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Trait Data and Analysis for 10430997

Protein kinase C and casein kinase substrate in neurons 2

Details and Links

Group Mouse: BXD group
Tissue Hippocampus mRNA
Gene Symbol Pacsin2
Aliases Wikidata: Not available
GeneNetwork: Pacsin2; AI197433
Location Chr 15 @ 83.375607 Mb on the minus strand
Summary Enables cytoskeletal protein binding activity; lipid binding activity; and protein-macromolecule adaptor activity. Involved in several processes, including cell migration involved in sprouting angiogenesis; cell projection morphogenesis; and plasma membrane tubulation. Acts upstream of or within negative regulation of endocytosis. Located in caveola; cell-cell junction; and cytosol. Is active in adherens junction and glutamatergic synapse. Is expressed in several structures, including alimentary system; aorta; cerebral cortex ventricular layer; genitourinary system; and thymus. Orthologous to human PACSIN2 (protein kinase C and casein kinase substrate in neurons 2). [provided by Alliance of Genome Resources, May 2025]
Database UTHSC BXD Aged Hippocampus rev3 Affy Mouse Gene 1.0 ST (Sep12) RMA
Resource Links Gene    GeneMANIA    Protein Atlas    Rat Genome DB    GTEx Portal   
UCSC    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

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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).
Haley-Knott Regression
HK regression (QTL Reaper) is a fast mapping method with permutation that works well with F2 intercrosses and backcrosses (PMID: 16718932), but is not recommended for admixed populations, advanced intercrosses, or strain families such as the BXDs (QTL Reaper code).
R/qtl (version 1.44.9)
R/qtl maps using several models and uniquely support 4-way intercrosses such as the "Aging Mouse Lifespan Studies" (NIA UM-HET3). We will add support for R/qtl2 (PMID: 30591514) in the near future—a version that handles complex populations with admixture and many haplotypes.
R/qtl2 (version 0.36)
R/qtl2 (aka qtl2) is a reimplementation of the QTL analysis software R/qtl, to better handle high-dimensional data and complex cross designs.. R/QTL2 documentation
Pair Scan (R/qtl v 1.44.9)
The Pair Scan mapping tool performs a search for joint effects of two separate loci that may influence a trait. This search typically requires large sample sizes. Pair Scans can included covariates such as age and sex. For more on this function by K. Broman and colleagues see www.rdocumentation.org/packages/qtl/versions/1.60/topics/scantwo
More information on R/qtl mapping models and methods can be found here.

Review and Edit Data



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  # read into R
  trait <- read.csv("10430997.csv", header = TRUE, comment.char = "#")

  # read into python
  import pandas as pd
  trait = pd.read_csv("10430997.csv", header = 0, comment = "#")
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Samples


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