3385 gene expression traits for 41 MA lines of Drosophila serrata BSF input format

Emma Hine (2017): 3385 gene expression traits for 41 MA lines of Drosophila serrata BSF input format. The University of Queensland. Dataset. doi:10.14264/uql.2017.783

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Related Publications and Datasets
Project name Bayesian Sparse Factor Analysis of Mutation Accumulation Lines
Project description
We analysed 3385 gene expression traits with non-zero among-line variance in a data set consisting of 41 mutation accumulation lines of Drosophila serrata. Frequent mutational covariance had previously been demonstrated in random 5-trait subsets of these 3385 traits (McGuigan et al 2014). Here we used the Bayesian sparse factor model modified from Runcie and Mukherjee (2013) to characterise the covariance among all 3385 traits simultaneously. We found that 46% of the estimated mutational variance could be attributed to 21 dimensions, which is substantially more than the model allocated to randomised data sets (much closer to zero, but I need to redo this calculation). This result suggests that the distribution of genetic variance arising from mutation is likely to be highly uneven, with implications for the relevance of theoretical models of mutation-selection balance and our understanding of the origin of evolutionary constraints.

Contact name Emma Hine
Contact email e.hine@uq.edu.au
Creator name Emma Hine
Creator(s) role Postdoctoral Fellow
Dataset name 3385 gene expression traits for 41 MA lines of Drosophila serrata BSF input format
Dataset description
The data is contained in an 82 x 16925 matrix. The 82 rows represent 41 mutation lines, each with two biological repliates. The first two rows are the first and second replicates of line 1, and so on. The 16925 columns represent 5 log 10 probe measurements for each of 3385 gene expression traits. The first 5 columns are the 5 probe measurements of gene 1, etc.
Access conditions Open Access
Licencing and terms of access Creative Commons Attribution share alike

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ANZSRC Field of Research (FoR) Code 060412 Quantitative Genetics (incl. Disease and Trait Mapping Genetics)
060303 Biological Adaptation
DOI 10.14264/uql.2017.783
Related Publications
Runcie, D. E. and S. Mukherjee, 2013 Dissecting high- dimensional phenotypes with bayesian sparse factor analysis of genetic covariance matrices. Genetics 194: 753–67.
Language eng
Collection type Dataset
Publisher The University of Queensland
Publication Year 2017

Document type: Data Collection
Collection: Research Data Collections
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Created: Tue, 29 Aug 2017, 13:06:17 EST by Dr Emma Hine