Add version flag to content front matter and environments. Resolves #697

.

content/about/dcp-roadmap.md → content/about/platform/dcp-roadmap.md

@@ -27,11 +27,11 @@ Aim 5. Create standards for the community to use to describe single-cell experim
 
 To support initial efforts in atlas development, the DCP team is focusing on describing experimental design, collecting and harmonizing data, and assuring data integrity, serving both the biologists generating single-cell data and the computational biologists needing to access it. 
 
-![Practice_table](./_images/Practice_table.png)
+![Practice_table](../_images/Practice_table.png)
 
 # DCP Quarterly Roadmap
 
 The DCP Quarterly Roadmap lists the in progress and upcoming activities for achieving the DCP Strategic Aims as they relate to our current role in atlas development.
 
-![Practice_table](./_images/Practice_table.png)
+![Practice_table](../_images/Practice_table.png)
 

content/about/about-the-dcp.md → content/about/platform/dcp.md

@@ -1,5 +1,4 @@
 ---
-path: "/about/platform/dcp"
 date: "2018-05-03"
 title: "About the Data Coordination Platform"
 draft: false

content/about/about-the-hca.md → content/about/platform/hca.md

@@ -1,5 +1,4 @@
 ---
-path: "/about/platform/hca"
 date: "2018-05-03"
 title: "About the Human Cell Atlas"
 ---

content/analyze/methods/methods-packages.md

@@ -4,12 +4,12 @@ date: "2018-05-03"
 title: "Methods Packages"
 componentName: "analyze"
 linked:
-    - ./infercnv.md
-    - ./magic.md
-    - ./phate.md
-    - ./sc3.md
-    - ./slingshot.md
-    - ./stream.md
+    - ./methods-packages/infer.md
+    - ./methods-packages/magic.md
+    - ./methods-packages/phate.md
+    - ./methods-packages/sc3.md
+    - ./methods-packages/slingshot.md
+    - ./methods-packages/stream.md
 ---
 
 #  Methods Packages

content/analyze/methods/infercnv.md → content/analyze/methods/methods-packages/infer.md

@@ -12,15 +12,15 @@ componentName: "analysisDetail"
 
 [![Build Status](https://travis-ci.com/broadinstitute/infercnv.svg?branch=master )](https://travis-ci.com/broadinstitute/infercnv)
 
-[![InferCNV](../_images/methods/infercnv_logo.png)](https://github.com/broadinstitute/infercnv)
+[![InferCNV](../../_images/methods/infercnv_logo.png)](https://github.com/broadinstitute/infercnv)
 
 [InferCNV](https://github.com/broadinstitute/infercnv) is used to explore tumor single cell RNA-Seq data to identify evidence for large-scale chromosomal copy number variations, such as gains or deletions of entire chromosomes or large segments of chromosomes. This is done by exploring expression intensity of genes across positions of the genome in comparison to a set of reference 'normal' cells. A heatmap is generated illustrating the relative expression intensities across each chromosome, and it often becomes readily apparent as to which regions of the genome are over-abundant or less-abundant as compared to normal cells.
 
 InferCNV provides access to several residual expression filters to explore minimizing noise and further revealing the signal supporting CNV. Additionally, inferCNV includes methods to predict CNV regions and define cell clusters according to patterns of heterogeneity.
 
 InferCNV is one component of the TrinityCTAT toolkit focused on leveraging the use of RNA-Seq to better understand cancer transcriptomes.
 
-[![inferCNV](../_images/methods/infercnv_screenshot.png)](https://github.com/broadinstitute/infercnv)
+[![inferCNV](../../_images/methods/infercnv_screenshot.png)](https://github.com/broadinstitute/infercnv)
 
 ## Use
 

content/analyze/methods/stream.md → content/analyze/methods/methods-packages/stream.md

@@ -12,11 +12,11 @@ componentName: "analysisDetail"
 
 [![Build Status](https://travis-ci.org/pinellolab/STREAM.svg)](https://travis-ci.org/pinellolab/STREAM)
 
-[![STREAM](../_images/methods/stream_logo.png)](http://stream.pinellolab.org/)
+[![STREAM](../../_images/methods/stream_logo.png)](http://stream.pinellolab.org/)
 
 [STREAM](https://bioconda.github.io/recipes/stream/README.html) is an interactive computational pipeline for reconstructing complex cellular developmental trajectories from sc-qPCR, scRNA-seq or scATAC-seq data.
 
-[![STREAM](../_images/methods/stream_screenshot.png)](http://stream.pinellolab.org/)
+[![STREAM](../../_images/methods/stream_screenshot.png)](http://stream.pinellolab.org/)
 
 ## Usage
 

content/analyze/portals/analysis-portals.md

@@ -4,17 +4,17 @@ date: "2018-05-03"
 title: "Analysis Portals"
 componentName: "analyze"
 linked:
-    - ./asap.md
-    - ./bioturing-browser.md
-    - ./cellxgene.md
-    - ./cytoscape.md
-    - ./dnastack.md
-    - ./hca-galaxy-instance.md
-    - ./single-cell-expression-atlas.md
-    - ./single-cell-portal.md
-    - ./genepattern-notebook.md
-    - ./ucsc-cell-browser.md
-    - ./ucsc-xena.md
+    - ./analysis-portals/asap.md
+    - ./analysis-portals/bioturing-browser.md
+    - ./analysis-portals/cellxgene.md
+    - ./analysis-portals/cytoscape.md
+    - ./analysis-portals/dnastack.md
+    - ./analysis-portals/hca-galaxy-instance.md
+    - ./analysis-portals/single-cell-expression-atlas.md
+    - ./analysis-portals/single-cell-portal.md
+    - ./analysis-portals/genepattern-notebook-environment.md
+    - ./analysis-portals/ucsc-cell-browser.md
+    - ./analysis-portals/ucsc-xena.md
 ---
 
 # Analysis Portals

content/analyze/portals/asap.md → content/analyze/portals/analysis-portals/asap.md

@@ -11,7 +11,7 @@ componentName: "analysisDetail"
 
 [ASAP](https://asap.epfl.ch/) allows the user to perform custom analyses and compare algorithms for each step of the single cell or bulk RNA-seq analysis pipeline post genome alignment via an intuitive web interface (Gardeux et al., Bioinformatics, 2017). These steps include parsing, filtering, and normalization of the input gene expression matrix, visual (2D and 3D) representation, differential expression, clustering, heatmaps, trajectory inference and functional enrichment analyses to characterize novel cell clusters, specific cell types, or differentiation processes. Thus, ASAP has been developed to lower the bioinformatic entry level to single cell experiments and to catalyze collaborations between computational biologists and experimentalists via an easy-to-use data interaction portal.
 
-[![ASAP](../_images/portals/asap.png)](https://asap.epfl.ch)
+[![ASAP](../../_images/portals/asap.png)](https://asap.epfl.ch)
 
 ## Contact
 Vincent Gardeux ([Vincent.Gardeux@epfl.ch](mailto:Vincent.Gardeux@epfl.ch))\

content/analyze/portals/bioturing-browser.md → content/analyze/portals/analysis-portals/bioturing-browser.md

@@ -11,7 +11,7 @@ componentName: "analysisDetail"
 
 [BioTuring Single Cell Browser](https://bioturing.com/product/bbrowser) combines modern data visualization techniques, statistical machine learning toolboxes, and a rich knowledge base to create a unique platform for single cell data analytics.
 
-[![BioTuring Single Cell Browser](../_images/portals/bioturing-browser.png)](https://bioturing.com/product/bbrowser)
+[![BioTuring Single Cell Browser](../../_images/portals/bioturing-browser.png)](https://bioturing.com/product/bbrowser)
 
 ## Contact
 Son Pham ([sonpham@bioturing.com](mailto:sonpham@bioturing.com))

content/analyze/portals/cellxgene.md → content/analyze/portals/analysis-portals/cellxgene.md

@@ -11,7 +11,7 @@ componentName: "analysisDetail"
 
 [cellxgene](https://github.com/chanzuckerberg/cellxgene) is an interactive, performant explorer for single cell transcriptomics data - an open-source experiment in how to bring powerful tools from modern web development to visualize and explore large single-cell transcriptomics datasets. cellxgene hopes to both enable scientists to explore their data and to equip developers with scalable, reusable patterns and frameworks for visualizing large scientific datasets. Features will include scalable visualization of at least 1 million cells, interactive exploration via performant cross-filtering and comparison, and a flexible API that supports a range of existing analysis packages (e.g. scanpy) for backend computational tasks integrated with client-side visualization.
 
-[![cellxgene](../_images/portals/cellxgene.png)](https://github.com/chanzuckerberg/cellxgene)
+[![cellxgene](../../_images/portals/cellxgene.png)](https://github.com/chanzuckerberg/cellxgene)
 
 ## Contact
 Fiona Griffin ([fiona.griffin@chanzuckerberg.com](mailto:fiona.griffin@chanzuckerberg.com))

content/analyze/portals/cytoscape.md → content/analyze/portals/analysis-portals/cytoscape.md

@@ -15,7 +15,7 @@ Cytoscape's core distribution provides a basic set of features for data integrat
 
 Apps may be developed by anyone using the Cytoscape open API based on Java™ technology and App community development is encouraged. Most of the Apps are freely available from Cytoscape App Store.  Cytoscape is being extended through apps and core features to search, extract, visualize, and analyze data from the Human Cell Atlas, with a focus on network and pathway analysis.
 
-[![Cytoscape](../_images/portals/cytoscape.png)](http://www.cytoscape.org)
+[![Cytoscape](../../_images/portals/cytoscape.png)](http://www.cytoscape.org)
 
 ## Contact
 [Cytoscape Helpdesk](https://groups.google.com/forum/#!forum/cytoscape-helpdesk) ([cytoscape-helpdesk@googlegroups.com](mailto:cytoscape-helpdesk@googlegroups.com))

content/analyze/portals/dnastack.md → content/analyze/portals/analysis-portals/dnastack.md

@@ -10,7 +10,7 @@ componentName: "analysisDetail"
 
 [DNAstack](https://www.dnastack.com) is a cloud platform for bioinformatics based on open standards like Workflow Description Language and Common Workflow Language.
 
-[![DNAstack](../_images/portals/dnastack.jpg)](https://www.dnastack.com)
+[![DNAstack](../../_images/portals/dnastack.jpg)](https://www.dnastack.com)
 
 ## Contact
 General information ([info@dnastack.com](mailto:info@dnastack.com))

content/analyze/portals/genepattern-notebook.md → content/analyze/portals/analysis-portals/genepattern-notebook-environment.md

@@ -11,7 +11,7 @@ componentName: "analysisDetail"
 
 [GenePattern Notebook](http://www.genepattern-notebook.org) integrates the popular Jupyter Notebook platform, which interleaves text, graphics, and code, with the hundreds of genomic analyses available in the GenePattern platform, providing a workspace for reproducible research and open science to all researchers, regardless of their programming experience. The environment allows researchers to create, share, and publish detailed descriptions of their work, including the executable analyses, making it easy for others to understand it and adapt it to their own research.
 
-[![GenePattern Notebook](../_images/portals/genepattern-notebook.png)](http://www.genepattern-notebook.org)
+[![GenePattern Notebook](../../_images/portals/genepattern-notebook.png)](http://www.genepattern-notebook.org)
 
 ## Contact
 Genepattern Team ([genepattern-team@broadinstitute.org](mailto:genepattern-team@broadinstitute.org))

content/analyze/portals/hca-galaxy-instance.md → content/analyze/portals/analysis-portals/hca-galaxy-instance.md

@@ -14,7 +14,7 @@ It also includes facilities to import matrix data from the Human Cell Atlas and
 The clustering workflow for the release 6 of EBI Single Cell Expression Atlas are reproducible through this portal.
 The portal runs as part of the larger usegalaxy.eu infrastructure and has access to thousands of cores and terabytes of RAM and storage, kindly hosted by the U. of Freiburg, den.bi and Elixir.
 
-[![Human Cell Atlas Galaxy Instance](../_images/portals/hca-galaxy-instance.png)](https://humancellatlas.usegalaxy.eu)
+[![Human Cell Atlas Galaxy Instance](../../_images/portals/hca-galaxy-instance.png)](https://humancellatlas.usegalaxy.eu)
 
 ## Contact
 Website: [https://www.ebi.ac.uk/support/gxasc](https://www.ebi.ac.uk/support/gxasc)\

content/analyze/portals/single-cell-expression-atlas.md → content/analyze/portals/analysis-portals/single-cell-expression-atlas.md

@@ -11,7 +11,7 @@ componentName: "analysisDetail"
 
 [Single Cell Expression Atlas](https://www.ebi.ac.uk/gxa/sc/home) supports research in single cell transcriptomics. The Atlas annotates publicly available single cell RNA-Seq experiments with ontology identifiers and re-analyses them using standardised pipelines available through iRAP, our RNA-Seq analysis toolkit. The browser enables visualisation of clusters of cells, their annotations and supports searches for gene expression within and across studies.
 
-[![Single Cell Expression Atlas](../_images/portals/single-cell-expression-atlas.png)](https://www.ebi.ac.uk/gxa/sc/home)
+[![Single Cell Expression Atlas](../../_images/portals/single-cell-expression-atlas.png)](https://www.ebi.ac.uk/gxa/sc/home)
 
 ## Contact
 Website: [https://www.ebi.ac.uk/support/gxasc](https://www.ebi.ac.uk/support/gxasc)\

content/analyze/portals/single-cell-portal.md → content/analyze/portals/analysis-portals/single-cell-portal.md

@@ -15,7 +15,7 @@ componentName: "analysisDetail"
 3. centralizing downloadable data, visualizations, and analysis to enable reproducible analysis;
 4. providing easy and secure sharing mechanisms to support all stages of scientific inquiry.
 
-[![Single Cell Portal](../_images/portals/single-cell-portal.png)](https://portals.broadinstitute.org/single_cell)
+[![Single Cell Portal](../../_images/portals/single-cell-portal.png)](https://portals.broadinstitute.org/single_cell)
 
 ## Contact
 Single Cell Portal team ([scp-support@broadinstitute.zendesk.com](mailto:scp-support@broadinstitute.zendesk.com))

content/analyze/portals/ucsc-cell-browser.md → content/analyze/portals/analysis-portals/ucsc-cell-browser.md

@@ -11,7 +11,7 @@ componentName: "analysisDetail"
 
 [UCSC Cell Browser](http://cells.ucsc.edu/) is a software tool for single cell RNA expression, a 2D viewer that shows cells as a dimensionality reduction plot with the expression data overlaid. The viewer allows a visual comparison of large single-cell datasets in 2D, overlaying metadata, marker gene levels and cell clustering information. This is useful when comparing single cell layout (dimensionality reduction) methods and batch correction methods.
 
-[![UCSC Cell Browser](../_images/portals/ucsc-cell-browser.png)](http://cells.ucsc.edu)
+[![UCSC Cell Browser](../../_images/portals/ucsc-cell-browser.png)](http://cells.ucsc.edu)
 
 ## Contact
 Max Haeussler ([max@soe.ucsc.edu](mailto:max@soe.ucsc.edu))

content/analyze/portals/ucsc-xena.md → content/analyze/portals/analysis-portals/ucsc-xena.md

@@ -13,7 +13,7 @@ componentName: "analysisDetail"
 
  Xena is built for performance, allowing you to dynamically view 1 million cells at a time. Xena downloads the latest HCA gene expression matrices available at [HCA Data Portal](/) and makes them available for visualization via our Visual Spreadsheet. 
 
-[![UCSC Xena single cell browser](../_images/portals/ucsc-xena.png)](https://singlecell.xenahubs.net)
+[![UCSC Xena single cell browser](../../_images/portals/ucsc-xena.png)](https://singlecell.xenahubs.net)
 
 Xena's Visual Spreadsheet is analogous to an office spreadsheet: it is a visual representation of a data grid where each column is a slice of genomic data (e.g. a gene or a set of genes' expression, inferred cell type, cell location), and each row is a single cell.
 

content/analyze/visualization/visualization-packages.md

@@ -4,10 +4,10 @@ date: "2018-05-03"
 title: "Visualization Packages"
 componentName: "analyze"
 linked:
-    - ./anatomogram.md
-    - ./ideogram.md
-    - ./igv.md
-    - ./morpheus.md
+    - ./visualization-packages/anatomogram.md
+    - ./visualization-packages/ideogram.md
+    - ./visualization-packages/igv.md
+    - ./visualization-packages/morpheus.md
 ---
 
 # Visualization Packages

content/analyze/visualization/anatomogram.md → content/analyze/visualization/visualization-packages/anatomogram.md

@@ -14,7 +14,7 @@ componentName: "analysisDetail"
 
 Anatomogram is an interactive component to display an anatomical view of an organism. Selected species support alternative views depending on their specific anatomical features (e.g. male, female and brain in mouse and human, flower and full plant in rice). It uses SVGs where shapes representing organism parts are annotated with ontology accessions that are the IDs the component uses to receive and send events through callbacks.
 
-[![Anatomogram](../_images/visualization/anatomogram.png)](https://gxa.github.io/anatomogram-demo)
+[![Anatomogram](../../_images/visualization/anatomogram.png)](https://gxa.github.io/anatomogram-demo)
 
 ## Install
 `npm install anatomogram`

content/analyze/visualization/ideogram.md → content/analyze/visualization/visualization-packages/ideogram.md

@@ -11,15 +11,15 @@ componentName: "analysisDetail"
 
 [![Build Status](https://travis-ci.org/eweitz/ideogram.svg?branch=master)](https://travis-ci.org/eweitz/ideogram)
 [![Coverage Status](https://coveralls.io/repos/github/eweitz/ideogram/badge.svg)](https://coveralls.io/github/eweitz/ideogram)
-[![Mashup](../_images/mashup.svg)](https://github.com/eweitz/ideogram/blob/master/examples/react/README.md#ideogram-in-react)
+[![Mashup](../../_images/mashup.svg)](https://github.com/eweitz/ideogram/blob/master/examples/react/README.md#ideogram-in-react)
 
 [Ideogram.js](https://eweitz.github.io/ideogram/) is a JavaScript library for chromosome visualization. 
 
 Ideogram supports drawing and animating genome-wide datasets for [human](https://eweitz.github.io/ideogram/human), [mouse](https://eweitz.github.io/ideogram/mouse), and [many other eukaryotes](https://eweitz.github.io/ideogram/eukaryotes).  The [Ideogram API](https://github.com/eweitz/ideogram/blob/master/api.md) for annotations supports [histograms](https://eweitz.github.io/ideogram/annotations-histogram), [heatmaps](https://eweitz.github.io/ideogram/annotations-heatmap), [overlays](https://eweitz.github.io/ideogram/annotations-overlaid), and points of arbitrary shape and color layered in [tracks](https://eweitz.github.io/ideogram/annotations-tracks). Ideogram can depict haploid, [diploid](https://eweitz.github.io/ideogram/ploidy-basic) or higher ploidy genomes (e.g. plants), as well as aneuploidy, [genetic recombination](https://eweitz.github.io/ideogram/ploidy-recombination), and [homologous features](https://eweitz.github.io/ideogram/homology-basic) between chromosomes. 
 
 Ideogram can be embedded as a [reusable component](https://github.com/eweitz/ideogram#usage) in any web page or application, and leverages D3.js and SVG to achieve fast, crisp client-side rendering. You can also integrate Ideogram with JavaScript frameworks like [Angular](https://github.com/eweitz/ideogram/tree/master/examples/angular), [React](https://github.com/eweitz/ideogram/tree/master/examples/react), and [Vue](https://github.com/eweitz/ideogram/tree/master/examples/vue), as well as data science platforms like [R](https://github.com/eweitz/ideogram/tree/master/examples/r) and [Jupyter Notebook](https://github.com/eweitz/ideogram/tree/master/examples/jupyter).
 
-[![Ideogram](../_images/visualization/ideogram.png)](https://eweitz.github.io/ideogram/annotations-histogram)
+[![Ideogram](../../_images/visualization/ideogram.png)](https://eweitz.github.io/ideogram/annotations-histogram)
 
 ## Install
 `npm install ideogram`

content/analyze/visualization/igv.md → content/analyze/visualization/visualization-packages/igv.md

@@ -10,11 +10,11 @@ componentName: "analysisDetail"
 ---
 
 [![Build Status](https://travis-ci.org/igvteam/igv.js.svg?branch=master)](https://travis-ci.org/igvteam/igv.js)
-[![Mashup](../_images/mashup.svg)](https://github.com/eweitz/igv.js-react/blob/master/README.md#igvjs-in-react)
+[![Mashup](../../_images/mashup.svg)](https://github.com/eweitz/igv.js-react/blob/master/README.md#igvjs-in-react)
 
 igv.js is an embeddable interactive genome visualization component based on the desktop Integrative Genomics Viewer (IGV).
 
-[![ivg](../_images/visualization/igv.png)](http://igv.org/web/release/2.2.0/examples/bam.html)
+[![ivg](../../_images/visualization/igv.png)](http://igv.org/web/release/2.2.0/examples/bam.html)
 
 ## Install
 `npm install igv`

content/analyze/visualization/morpheus.md → content/analyze/visualization/visualization-packages/morpheus.md

@@ -10,11 +10,11 @@ componentName: "analysisDetail"
 ---
 
 [![Build Status](https://travis-ci.org/cmap/morpheus.js.svg?branch=master)](https://travis-ci.org/cmap/morpheus.js)
-[![Mashup](../_images/mashup.svg)](https://github.com/eweitz/morpheus.js-react/blob/master/README.md#morpheusjs-in-react)
+[![Mashup](../../_images/mashup.svg)](https://github.com/eweitz/morpheus.js-react/blob/master/README.md#morpheusjs-in-react)
 
 Morpheus is versatile matrix visualization and analysis software. View your dataset as a heat map, then explore the interactive tools in Morpheus. Cluster, create new annotations, search, filter, sort, display charts, and more.
 
-[![Morpheus](../_images/visualization/morpheus.png)](https://software.broadinstitute.org/morpheus)
+[![Morpheus](../../_images/visualization/morpheus.png)](https://software.broadinstitute.org/morpheus)
 
 ## Install
 `npm install morpheus-app`

content/contribute/data/contributing-data-suitability.md → content/contribute/data/contributing-to-hca/contributing-data-suitability.md

@@ -10,7 +10,7 @@ The first phase of the HCA will profile tens of millions of human cells, isolate
 
 Currently, the HCA considers five criteria to assess the suitability of a dataset for building the Atlas. 
 
-![contribute](../_images/data-suitability.png)
+![contribute](../../_images/data-suitability.png)
 
 Each of the five criteria have the following statuses:
 

content/contribute/data/contributing-expect-prepare.md → content/contribute/data/contributing-to-hca/contributing-expect-prepare.md

@@ -8,7 +8,7 @@ title: "Data Submission Process"
 
 Once you are ready to submit your data, you will be supported by the Human Cell Atlas data wranglers. We currently use spreadsheets to collect metadata and a command-line tool to transfer the data files to our cloud infrastructure. 
 
-![contribute](../_images/contribute.png)
+![contribute](../../_images/contribute.png)
 
 In order to process your cellular resolution data, we will request the following information: