GSE155064: Gene expression profiling of Control and Low BCAA fed aged mouse muscle

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
Female mice
GSM4694643 GSM4694644 GSM4694645 GSM4694646 GSM4694647 GSM4694648
GSM4694637 GSM4694638 GSM4694639 GSM4694640 GSM4694641 GSM4694642
Male mice
GSM4694631 GSM4694632 GSM4694633 GSM4694634 GSM4694635 GSM4694636
GSM4694625 GSM4694626 GSM4694627 GSM4694628 GSM4694629 GSM4694630
Description

Submission Date: Jul 24, 2020

Summary: Transcriptome analysis of RNA samples from quadriceps muscle to understand how restricting dietary BCAAs influences muscle gene expression

GEO Accession ID: GSE155064

PMID: No Pubmed ID

Description

Submission Date: Jul 24, 2020

Summary: Transcriptome analysis of RNA samples from quadriceps muscle to understand how restricting dietary BCAAs influences muscle gene expression

GEO Accession ID: GSE155064

PMID: No Pubmed ID

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.