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author | Pjotr Prins | 2016-05-29 16:57:28 +0000 |
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committer | Pjotr Prins | 2016-05-29 16:57:28 +0000 |
commit | 42f7955c8619ba43766a3b13626d554c2f3d8399 (patch) | |
tree | 49c9d16f5579a61a9900c440c2f114e210cf7bea /doc/joss | |
parent | e7eaf8cd14257c31f83f9e123a8ce443d94280e3 (diff) | |
download | genenetwork2-2.0.tar.gz |
JOSS: add MQM citation and fix typov2.0
Diffstat (limited to 'doc/joss')
-rw-r--r-- | doc/joss/2016/paper.bib | 14 | ||||
-rw-r--r-- | doc/joss/2016/paper.md | 8 |
2 files changed, 18 insertions, 4 deletions
diff --git a/doc/joss/2016/paper.bib b/doc/joss/2016/paper.bib index 73a88227..34c0fd05 100644 --- a/doc/joss/2016/paper.bib +++ b/doc/joss/2016/paper.bib @@ -34,3 +34,17 @@ url = {http://www.ncbi.nlm.nih.gov/pubmed/21892150}, abstract = {We describe factored spectrally transformed linear mixed models (FaST-LMM), an algorithm for genome-wide association studies (GWAS) that scales linearly with cohort size in both run time and memory use. On Wellcome Trust data for 15,000 individuals, FaST-LMM ran an order of magnitude faster than current efficient algorithms. Our algorithm can analyze data for 120,000 individuals in just a few hours, whereas current algorithms fail on data for even 20,000 individuals (http://mscompbio.codeplex.com/).} } + +@article{Arends:2010, + author = {Arends, D. and Prins, P. and Jansen, R. C. and Broman, K. W.}, + title = {{R/qtl: high-throughput multiple QTL mapping}}, + journal = {Bioinformatics}, + year = {2010}, + volume = {26}, + number = {23}, + pages = {2990-2992}, + doi = {10.1093/bioinformatics/btq565}, + url = {http://www.ncbi.nlm.nih.gov/pubmed/20966004}, + abstract = {MOTIVATION: R/qtl is free and powerful software for mapping and exploring quantitative trait loci (QTL). R/qtl provides a fully comprehensive range of methods for a wide range of experimental cross types. We recently added multiple QTL mapping (MQM) to R/qtl. MQM adds higher statistical power to detect and disentangle the effects of multiple linked and unlinked QTL compared with many other methods. MQM for R/qtl adds many new features including improved handling of missing data, analysis of 10,000 s of molecular traits, permutation for determining significance thresholds for QTL and QTL hot spots, and visualizations for cis-trans and QTL interaction effects. MQM for R/qtl is the first free and open source implementation of MQM that is multi-platform, scalable and suitable for automated procedures and large genetical genomics datasets. AVAILABILITY: R/qtl is free and open source multi-platform software for the statistical language R, and is made available under the GPLv3 license. R/qtl can be installed from http://www.rqtl.org/. R/qtl queries should be directed at the mailing list, see http://www.rqtl.org/list/. CONTACT: kbroman@biostat.wisc.edu.}, + +} diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index 81ec2b72..42fcd500 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -41,10 +41,10 @@ bibliography: paper.bib # Summary -GeneNetwork (GN) is a free and open source (FOSS) framework for web -based genetics that can be deployed anywhere. GN allows biologists to -upload experimental data and map phenotypes interactively against -genotypes using tools, such as R/QTL [@mqm paper] mapping, interval +GeneNetwork (GN) is a free and open source (FOSS) framework for +web-based genetics that can be deployed anywhere. GN allows biologists +to upload experimental data and map phenotypes interactively against +genotypes using tools, such as R/QTL [@Arends:2010] mapping, interval mapping for model organisms and pylmm; an implementation of FaST-LMM [@Lippert:2011] which is suitable for human populations and outbred crosses, such as the mouse diversity outcross. Interactive D3 graphics |