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Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia
by
Greenleaf, William J
, Majeti, Ravindra
, Mezger, Anja
, Klemm, Sandy
, Gars, Eric
, Kathiria, Arwa S
, Chang, Howard Y
, McGinnis, Lisa M
, Parks, Benjamin
, M Ryan Corces
, Granja, Jeffrey M
, Liedtke, Michaela
, Zheng, Grace X Y
in
Accessibility
/ Blood
/ CD69 antigen
/ Chromatin
/ Deoxyribonucleic acid
/ DNA
/ Epigenetics
/ Gene expression
/ Gene mapping
/ Heterogeneity
/ Leukemia
/ Molecular modelling
/ Patients
/ Phenotypes
/ Proteins
/ Regulatory sequences
/ Runx1 protein
/ Transcription factors
2019
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Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia
by
Greenleaf, William J
, Majeti, Ravindra
, Mezger, Anja
, Klemm, Sandy
, Gars, Eric
, Kathiria, Arwa S
, Chang, Howard Y
, McGinnis, Lisa M
, Parks, Benjamin
, M Ryan Corces
, Granja, Jeffrey M
, Liedtke, Michaela
, Zheng, Grace X Y
in
Accessibility
/ Blood
/ CD69 antigen
/ Chromatin
/ Deoxyribonucleic acid
/ DNA
/ Epigenetics
/ Gene expression
/ Gene mapping
/ Heterogeneity
/ Leukemia
/ Molecular modelling
/ Patients
/ Phenotypes
/ Proteins
/ Regulatory sequences
/ Runx1 protein
/ Transcription factors
2019
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia
by
Greenleaf, William J
, Majeti, Ravindra
, Mezger, Anja
, Klemm, Sandy
, Gars, Eric
, Kathiria, Arwa S
, Chang, Howard Y
, McGinnis, Lisa M
, Parks, Benjamin
, M Ryan Corces
, Granja, Jeffrey M
, Liedtke, Michaela
, Zheng, Grace X Y
in
Accessibility
/ Blood
/ CD69 antigen
/ Chromatin
/ Deoxyribonucleic acid
/ DNA
/ Epigenetics
/ Gene expression
/ Gene mapping
/ Heterogeneity
/ Leukemia
/ Molecular modelling
/ Patients
/ Phenotypes
/ Proteins
/ Regulatory sequences
/ Runx1 protein
/ Transcription factors
2019
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Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia
Journal Article
Single-cell multiomic analysis identifies regulatory programs in mixed-phenotype acute leukemia
2019
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Overview
Identifying the causes of human diseases requires deconvolution of abnormal molecular phenotypes spanning DNA accessibility, gene expression and protein abundance1–3. We present a single-cell framework that integrates highly multiplexed protein quantification, transcriptome profiling and analysis of chromatin accessibility. Using this approach, we establish a normal epigenetic baseline for healthy blood development, which we then use to deconvolve aberrant molecular features within blood from patients with mixed-phenotype acute leukemia4,5. Despite widespread epigenetic heterogeneity within the patient cohort, we observe common malignant signatures across patients as well as patient-specific regulatory features that are shared across phenotypic compartments of individual patients. Integrative analysis of transcriptomic and chromatin-accessibility maps identified 91,601 putative peak-to-gene linkages and transcription factors that regulate leukemia-specific genes, such as RUNX1-linked regulatory elements proximal to the marker gene CD69. These results demonstrate how integrative, multiomic analysis of single cells within the framework of normal development can reveal both distinct and shared molecular mechanisms of disease from patient samples.
Publisher
Nature Publishing Group
Subject
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