From 786f9a3aa69365b57f42174356bb9918951542db Mon Sep 17 00:00:00 2001 From: valosekj Date: Mon, 4 Sep 2023 19:10:35 -0400 Subject: [PATCH] Update PAM50-normalized-metrics release to r20230904 --- binder/postBuild | 2 +- content/index.ipynb | 4 ++-- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/binder/postBuild b/binder/postBuild index 798a3b9..18a891a 100644 --- a/binder/postBuild +++ b/binder/postBuild @@ -1,2 +1,2 @@ #!/bin/bash -git clone --depth 1 https://github.com/spinalcordtoolbox/PAM50-normalized-metrics.git content/analysis \ No newline at end of file +git clone --depth 1 https://github.com/spinalcordtoolbox/PAM50-normalized-metrics.git --branch r20230904 content/analysis \ No newline at end of file diff --git a/content/index.ipynb b/content/index.ipynb index 457b41d..5d50329 100644 --- a/content/index.ipynb +++ b/content/index.ipynb @@ -246,7 +246,7 @@ "## 3.2 Normalization\n", "\n", "

\n", - "The normalized morphometric measures saved as comma-separated value (CSV) files (one file per subject) are accessible in this GitHub repository: https://github.com/spinalcordtoolbox/PAM50-normalized-metrics/tree/r20230222 (release: r20230223). \n", + "The normalized morphometric measures saved as comma-separated value (CSV) files (one file per subject) are accessible in this GitHub repository: https://github.com/spinalcordtoolbox/PAM50-normalized-metrics/tree/r20230904 (release: r20230904). \n", "The normalization method is implemented in the Python programming language and is available through the SCT’s sct_process_segmentation as part of SCT v6.0 and higher.\n", "

\n", "\n", @@ -680,7 +680,7 @@ "# DATA AVAILABILITY STATEMENT\n", "\n", "

\n", - "In order to facilitate reproducibility and open science principles, all codes, processing scripts, and results are shared as open-source and freely available to the whole community. The anonymized and defaced spine-generic dataset is organized according to the BIDS standard and managed using git-annex in the following GitHub repository: https://github.com/spine-generic/data-multi-subject/tree/r20230223 (release: r20230223). The processing used to compute morphometric measures of individual subjects in the PAM50 template space is available in this GitHub repository: https://github.com/sct-pipeline/dcm-metric-normalization/blob/r20230222/scripts/process_data_spine-generic.sh (release: r20230223). The computed morphometric measures in CSV format are available in this GitHub repository: https://github.com/spinalcordtoolbox/PAM50-normalized-metrics/tree/r20230222 (release: r20230223). The normalization method is available through the sct_process_segmentation function as part of the Spinal Cord Toolbox (SCT) v6.0 and higher: https://github.com/spinalcordtoolbox/spinalcordtoolbox/tree/6.0. The interactive figures in this article were produced using code integrated with Jupyter Lab notebook and powered by Plotly (https://plotly.com).\n", + "In order to facilitate reproducibility and open science principles, all codes, processing scripts, and results are shared as open-source and freely available to the whole community. The anonymized and defaced spine-generic dataset is organized according to the BIDS standard and managed using git-annex in the following GitHub repository: https://github.com/spine-generic/data-multi-subject/tree/r20230223 (release: r20230223). The processing used to compute morphometric measures of individual subjects in the PAM50 template space is available in this GitHub repository: https://github.com/sct-pipeline/dcm-metric-normalization/blob/r20230222/scripts/process_data_spine-generic.sh (release: r20230223). The computed morphometric measures in CSV format are available in this GitHub repository: https://github.com/spinalcordtoolbox/PAM50-normalized-metrics/tree/r20230904 (release: r20230223). The normalization method is available through the sct_process_segmentation function as part of the Spinal Cord Toolbox (SCT) v6.0 and higher: https://github.com/spinalcordtoolbox/spinalcordtoolbox/tree/6.0. The interactive figures in this article were produced using code integrated with Jupyter Lab notebook and powered by Plotly (https://plotly.com).\n", "

\n" ] },