DeconRNASeq statistics

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Citations per year

Number of citations per year for the bioinformatics software tool DeconRNASeq
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Tool usage distribution map

This map represents all the scientific publications referring to DeconRNASeq per scientific context
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Associated diseases

This word cloud represents DeconRNASeq usage per disease context
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Protocols

DeconRNASeq specifications

Information


Unique identifier OMICS_01230
Name DeconRNASeq
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Stability Stable
Maintained Yes

Versioning


No version available

Documentation


Publication for DeconRNASeq

DeconRNASeq citations

 (8)
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Immunization Elicits Antigen Specific Antibody Sequestration in Dorsal Root Ganglia Sensory Neurons

2018
Front Immunol
PMCID: 5932385
PMID: 29755449
DOI: 10.3389/fimmu.2018.00638
call_split See protocol

[…] We utilized DeconRNASeq software () to perform RNA-seq deconvolution analysis to infer cell type compositions of the neuronal preparations isolated from alum-injected and alum + KLH-immunized mice. DeconRNASeq, a […]

library_books

Epigenetic impacts of stress priming of the neuroinflammatory response to sarin surrogate in mice: a model of Gulf War illness

2018
PMCID: 5857314
PMID: 29549885
DOI: 10.1186/s12974-018-1113-9

[…] The R Bioconductor package DeconRNASeq [] was used to estimate the proportion of different cell types within the sample from the RNA-seq data. Data enriched for specific CNS cell types were downloaded from the Gene Expression O […]

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Computational de novo discovery of distinguishing genes for biological processes and cell types in complex tissues

2018
PLoS One
PMCID: 5832224
PMID: 29494600
DOI: 10.1371/journal.pone.0193067

[…] rs measuring the required input. Examples of such partial deconvolution methods are lsfit and cs-lsfit [] which use least-squares fitting, or the quadratic programming approaches used in qprog [] and DeconRNASeq []. The drawback of these methods is that they require hard-to-obtain information on either the sample compositions or high-quality pure cell-type signatures.Complete deconvolution is a mo […]

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Integrated analysis of single cell embryo data yields a unified transcriptome signature for the human pre implantation epiblast

2018
PMCID: 5818005
PMID: 29361568
DOI: 10.1242/dev.158501

[…] rage agglomeration methods were used for cluster analyses. Fractional identity between pre-implantation stages and in vitro cultured cells was determined via quadratic programming using the R package DeconRNASeq (). Average expression levels of cells comprising distinct stages were used as the ‘signature’ dataset, and the relative identity of each culture protocol/sample group was computed by quad […]

library_books

Comprehensive analysis of normal adjacent to tumor transcriptomes

2017
Nat Commun
PMCID: 5651823
PMID: 29057876
DOI: 10.1038/s41467-017-01027-z

[…] tion was performed using the Rtsne (version 0.10) package and the EDASeq package on the log2 CPM values (RNA-seq), or log2 RMA values (microarray). The deconvolution procedure was performed using the DeconRNASeq package. This algorithm adopts a globally optimized non-negative decomposition algorithm through quadratic programming for estimating the mixing proportions of distinctive tissue types. He […]

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Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data

2017
eLife
PMCID: 5718706
PMID: 29130882
DOI: 10.7554/eLife.26476.049

[…] ets, we used the gene signatures obtained from the TCGA data for melanoma or colorectal cancer depending on the origin of cancer.ESTIMATE () was run with their R package version 1.0.11.For CIBERSORT, DeconRNASeq and ISOpure, when run based on our gene expression reference profiles, we used the reference profiles from peripheral blood immune cells for the predictions in blood and the reference prof […]


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DeconRNASeq institution(s)
Biomarker Development, Translational Medicine, Novartis Institutes for BioMedical Research, Cambridge, MA, USA

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