Trait Data and Analysis for ENSMUST00000119206

Repulsive guidance molecule family member A

Details and Links

Group Mouse: CIE-INIA group
Tissue LCM Brain Regions mRNA
Gene Symbol Rgma
Aliases Wikidata: RGM; BC059072; C230063O06
GeneNetwork: BC059072; C230063O06
Location Chr 7 @ 73.375519 Mb on the plus strand
Summary Enables coreceptor activity and signaling receptor binding activity. Acts upstream of or within several processes, including nervous system development; positive regulation of GTPase activity; and positive regulation of membrane protein ectodomain proteolysis. Located in cell surface. Is expressed in several structures, including future brain; gut; nervous system; sensory organ; and trunk somite. Human ortholog(s) of this gene implicated in multiple sclerosis. Orthologous to human RGMA (repulsive guidance molecule BMP co-receptor a). [provided by Alliance of Genome Resources, Apr 2022]
Database INIA LCM (11 Regions) CIE/AIR RNA-seq Transcript Level (Dec15)
Resource Links Gene    GeneMANIA    Protein Atlas    Rat Genome DB    GTEx Portal   
UCSC    BioGPS    STRING    PANTHER    Gemma    ABA    EBI GWAS   

Statistics


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Transform and Filter Data

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Calculate Correlations

Chr:     Mb:  to 
Sample Correlation
The Sample Correlation is computed between trait data and any other traits in the sample database selected above. Use Spearman Rank when the sample size is small (<20) or when there are influential outliers.
Literature Correlation
The Literature Correlation (Lit r) between this gene and all other genes is computed
using the Semantic Gene Organizer and human, rat, and mouse data from PubMed. Values are ranked by Lit r, but Sample r and Tissue r are also displayed.
More on using Lit r
Tissue Correlation
The Tissue Correlation (Tissue r) estimates the similarity of expression of two genes or transcripts across different cells, tissues, or organs (glossary). Tissue correlations are generated by analyzing expression in multiple samples usually taken from single cases.
Pearson and Spearman Rank correlations have been computed for all pairs of genes using data from mouse samples.

Mapping Tools

Mapping options are disabled for data not matched with genotypes.

Review and Edit Data

            
  # read into R
  trait <- read.csv("ENSMUST00000119206.csv", header = TRUE, comment.char = "#")

  # read into python
  import pandas as pd
  trait = pd.read_csv("ENSMUST00000119206.csv", header = 0, comment = "#")
            
          
Edit CaseAttributes

Samples


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