From 4ccb2411b78bcc5112316cef7192033d698b8b03 Mon Sep 17 00:00:00 2001 From: Pjotr Prins Date: Sun, 29 May 2016 16:51:45 +0000 Subject: Added JOSS paper --- doc/joss/2016/paper.bib | 36 ++++++++++++++++++++ doc/joss/2016/paper.json | 23 +++++++++++++ doc/joss/2016/paper.md | 84 +++++++++++++++++++++++++++++++++++++++++++++++ doc/joss/2016/qtl.png | Bin 0 -> 146924 bytes doc/joss/2016/qtl2.png | Bin 0 -> 375505 bytes 5 files changed, 143 insertions(+) create mode 100644 doc/joss/2016/paper.bib create mode 100644 doc/joss/2016/paper.json create mode 100644 doc/joss/2016/paper.md create mode 100644 doc/joss/2016/qtl.png create mode 100644 doc/joss/2016/qtl2.png (limited to 'doc/joss/2016') diff --git a/doc/joss/2016/paper.bib b/doc/joss/2016/paper.bib new file mode 100644 index 00000000..73a88227 --- /dev/null +++ b/doc/joss/2016/paper.bib @@ -0,0 +1,36 @@ +@article{WGCNA:2008, + author = {Langfelder, P. and Horvath, S.}, + title = {{WGCNA: an R package for weighted correlation network analysis}}, + journal = {BMC Bioinformatics}, + year = {2008}, + volume = {9}, + pages = {559}, + doi = {10.1186/1471-2105-9-559}, + url = {http://www.ncbi.nlm.nih.gov/pubmed/19114008}, + abstract = {BACKGROUND: Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. RESULTS: The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. CONCLUSION: The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.} +} + +@article{Wang:2016, + author = {Wang, X. and Pandey, A. K. and Mulligan, M. K. and Williams, E. G. and Mozhui, K. and Li, Z. and Jovaisaite, V. and Quarles, L. D. and Xiao, Z. and Huang, J. and Capra, J. A. and Chen, Z. and Taylor, W. L. and Bastarache, L. and Niu, X. and Pollard, K. S. and Ciobanu, D. C. and Reznik, A. O. and Tishkov, A. V. and Zhulin, I. B. and Peng, J. and Nelson, S. F. and Denny, J. C. and Auwerx, J. and Lu, L. and Williams, R. W.}, + title = {{Joint mouse-human phenome-wide association to test gene function and disease risk}}, + journal = {Nat Commun}, + year = {2016}, + volume = {7}, + pages = {10464}, + doi = {10.1038/ncomms10464}, + url = {http://www.ncbi.nlm.nih.gov/pubmed/26833085}, + abstract = {Phenome-wide association is a novel reverse genetic strategy to analyze genome-to-phenome relations in human clinical cohorts. Here we test this approach using a large murine population segregating for approximately 5 million sequence variants, and we compare our results to those extracted from a matched analysis of gene variants in a large human cohort. For the mouse cohort, we amassed a deep and broad open-access phenome consisting of approximately 4,500 metabolic, physiological, pharmacological and behavioural traits, and more than 90 independent expression quantitative trait locus (QTL), transcriptome, proteome, metagenome and metabolome data sets--by far the largest coherent phenome for any experimental cohort (www.genenetwork.org). We tested downstream effects of subsets of variants and discovered several novel associations, including a missense mutation in fumarate hydratase that controls variation in the mitochondrial unfolded protein response in both mouse and Caenorhabditis elegans, and missense mutations in Col6a5 that underlies variation in bone mineral density in both mouse and human.} +} + +@article{Lippert:2011, + author = {Lippert, C. and Listgarten, J. and Liu, Y. and Kadie, C. M. and Davidson, R. I. and Heckerman, D.}, + title = {{FaST linear mixed models for genome-wide association studies}}, + journal = {Nat Methods}, + year = {2011}, + volume = {8}, + number = {10}, + pages = {833-835}, + doi = {10.1038/nmeth.1681}, + 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/).} +} diff --git a/doc/joss/2016/paper.json b/doc/joss/2016/paper.json new file mode 100644 index 00000000..c3c02156 --- /dev/null +++ b/doc/joss/2016/paper.json @@ -0,0 +1,23 @@ +{ + "@context": "https://raw.githubusercontent.com/mbjones/codemeta/master/codemeta.jsonld", + "@type": "Code", + "author": [ + { + "@id": "0000-0002-9623-3401", + "@type": "Person", + "email": "jakevdp@uw.edu", + "name": "Jake VanderPlas", + "affiliation": "University of Washington eScience Institute" + } + ], + "identifier": "https://zenodo.org/record/50995#.Vyp9DBUrJBw", + "codeRepository": "http://github.com/jakevdp/mst_clustering", + "datePublished": "2016-05-04", + "dateModified": "2016-05-04", + "dateCreated": "2016-05-04", + "description": "Clustering via Euclidean Minimum Spanning Trees", + "keywords": "machine learning", + "license": "BSD", + "title": "mst_clustering", + "version": "v1.0" +} diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md new file mode 100644 index 00000000..81ec2b72 --- /dev/null +++ b/doc/joss/2016/paper.md @@ -0,0 +1,84 @@ +--- +title: 'GeneNetwork: framework for web-based genetics' +tags: + - bioinformatics + - genetics + - genomics +authors: + - name: Zachary Sloan + orcid: 0000-0002-8099-1363 + affiliation: University of Tennessee Health Science Center, USA + - name: Danny Arends + orcid: 0000-0001-8738-0162 + affiliation: Humboldt Universityl, Berlin, Germany + - name: Karl W. Broman + orcid: 0000-0002-4914-6671 + affiliation: University of Wisconsin, USA + - name: Arthur Centeno + orcid: 0000-0003-3142-2081 + affiliation: University of Tennessee Health Science Center, USA + - name: Nick Furlotte + orcid: ? + - name: Harm Nijveen + orcid: 0000-0002-9167-4945 + affiliation: Wageningen University, The Netherlands + - name: Lei Yan + orcid: 0000-0001-5259-3379 + affiliation: University of Tennessee Health Science Center, USA + - name: Xiang Zhou + orcid: 0000-0002-4331-7599 + affiliation: University of Michigan + - name: Robert W. WIlliams + orcid: 0000-0001-8924-4447 + affiliation: University of Tennessee Health Science Center, USA + - name: Pjotr Prins + orcid: orcid.org/0000-0002-8021-9162 + affiliation: University Medical Center Utrecht, The Netherlands + affiliation: University of Tennessee Health Science Center, USA +date: 29 May 2016 +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 +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 +are included from R/qtlcharts and presentation-ready figures can be +generated. Recently we have added functionality for phenotype +correlation [@Wang:2016] and network analysis [@WGCNA:2008]. + +-![Mouse LMM mapping example](qtl2.png) + +GN is written in python and javascript and contains a rich set of +tools and libraries that can be written in any computer language. A +full list of included software can be found in +[guix-bioinformatics](https://github.com/genenetwork/guix-bioinformatics/blob/master/gn/packages/genenetwork.scm). To +make it easy to install GN locally in a byte reproducible way, +including all dependencies and a 2GB MySQL test database (the full +database is 160GB and growing), GN is packaged with +[GNU Guix](https://www.gnu.org/software/guix/), as described +[here](https://github.com/genenetwork/genenetwork2/blob/staging/doc/README.org). +GNU Guix deployment makes it feasible to deploy and rebrand GN +anywhere. + +# Future work + +More mapping tools will be added, including support for Genome-wide +Efficient Mixed Model Association (GEMMA). The +[Biodiallance genome browser](http://www.biodalliance.org/) is being +added as a Google Summer of Code project with special tracks related +to QTL mapping and network analysis. Faster LMM solutions are being +worked on, including GPU support. + +A REST interface is being added so that data can be uploaded to a +server, analysis run remotely on high performance hardware, and +results downloaded and used for further analysis. This feature will +allow biologist-programmers to use R and python on their computer and +execute computations on GN enabled servers. + +# References diff --git a/doc/joss/2016/qtl.png b/doc/joss/2016/qtl.png new file mode 100644 index 00000000..995a2739 Binary files /dev/null and b/doc/joss/2016/qtl.png differ diff --git a/doc/joss/2016/qtl2.png b/doc/joss/2016/qtl2.png new file mode 100644 index 00000000..e0b684ef Binary files /dev/null and b/doc/joss/2016/qtl2.png differ -- cgit v1.2.3 From 42f7955c8619ba43766a3b13626d554c2f3d8399 Mon Sep 17 00:00:00 2001 From: Pjotr Prins Date: Sun, 29 May 2016 16:57:28 +0000 Subject: JOSS: add MQM citation and fix typo --- doc/joss/2016/paper.bib | 14 ++++++++++++++ doc/joss/2016/paper.md | 8 ++++---- 2 files changed, 18 insertions(+), 4 deletions(-) (limited to 'doc/joss/2016') 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 -- cgit v1.2.3 From 76a15627f15f9612702cc135747bb383c5a776b1 Mon Sep 17 00:00:00 2001 From: Arfon Smith Date: Sun, 29 May 2016 21:16:35 -0500 Subject: Fixing paper metadata --- doc/joss/2016/paper.md | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) (limited to 'doc/joss/2016') diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index 42fcd500..38db3ca7 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -18,7 +18,6 @@ authors: orcid: 0000-0003-3142-2081 affiliation: University of Tennessee Health Science Center, USA - name: Nick Furlotte - orcid: ? - name: Harm Nijveen orcid: 0000-0002-9167-4945 affiliation: Wageningen University, The Netherlands @@ -33,8 +32,7 @@ authors: affiliation: University of Tennessee Health Science Center, USA - name: Pjotr Prins orcid: orcid.org/0000-0002-8021-9162 - affiliation: University Medical Center Utrecht, The Netherlands - affiliation: University of Tennessee Health Science Center, USA + affiliation: University Medical Center Utrecht, The Netherlands, University of Tennessee Health Science Center, USA date: 29 May 2016 bibliography: paper.bib --- -- cgit v1.2.3 From 7cc0899e46d2a5538b2646191daba6987d9ed16f Mon Sep 17 00:00:00 2001 From: DannyArends Date: Mon, 30 May 2016 09:39:00 +0200 Subject: Fixing my affiliation --- doc/joss/2016/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'doc/joss/2016') diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index 38db3ca7..bc63e835 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -10,7 +10,7 @@ authors: affiliation: University of Tennessee Health Science Center, USA - name: Danny Arends orcid: 0000-0001-8738-0162 - affiliation: Humboldt Universityl, Berlin, Germany + affiliation: Humboldt University, Berlin, Germany - name: Karl W. Broman orcid: 0000-0002-4914-6671 affiliation: University of Wisconsin, USA -- cgit v1.2.3 From 1912e8dd100cf97bd706e8c475dc9d09c1c3e56f Mon Sep 17 00:00:00 2001 From: DannyArends Date: Mon, 30 May 2016 09:40:55 +0200 Subject: Removing paper.json (unneeded) --- doc/joss/2016/paper.json | 23 ----------------------- 1 file changed, 23 deletions(-) delete mode 100644 doc/joss/2016/paper.json (limited to 'doc/joss/2016') diff --git a/doc/joss/2016/paper.json b/doc/joss/2016/paper.json deleted file mode 100644 index c3c02156..00000000 --- a/doc/joss/2016/paper.json +++ /dev/null @@ -1,23 +0,0 @@ -{ - "@context": "https://raw.githubusercontent.com/mbjones/codemeta/master/codemeta.jsonld", - "@type": "Code", - "author": [ - { - "@id": "0000-0002-9623-3401", - "@type": "Person", - "email": "jakevdp@uw.edu", - "name": "Jake VanderPlas", - "affiliation": "University of Washington eScience Institute" - } - ], - "identifier": "https://zenodo.org/record/50995#.Vyp9DBUrJBw", - "codeRepository": "http://github.com/jakevdp/mst_clustering", - "datePublished": "2016-05-04", - "dateModified": "2016-05-04", - "dateCreated": "2016-05-04", - "description": "Clustering via Euclidean Minimum Spanning Trees", - "keywords": "machine learning", - "license": "BSD", - "title": "mst_clustering", - "version": "v1.0" -} -- cgit v1.2.3 From 7e3e07c1e3fb150a2d37088a8b250ef028c162ba Mon Sep 17 00:00:00 2001 From: DannyArends Date: Mon, 30 May 2016 09:42:01 +0200 Subject: Consistency in the orchid IDs --- doc/joss/2016/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'doc/joss/2016') diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index bc63e835..02fc6a65 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -31,7 +31,7 @@ authors: orcid: 0000-0001-8924-4447 affiliation: University of Tennessee Health Science Center, USA - name: Pjotr Prins - orcid: orcid.org/0000-0002-8021-9162 + orcid: 0000-0002-8021-9162 affiliation: University Medical Center Utrecht, The Netherlands, University of Tennessee Health Science Center, USA date: 29 May 2016 bibliography: paper.bib -- cgit v1.2.3 From e241d27ccd3302632fec52043fc8b42125f4cfd7 Mon Sep 17 00:00:00 2001 From: Pjotr Prins Date: Thu, 2 Jun 2016 09:40:22 +0200 Subject: Paper: addressing https://github.com/openjournals/joss-reviews/issues/25 1st par: "experimental data" could be fleshed out in 2-3 words for the biologist reader (is it SNPs, microarray data, NGS, Y2H or manually counted individuals?) --- doc/joss/2016/paper.md | 19 +++++++++++-------- 1 file changed, 11 insertions(+), 8 deletions(-) (limited to 'doc/joss/2016') diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index 02fc6a65..a3eb4477 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -41,14 +41,17 @@ bibliography: paper.bib 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 -are included from R/qtlcharts and presentation-ready figures can be -generated. Recently we have added functionality for phenotype -correlation [@Wang:2016] and network analysis [@WGCNA:2008]. +to upload high-throughput experimental data, such as expression data +from microarrays and RNA-seq, and also `classic' phenotypes, such as +disease phenotypes. These phenotypes can be mapped interactively +against genotypes using embedded tools, such as R/QTL [@Arends:2010] +mapping, interval mapping for model organisms and pylmm; an +implementation of FaST-LMM [@Lippert:2011] which is more suitable for +human populations and outbred crosses, such as the mouse diversity +outcross. Interactive D3 graphics are included from R/qtlcharts and +presentation-ready figures can be generated. Recently we have added +functionality for phenotype correlation [@Wang:2016] and network +analysis [@WGCNA:2008]. -![Mouse LMM mapping example](qtl2.png) -- cgit v1.2.3 From 9669b09bdd8885acae07e05cb878e575b1b2c6e1 Mon Sep 17 00:00:00 2001 From: Pjotr Prins Date: Thu, 2 Jun 2016 09:43:58 +0200 Subject: Paper: addressing https://github.com/openjournals/joss-reviews/issues/25 2nd par: "can be found in ___ guix-bioinformatics", please insert 'the article', 'the package', 'the lab fridge labeled'.. whichever is aproppriate ;-) --- doc/joss/2016/paper.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) (limited to 'doc/joss/2016') diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index a3eb4477..62daf177 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -57,7 +57,8 @@ analysis [@WGCNA:2008]. GN is written in python and javascript and contains a rich set of tools and libraries that can be written in any computer language. A -full list of included software can be found in +full list of included software can be found in the package named +`genenetwork2' and defined in [guix-bioinformatics](https://github.com/genenetwork/guix-bioinformatics/blob/master/gn/packages/genenetwork.scm). To make it easy to install GN locally in a byte reproducible way, including all dependencies and a 2GB MySQL test database (the full -- cgit v1.2.3 From 3788a3ae75d8260c167818786aeeeb20b22fb305 Mon Sep 17 00:00:00 2001 From: Pjotr Prins Date: Thu, 2 Jun 2016 09:45:41 +0200 Subject: Paper: addressing https://github.com/openjournals/joss-reviews/issues/25 last par: "Python" is spelled with a capital 'P' --- doc/joss/2016/paper.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) (limited to 'doc/joss/2016') diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index 62daf177..9ac323d2 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -80,7 +80,7 @@ worked on, including GPU support. A REST interface is being added so that data can be uploaded to a server, analysis run remotely on high performance hardware, and results downloaded and used for further analysis. This feature will -allow biologist-programmers to use R and python on their computer and +allow biologist-programmers to use R and Python on their computer and execute computations on GN enabled servers. # References -- cgit v1.2.3 From fbd60cd5fccdd6e664865a74fd1a4433fc1ec55d Mon Sep 17 00:00:00 2001 From: Pjotr Prins Date: Wed, 8 Jun 2016 10:23:53 +0000 Subject: JOSS: added orcid for Nick Furlotte --- doc/joss/2016/paper.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) (limited to 'doc/joss/2016') diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index 9ac323d2..6b640836 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -17,7 +17,8 @@ authors: - name: Arthur Centeno orcid: 0000-0003-3142-2081 affiliation: University of Tennessee Health Science Center, USA - - name: Nick Furlotte + - name: Nicholas Furlotte + orcid: 0000-0002-9096-6276 - name: Harm Nijveen orcid: 0000-0002-9167-4945 affiliation: Wageningen University, The Netherlands -- cgit v1.2.3 From 47cf69f2f2fc8243b94f17387547c1fc12fb60ab Mon Sep 17 00:00:00 2001 From: Pjotr Prins Date: Thu, 9 Jun 2016 09:07:34 +0000 Subject: Docs: add SVG graph --- doc/README.org | 2 +- doc/joss/2016/paper.md | 2 ++ 2 files changed, 3 insertions(+), 1 deletion(-) (limited to 'doc/joss/2016') diff --git a/doc/README.org b/doc/README.org index bcc8a65e..681357ef 100644 --- a/doc/README.org +++ b/doc/README.org @@ -24,7 +24,7 @@ * Introduction -Large system deployments can get very complex. In this document we +Large system deployments can get very [[http://biobeat.org/gn2.svg][complex]]. In this document we explain the GeneNetwork version 2 (GN2) reproducible deployment system which is based on GNU Guix (see also Pjotr's [[https://github.com/pjotrp/guix-notes/blob/master/README.md][Guix-notes]]). The Guix system can be used to install GN with all its files and dependencies. diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index 6b640836..7c6f76cc 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -69,6 +69,8 @@ database is 160GB and growing), GN is packaged with GNU Guix deployment makes it feasible to deploy and rebrand GN anywhere. +-![GN2 dependency graph](http://biobeat.org/gn2.svg) + # Future work More mapping tools will be added, including support for Genome-wide -- cgit v1.2.3 From ed482493f2fa907632bacffac7a1938e9656b0d5 Mon Sep 17 00:00:00 2001 From: Pjotr Prins Date: Thu, 9 Jun 2016 09:37:30 +0000 Subject: Doc: moved graph into README --- doc/README.org | 5 +++++ doc/joss/2016/paper.md | 2 -- 2 files changed, 5 insertions(+), 2 deletions(-) (limited to 'doc/joss/2016') diff --git a/doc/README.org b/doc/README.org index 681357ef..a36d04bb 100644 --- a/doc/README.org +++ b/doc/README.org @@ -34,6 +34,11 @@ main Guix package tree and that of the Genenetwork package tree. Current supported versions can be found as the SHA values of 'gn-latest' branches of [[https://github.com/genenetwork/guix-bioinformatics/tree/gn-latest][Guix bioinformatics]] and [[https://github.com/genenetwork/guix/tree/gn-latest][GNU Guix main]]. +Graph of all runtime dependencies as installed by GNU Guix. + +-![GN2 dependency graph](http://biobeat.org/gn2.svg) + + * Quick installation recipe This is a recipe for quick and dirty installation of GN2. For diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index 7c6f76cc..6b640836 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -69,8 +69,6 @@ database is 160GB and growing), GN is packaged with GNU Guix deployment makes it feasible to deploy and rebrand GN anywhere. --![GN2 dependency graph](http://biobeat.org/gn2.svg) - # Future work More mapping tools will be added, including support for Genome-wide -- cgit v1.2.3 From 75c7a0828625e3aaf6326e91fadf20df96207fc3 Mon Sep 17 00:00:00 2001 From: Pjotr Prins Date: Thu, 16 Jun 2016 17:15:39 +0000 Subject: JOSS: fix typo and amend URL --- doc/joss/2016/paper.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) (limited to 'doc/joss/2016') diff --git a/doc/joss/2016/paper.md b/doc/joss/2016/paper.md index 6b640836..12b3b5d0 100644 --- a/doc/joss/2016/paper.md +++ b/doc/joss/2016/paper.md @@ -28,7 +28,7 @@ authors: - name: Xiang Zhou orcid: 0000-0002-4331-7599 affiliation: University of Michigan - - name: Robert W. WIlliams + - name: Robert W. Williams orcid: 0000-0001-8924-4447 affiliation: University of Tennessee Health Science Center, USA - name: Pjotr Prins @@ -65,7 +65,7 @@ make it easy to install GN locally in a byte reproducible way, including all dependencies and a 2GB MySQL test database (the full database is 160GB and growing), GN is packaged with [GNU Guix](https://www.gnu.org/software/guix/), as described -[here](https://github.com/genenetwork/genenetwork2/blob/staging/doc/README.org). +[here](https://github.com/genenetwork/genenetwork2/blob/master/doc/README.org). GNU Guix deployment makes it feasible to deploy and rebrand GN anywhere. -- cgit v1.2.3