Trait Data and Analysis for ENSG00000080644

Cholinergic receptor, 2C nicotinic, 2C alpha 3 (neuronal)

Details and Links

Group Human: GTEx_v5 group
Tissue Ovary mRNA
Gene Symbol CHRNA3
Aliases Wikidata: BAIPRCK; LNCR2; NACHRA3; PAOD2; (a)3; A730007P14Rik; Acra-3; Acra3
GeneNetwork: LNCR2; NACHRA3; PAOD2
Location Chr 15 @ 78.593052 Mb on the minus strand
Summary This locus encodes a member of the nicotinic acetylcholine receptor family of proteins. Members of this family of proteins form pentameric complexes comprised of both alpha and beta subunits. This locus encodes an alpha-type subunit, as it contains characteristic adjacent cysteine residues. The encoded protein is a ligand-gated ion channel that likely plays a role in neurotransmission. Polymorphisms in this gene have been associated with an increased risk of smoking initiation and an increased susceptibility to lung cancer. Alternatively spliced transcript variants have been described. [provided by RefSeq, Nov 2009]
Database GTEXv5 Human Ovary RefSeq (Sep15) RPKM log2
Resource Links Gene    OMIM    GeneMANIA    Protein Atlas    Rat Genome DB    GTEx Portal   
BioGPS    STRING    PANTHER    Gemma    ABA    EBI GWAS   

Statistics


More about Normal Probability Plots and more about interpreting these plots from the glossary

Transform and Filter Data

Edit or delete values in the Trait Data boxes, and use the Reset option as needed.



Outliers highlighted in orange can be hidden using the Hide Outliers button.

Samples with no value (x) can be hidden by clickingHide No Value button.

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

GEMMA
GEMMA maps with correction for kinship using a linear mixed model and can include covariates such as sex and age. Defaults include a minor allele frequency of 0.05 and the leave-one-chromosome-out method (PMID: 2453419, and GitHub code).
More information on R/qtl mapping models and methods can be found here.

Review and Edit Data

            
  # read into R
  trait <- read.csv("ENSG00000080644.csv", header = TRUE, comment.char = "#")

  # read into python
  import pandas as pd
  trait = pd.read_csv("ENSG00000080644.csv", header = 0, comment = "#")
            
          
Edit CaseAttributes

Samples


Loading...