aboutsummaryrefslogtreecommitdiff
path: root/doc
diff options
context:
space:
mode:
authorPjotr Prins2016-05-29 16:57:28 +0000
committerPjotr Prins2016-05-29 16:57:28 +0000
commit42f7955c8619ba43766a3b13626d554c2f3d8399 (patch)
tree49c9d16f5579a61a9900c440c2f114e210cf7bea /doc
parente7eaf8cd14257c31f83f9e123a8ce443d94280e3 (diff)
downloadgenenetwork2-2.0.tar.gz
JOSS: add MQM citation and fix typov2.0
Diffstat (limited to 'doc')
-rw-r--r--doc/joss/2016/paper.bib14
-rw-r--r--doc/joss/2016/paper.md8
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