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CIBERSORT specifications

Information


Unique identifier OMICS_16757
Name CIBERSORT
Alternative name Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts
Interface Web user interface
Input data A matrix of reference gene expression signatures and some datasets.
Output data A heat map table, stacked bar plot representations of each cell type present in the mixture.
Programming languages Java, PHP, R
Database management system MySQL
Computer skills Basic
Stability Stable
Maintained Yes

Maintainer


  • person_outline Ash Alizadeh

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Publication for Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts

CIBERSORT citations

 (55)
call_split

Factor XIIIA—expressing inflammatory monocytes promote lung squamous cancer through fibrin cross linking

2018
Nat Commun
PMCID: 5959879
PMID: 29777108
DOI: 10.1038/s41467-018-04355-w
call_split See protocol

[…] is similar to what was previously described for calculating immune gene signatures, but is preceded by the non-parametric steps 1 and 2. This approach is different from deconvolution methods such as CIBERSORT and TIMER because, in theory, with our algorithm, a sample can be relatively enriched with respect to the broadest range of immune cell types (from none to all). It also differs from ssGSEA, […]

library_books

Clinical and genomic landscape of gastric cancer with a mesenchymal phenotype

2018
Nat Commun
PMCID: 5934392
PMID: 29725014
DOI: 10.1038/s41467-018-04179-8

[…] tent with the diffuse type having a higher stromal or non-tumor content, MP subtype has higher non-tumor content than EP subtype (Supplementary Fig. ). Likewise, estimation of non-tumor content using CIBERSORT also showed a higher percentage of non-tumor cells in MP subtype (Supplementary Fig. ). […]

library_books

Deviations of the immune cell landscape between healthy liver and hepatocellular carcinoma

2018
Sci Rep
PMCID: 5906687
PMID: 29670256
DOI: 10.1038/s41598-018-24437-5

[…] CIBERSORT is an analytical tool which accurately quantifies the relative levels of distinct immune cell types within a complex gene expression mixture (https://cibersort.stanford.edu). To characterize […]

library_books

Multi omics analysis reveals neoantigen independent immune cell infiltration in copy number driven cancers

2018
Nat Commun
PMCID: 5882811
PMID: 29615613
DOI: 10.1038/s41467-018-03730-x

[…] ained histopathologists and found patients with high lymphocytes levels show significantly higher CTL scores than those with low lymphocyte infiltration (P = 3.86 × 10−5), though CTLs as evaluated by CIBERSORT failed to reach statistical significance when performing the same analysis (P = 0.11) (Supplementary Fig. ). Furthermore, our CTL score demonstrated strong enrichment in known immuno-oncolog […]

library_books

The immune contexture of hepatocellular carcinoma predicts clinical outcome

2018
Sci Rep
PMCID: 5876395
PMID: 29599491
DOI: 10.1038/s41598-018-21937-2

[…] Figure , genes listed in Supplementary Table ).Figure 5In order to compare our gene signature with the hitherto state of the art, we tested three previously published gene sets: First, we applied the CIBERSORT algorithm to our TCGA patient dataset. Application of CIBERSORT to TCGA HCC samples (which was not done in the original pan-human cancer study by Gentles et al.) and using a resampling test […]

library_books

A Transcriptomic Signature of the Hypothalamic Response to Fasting and BDNF Deficiency in Prader Willi Syndrome

2018
Cell Rep
PMCID: 5896230
PMID: 29590610
DOI: 10.1016/j.celrep.2018.03.018

[…] al cells (). We found that downregulated genes were enriched for neuronal markers (p = 3 × 10−8), while upregulated genes were enriched for microglial genes (p = 9 × 10−5) (D). Further analysis using CIBERSORT () also showed that PWS hypothalamic tissue was characterized by a reduction in neurons (F). Interestingly, this cellular transcriptomic profile aligns with that seen in autism (), in severa […]

Citations

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CIBERSORT institution(s)
Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA; Division of Oncology, Department of Medicine, Stanford Cancer Institute, Stanford University, Stanford, CA, USA; Center for Cancer Systems Biology, Stanford University, Stanford, CA, USA; Department of Radiology, Stanford University, Stanford, CA, USA; Department of Radiation Oncology, Stanford University, Stanford, CA, USA; Division of Thoracic Surgery, Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA; Division of Hematology, Department of Medicine, Stanford Cancer Institute, Stanford University, Stanford, CA, USA
CIBERSORT funding source(s)
This work was supported by grants from the Doris Duke Charitable Foundation, the Damon Runyon Cancer Research Foundation, the B&J Cardan Oncology Research Fund, the Ludwig Institute for Cancer Research, US National Institutes of Health (NIH) grant U01 CA154969, NIH grant U19 AI090019, NIH grant 5T32 CA09302-35, US Department of Defense grant W81XWH-12-1-0498, and a grant from the Siebel Stem Cell Institute and the Thomas and Stacey Siebel Foundation.

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