Gene Expression Data Explorer
Info Gene counts are sourced from ARCHS4, which provides uniform alignment of GEO samples. You can learn more about ARCHS4 and its pipeline here.
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GROUP CONDITION SAMPLES
monocyte-derived dendritic cells
GSM4250898 GSM4250899 GSM4250900 GSM4250901 GSM4250902 GSM4250903 GSM4250904 GSM4250905 GSM4250906 GSM4250907 GSM4250908 GSM4250909 GSM4250910 GSM4250911 GSM4250912
GSM4250913 GSM4250914 GSM4250915 GSM4250916 GSM4250917 GSM4250918 GSM4250919 GSM4250920 GSM4250921 GSM4250922 GSM4250923 GSM4250924 GSM4250925 GSM4250926 GSM4250927
Description

Submission Date: Jan 06, 2020

Summary: We performed a comparison of transcriptome between monocyte-derived dendritic cells (moDC) cultured with neutrophil extracellular traps (NETs) from healthy donors or type 1 diabetes (T1D) patients. The source of moDCs is healthy donors and T1D patients

GEO Accession ID: GSE143143

PMID: 32346380

Description

Submission Date: Jan 06, 2020

Summary: We performed a comparison of transcriptome between monocyte-derived dendritic cells (moDC) cultured with neutrophil extracellular traps (NETs) from healthy donors or type 1 diabetes (T1D) patients. The source of moDCs is healthy donors and T1D patients

GEO Accession ID: GSE143143

PMID: 32346380

Visualize Samples

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.

Signatures:

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Control Condition

Perturbation Condition

Only conditions with at least 1 replicate are available to select

Differential Gene Expression Analysis
Info Differential expression signatures can be computed using DESeq2 or characteristic direction.
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Bulk RNA-seq Appyter

This pipeline enables you to analyze and visualize your bulk RNA sequencing datasets with an array of downstream analysis and visualization tools. The pipeline includes: PCA analysis, Clustergrammer interactive heatmap, library size analysis, differential gene expression analysis, enrichment analysis, and L1000 small molecule search.