal cortex, post-central gyrus.
Type: microarray
Date: 6/27/2013
More DetailsDataset: GSE5281
Description: Collect brain samples from three Alzheimer’s Disease Centers (ADCs) for subsequent gene expression, age groups, and APOE genotype. Expression profile LCM-captured cells on the Affymetrix U133 Plus 2.0 array. Perform LCM on 6 brain regions with about 14 biological replicates per brain region. The brain regions are as follows: 1) entorhinal cortex 2) hippocampus 3) medial temporal gyrus 4) posterior cingulate 5) superior frontal gyrus and 6) primary visual cortex.
Type: microarray
Date: 7/10/2006
More DetailsDataset: GSE84422
Description: 125 human brains were accessed from the Mount Sinai/JJ Peters VA Medical Center Brain Bank (MSBB). RNA samples from 19 brain regions isolated from the 125 MSBB specimens were collected and profiled using Affymetrix Genechip microarrays. There were 50 to 60 subjects per brain region with varying degrees of AD pathological abnormalities.
Type: microarray
Date: 08/19/2016
More DetailsDataset: GSE131617
Description: Transcriptome analysis of post-mortem brain tissue specimens from three brain regions (BRs), entorinal, temporal and frontal cortices, of 71 Japanese brain-donor subjects to identify genes relevant to the expansion of neurofibrillary tangles. In total, 213 brain tissue specimens (= 71 subjects × 3 BRs) were involved in this study.
Type: microarray
Date: 5/22/2019
More DetailsStep 1: choose dataset
Dataset Available for PCA:
Please scroll down to see more.
Place mouse on left buttons for dataset description.
Dataset: GSE33000
Description: DLPFC (BA9) brain tissues of AD patients, HD patients and non-demented controls samples were obtained from Harvard Brain tissue resource center (HBTRC). Post-mortem interval (PMI) was 17.8+8.3 hours (mean ± standard deviation), sample pH was 6.4±0.3 and RNA integrity number (RIN) was 6.8±0.8 for the average sample in the overall cohort.
Type: microarray
Date: 10/14/2011
More DetailsDataset: GSE44772
Description: Autopsied tissues from dorsolateral prefrontal cortex (PFC), visual cortex (VC) and cerebellum (CR) in brains of LOAD patients, and non-demented healthy controls, collected through the Harvard Brain Tissue Resource Center (HBTRC), were profiled on a custom-made Agilent 44K array (GPL4372_1).
Type: microarray
Date: 3/1/2013
More DetailsDataset: GSE48350
Description: This dataset contains microarray data from normal controls (aged 20-99 yrs) and Alzheimer's disease cases, from 4 brain regions: hippocampus, entorhinal cortex, superior frontal cortex, post-central gyrus.
Type: microarray
Date: 6/27/2013
More DetailsDataset: GSE5281
Description: Collect brain samples from three Alzheimer’s Disease Centers (ADCs) for subsequent gene expression, age groups, and APOE genotype. Expression profile LCM-captured cells on the Affymetrix U133 Plus 2.0 array. Perform LCM on 6 brain regions with about 14 biological replicates per brain region. The brain regions are as follows: 1) entorhinal cortex 2) hippocampus 3) medial temporal gyrus 4) posterior cingulate 5) superior frontal gyrus and 6) primary visual cortex.
Type: microarray
Date: 7/10/2006
More DetailsDataset: GSE84422
Description: 125 human brains were accessed from the Mount Sinai/JJ Peters VA Medical Center Brain Bank (MSBB). RNA samples from 19 brain regions isolated from the 125 MSBB specimens were collected and profiled using Affymetrix Genechip microarrays. There were 50 to 60 subjects per brain region with varying degrees of AD pathological abnormalities.
Type: microarray
Date: 08/19/2016
More DetailsDataset: GSE131617
Description: Transcriptome analysis of post-mortem brain tissue specimens from three brain regions (BRs), entorinal, temporal and frontal cortices, of 71 Japanese brain-donor subjects to identify genes relevant to the expansion of neurofibrillary tangles. In total, 213 brain tissue specimens (= 71 subjects × 3 BRs) were involved in this study.
Type: microarray
Date: 5/22/2019
More DetailsView Analysis Results:
ID Converter Notice
IDs provided by ID Converter is updated Agust 2021, since ID is a ever changing property, it is users responsibility to make sure all IDs used for their research is up to date and accurate. To continue, click Accept.
Biolearns Notice
Biolearn is a web server that mines gene modules with highly correlated expression profiles across sample cohorts. You are now leaving ADE site, please click Continue button below to proceed.
Reference:Huang Z, Han Z, Shao W, Xiang S, Salama P, Rizkalla M, Huang K, Zhang J. TSUNAMI: translational bioinformatics tool suite for network analysis and mining. Genomics, Proteomics & Bioinformatics. 2021 Mar 8.
scREAD Notice
You will access scREAD website, a single-cell RNA-Seq database for Alzheimer's Disease You are now leaving ADE site, please click Continue button below to proceed.
Reference:Jiang, Jing, Cankun Wang, Ren Qi, Hongjun Fu, and Qin Ma. “ScREAD: A Single-Cell RNA-Seq Database for Alzheimer’s Disease.” IScience 23, no. 11 (November 20, 2020): 101769.
RNA expression in cell types Notice
You will access celltypes.org .You are now leaving ADE site, please click Continue button below to proceed.
Reference:1. Zhang Y, Chen K, Sloan SA, Bennett ML, Scholze AR, O'Keeffe S, Phatnani HP, Guarnieri P, Caneda C, Ruderisch N, Deng S. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. Journal of Neuroscience. 2014 Sep 3;34(36):11929-47.
2. Darmanis S, Sloan SA, Zhang Y, Enge M, Caneda C, Shuer LM, Gephart MG, Barres BA, Quake SR. A survey of human brain transcriptome diversity at the single cell level. Proceedings of the National Academy of Sciences. 2015 Jun 9;112(23):7285-90.
3. Zhang Y, Sloan SA, Clarke LE, Caneda C, Plaza CA, Blumenthal PD, Vogel H, Steinberg GK, Edwards MS, Li G, Duncan III JA. Purification and characterization of progenitor and mature human astrocytes reveals transcriptional and functional differences with mouse. Neuron. 2016 Jan 6;89(1):37-53.
4. Tasic B, Menon V, Nguyen TN, Kim TK, Jarsky T, Yao Z, Levi B, Gray LT, Sorensen SA, Dolbeare T, Bertagnolli D. Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nature neuroscience. 2016 Feb;19(2):335-46.
5. Zeisel A, Muñoz-Manchado AB, Codeluppi S, Lönnerberg P, La Manno G, Juréus A, Marques S, Munguba H, He L, Betsholtz C, Rolny C. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science. 2015 Mar 6;347(6226):1138-42.
scFLUX
You will access scflux.org .You are now leaving ADE site, please click Continue button below to proceed.
Reference:Alghamdi N, Chang W, Dang P, Lu X, Wan C, Gampala S, Huang Z, Wang J, Ma Q, Zang Y, Fishel M, Cao S, Zhang C. A graph neural network model to estimate cell-wise metabolic flux using single-cell RNA-seq data. Genome Res. 2021 Oct;31(10):1867-1884. doi: 10.1101/gr.271205.120. Epub 2021 Jul 22. PMID: 34301623; PMCID: PMC8494226.