Trait Data and Analysis for 3639601

RGM domain family, member A

Details and Links

Group Human: HSB group
Tissue Primary Somatosensory (S1) Cortex mRNA
Gene Symbol RGMA
Aliases Wikidata: RGM; BC059072; C230063O06
GeneNetwork: RGMA; RGM
Location Chr 15 @ 93.586646 Mb
Summary This gene encodes a member of the repulsive guidance molecule family. The encoded protein is a glycosylphosphatidylinositol-anchored glycoprotein that functions as an axon guidance protein in the developing and adult central nervous system. This protein may also function as a tumor suppressor in some cancers. Alternate splicing results in multiple transcript variants. [provided by RefSeq, Oct 2009]
Database Human Primary Somatosensory (S1) Cortex Affy Hu-Exon 1.0 ST (Jul11) Quantile
Resource Links Gene    OMIM    GeneMANIA    Protein Atlas    Rat Genome DB    GTEx Portal   
BioGPS    STRING    PANTHER    Gemma    ABA    EBI GWAS   

Statistics


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Calculate Correlations

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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

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  # read into R
  trait <- read.csv("3639601.csv", header = TRUE, comment.char = "#")

  # read into python
  import pandas as pd
  trait = pd.read_csv("3639601.csv", header = 0, comment = "#")
            
          
Edit CaseAttributes

Samples


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