Microarray Data Explorer
Info Raw gene Expression data is sourced from GEO, and the appropriate db package for mapping probes to gene symbols was sourced from the Bioconductor AnnotationData packages. You can read more about microarray data here.
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GROUP CONDITION SAMPLES
Peripheral blood mononuclear cells (PBMC)
GSM4749821 GSM4749822 GSM4749823 GSM4749824 GSM4749825 GSM4749826 GSM4749827
GSM4749834 GSM4749835 GSM4749836 GSM4749837 GSM4749838 GSM4749839
GSM4749840 GSM4749841 GSM4749842 GSM4749843 GSM4749844 GSM4749845
GSM4749828 GSM4749829 GSM4749830 GSM4749831 GSM4749832 GSM4749833
GSM4749816 GSM4749817 GSM4749818 GSM4749819 GSM4749820
Description

Submission Date: Aug 27, 2020

Summary: We identified that PBMC of individuals simultaneously affected by a combination of T2DM, dyslipidemia and periodontitis, showed altered molecular profile mainly associated to inflammatory response, immune cell trafficking, and infectious disease pathways

Patients were divided into: T2DMpoorly-DL-P (n=5, Grupo 1), T2DMwell-DL-P (n=7, Grupo 2), DL-P (n=6, Grupo 3), P (n=6, Grupo 4) and Healthy (n=6, Control). T2DM poorly controlled = HbA1c ≥8.5%; T2DM well-controlled patients = HbA1c <7.0%

GEO Accession ID: GSE156993

PMID: No Pubmed ID

Description

Submission Date: Aug 27, 2020

Summary: We identified that PBMC of individuals simultaneously affected by a combination of T2DM, dyslipidemia and periodontitis, showed altered molecular profile mainly associated to inflammatory response, immune cell trafficking, and infectious disease pathways

Patients were divided into: T2DMpoorly-DL-P (n=5, Grupo 1), T2DMwell-DL-P (n=7, Grupo 2), DL-P (n=6, Grupo 3), P (n=6, Grupo 4) and Healthy (n=6, Control). T2DM poorly controlled = HbA1c ≥8.5%; T2DM well-controlled patients = HbA1c <7.0%

GEO Accession ID: GSE156993

PMID: No Pubmed ID

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Info Visualizations are precomputed using the Python package scanpy on the top 5000 most variable genes.

Precomputed Differential Gene Expression

Info Differential expression signatures are automatically computed using the limma R package. More options for differential expression are available to compute below.

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Differential Gene Expression Analysis
Info Differential expression signatures can be computed using DESeq2 or characteristic direction.
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