Trait Data and Analysis for ENSMUSG00000032303

Cholinergic receptor, nicotinic, alpha polypeptide 3

Details and Links

Group Mouse: CFW group
Tissue Hippocampus mRNA
Gene Symbol Chrna3
Aliases Wikidata: BAIPRCK; LNCR2; NACHRA3; PAOD2; (a)3; A730007P14Rik; Acra-3; Acra3
GeneNetwork: (a)3; A730007P14Rik; Acra-3; Acra3; MGC104879
Location Chr 9 @ 55.010354 Mb on the minus strand
Summary Enables acetylcholine-gated cation-selective channel activity. Acts upstream of or within several processes, including activation of transmembrane receptor protein tyrosine kinase activity; behavioral response to nicotine; and chemical synaptic transmission. Is integral component of postsynaptic specialization membrane. Part of acetylcholine-gated channel complex. Is active in cholinergic synapse. Is expressed in several structures, including central nervous system; gut; myenteric nerve plexus; paravertebral ganglion; and retina. Human ortholog(s) of this gene implicated in lung cancer. Orthologous to human CHRNA3 (cholinergic receptor nicotinic alpha 3 subunit). [provided by Alliance of Genome Resources, Apr 2022]
Database UCSD CFW Hippocampus (Jan17) RNA-Seq Log2 Z-score
Resource Links Gene    OMIM    GeneMANIA    Protein Atlas    Rat Genome DB    GTEx Portal   
UCSC    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

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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

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("ENSMUSG00000032303.csv", header = TRUE, comment.char = "#")

  # read into python
  import pandas as pd
  trait = pd.read_csv("ENSMUSG00000032303.csv", header = 0, comment = "#")
Edit CaseAttributes

Samples


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