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Trait Data and Analysis  for Record ID 1444368_at_B

  Details and Links

Gene Symbol: Chrna3
Aliases: (a)3; A730007P14Rik; Acra-3; Acra3; LNCR2; PAOD2; MGC104879; CHRNA3
Description: cholinergic receptor, nicotinic, alpha polypeptide 3; intron 3 (highly conserved region)
Location: Chr 9 @ 55.022707 Mb on the minus strand
Target Score: BLAT specificity: 12.3   Score: 246  
Species and Group: Mouse, B6BTBRF2
Database 3: (B6 x BTBR)F2-ob/ob Liver mRNA M430 (Jul04) MAS5
Resource Links: Gene  OMIM  GenBank  HomoloGene  
UCSC  BioGPS  STRING  PANTHER  Gemma  ABA  EBI GWAS  Wiki-Pi  

Add To Collection Find similar expression data  Check probe locations at UCSC  Write or review comments about this gene  View SNPs and Indels  Check sequence of probes
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  Basic Statistics



StatisticValue
N of Samples60
Mean8.357
Median8.415
Standard Error (SE)0.039
Standard Deviation (SD)0.306
Minimum7.454
Maximum9.098
Range (log2)1.644
Range (fold)3.125
Interquartile Range1.331

nP_ZnyapE73.gif


This plot evaluates whether data are normally distributed. Different symbols represent different groups.

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

Box_9gAZzps1.gif

More about Box Plots

Bar_rzOG9UHt.gif

Bar_HvZuQ16i.gif

  Calculate Correlations

Database:
Return:

Pearson    Spearman Rank



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.
Database:
Return:



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
Database:
Return:

Pearson    Spearman Rank



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

Chromosome:
Mapping Scale:
Permutations:

Bootstrap Test (n=2000)
Use Parents
Use Weighted



Interval Mapping computes linkage maps for the entire genome or single
chromosomes. The Permutation Test estimates suggestive and significant
linkage scores. The Bootstrap Test estimates the precision of the QTL location.

Display LRS above:
Permutations:

Display all LRS
Use Parents
Use Weighted



Marker regression computes and displays LRS values for individual markers.
This function also lists additive effects (phenotype units per allele) and
dominance deviations for some datasets.

Chromosome:
Mapping Scale:
Control Locus:
Permutations:

Bootstrap Test (n=2000)
Use Parents



Composite Interval Mapping allows you to control for a single marker as
a cofactor. To find a control marker, run the Marker Regression function.

Sort by:
Return:

Permutation Test (n=500)



Pair-Scan searches for pairs of chromosomal regions that are
involved in two-locus epistatic interactions.

  Review and Edit Data

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

  Block samples by index:        
  Options:                       


  Outliers highlighted in  yellow  can be hidden using the Hide Outliers button,
  and samples with no value (x) can be hidden by clicking Hide No Value .


IndexSampleValue
1 B6BTBRF1
2 BTBRB6F1
3 C57BL/6J
4 BTBRT<+>tf/J
5 CASE2
6 CASE12
7 CASE16
8 CASE22
9 CASE44
10 CASE45
11 CASE46
12 CASE48
13 CASE57
14 CASE61
15 CASE72
16 CASE75
17 CASE78
18 CASE100
19 CASE105
20 CASE111
21 CASE112
22 CASE116
23 CASE123
24 CASE130
25 CASE134
26 CASE136
27 CASE148
28 CASE153
29 CASE156
30 CASE157
31 CASE159
32 CASE165
33 CASE167
34 CASE169
35 CASE173
36 CASE183
37 CASE184
38 CASE186
39 CASE190
40 CASE194
41 CASE198
42 CASE200
43 CASE207
44 CASE209
45 CASE210
46 CASE212
47 CASE223
48 CASE224
49 CASE228
50 CASE234
51 CASE235
52 CASE248
53 CASE253
54 CASE254
55 CASE260
56 CASE264
57 CASE266
58 CASE268
59 CASE270
60 CASE285
61 CASE309
62 CASE310
63 CASE317
64 CASE318
65 CASE324
66 CASE327
67 CASE328
68 CASE332
69 CASE343
70 CASE413
71 CASE416
72 CASE418
73 CASE419
74 CASE438
75 CASE439
76 CASE440
77 CASE444
78 CASE455
79 CASE458
80 CASE472
81 CASE473
82 CASE474
83 CASE479
84 CASE484
85 CASE486
86 CASE489
87 CASE491
88 CASE493
89 CASE495
90 CASE499
91 CASE501
92 CASE513
93 CASE517
94 CASE518
95 CASE523
96 CASE537
97 CASE548
98 CASE549
99 CASE550
100 CASE553
101 CASE554
102 CASE559
103 CASE560
104 CASE564
105 CASE566
106 CASE575
107 CASE585
108 CASE605
109 CASE608
110 CASE615
111 CASE617
112 CASE620
113 CASE694
114 CASE722

CITG Web services initiated January, 1994 as Portable Dictionary of the Mouse Genome; June 15, 2001 as WebQTL; and Jan 5, 2005 as GeneNetwork. This site is currently operated by Rob Williams, Pjotr Prins, Zachary Sloan, Arthur Centeno. Design and code by Pjotr Prins, Zach Sloan, Arthur Centeno, Danny Arends, Christian Fischer, Sam Ockman, Lei Yan, Xiaodong Zhou, Christian Fernandez, Ning Liu, Rudi Alberts, Elissa Chesler, Sujoy Roy, Evan G. Williams, Alexander G. Williams, Kenneth Manly, Jintao Wang, and Robert W. Williams, colleagues. Python Powered Registered with Nif
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  • NIGMS Systems Genetics and Precision Medicine project (R01 GM123489, 2017-2021)
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  • NIA Translational Systems Genetics of Mitochondria, Metabolism, and Aging (R01AG043930, 2013-2018)
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  • NCI MMHCC (U01CA105417), NCRR, BIRN, (U24 RR021760)
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