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[DOC] Reorganize RTD sidebar and add section to release drafter (#411)
* Move FAQ and Support up a level in the sidebar. * Add "Breaking Changes" section to release drafter. * Switch order of Support and FAQ pages on sidebar. * Update release-drafter.yml Removes breaking changes st we can cut new release and continue discussing this later * Update release-drafter.yml Add in missing space
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‎.github/release-drafter.yml‎

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template: |
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## Release Notes
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## Changes
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‎docs/faq.rst‎

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FAQ
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---
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ICA has failed to converge.
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```````````````````````````
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The TEDICA step may fail to converge if TEDPCA is either too strict
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(i.e., there are too few components) or too lenient (there are too many).
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In our experience, this may happen when preprocessing has not been applied to
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the data, or when improper steps have been applied to the data (e.g., distortion
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correction, rescaling, nuisance regression).
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If you are confident that your data have been preprocessed correctly prior to
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applying tedana, and you encounter this problem, please submit a question to `NeuroStars`_.
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I think that some BOLD ICA components have been misclassified as noise.
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```````````````````````````````````````````````````````````````````````
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``tedana`` allows users to manually specify accepted components when calling the pipeline.
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You can use the ``--manacc`` argument to specify the indices of components to accept.
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Why isn't v3.2 of the component selection algorithm supported in ``tedana``?
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````````````````````````````````````````````````````````````````````````````
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There is a lot of solid logic behind the updated version of the TEDICA component
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selection algorithm, first added to the original ME-ICA codebase `here`_ by Dr. Prantik Kundu.
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However, we (the ``tedana`` developers) have encountered certain difficulties
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with this method (e.g., misclassified components) and the method itself has yet
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to be validated in any papers, posters, etc., which is why we have chosen to archive
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the v3.2 code, with the goal of revisiting it when ``tedana`` is more stable.
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Anyone interested in using v3.2 may compile and install an earlier release (<=0.0.4) of ``tedana``.
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.. _here: https://bitbucket.org/prantikk/me-ica/commits/906bd1f6db7041f88cd0efcac8a74074d673f4f5
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.. _NeuroStars: https://neurostars.org
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.. _fMRIPrep: https://fmriprep.readthedocs.io
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.. _afni_proc.py: https://afni.nimh.nih.gov/pub/dist/doc/program_help/afni_proc.py.html

‎docs/index.rst‎

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analysis of multi-echo fMRI data; however, ``tedana`` now assumes that you're
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working with data which has been previously preprocessed.
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For a summary of multi-echo fMRI, which is the imaging technique ``tedana`` builds on,
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visit `Multi-echo fMRI`_.
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For a summary of multi-echo fMRI, which is the imaging technique ``tedana`` builds on,
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visit `Multi-echo fMRI`_.
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For a detailed procedure of how ``tedana`` analyzes the data from multi-echo fMRI,
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For a detailed procedure of how ``tedana`` analyzes the data from multi-echo fMRI,
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visit `Processing pipeline details`_.
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.. _ME-ICA: https://github.com/me-ica/me-ica
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usage
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approach
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outputs
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faq
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support
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contributing
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roadmap
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api

‎docs/support.rst‎

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.. _support_ref:
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Support and communication
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-------------------------
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All bugs, concerns and enhancement requests for this software can be submitted here: https://github.com/ME-ICA/tedana/issues.
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If you would like to ask a question about usage or tedana's outputs, please submit a question to `NeuroStars`_ with the ``multi-echo`` tag.
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All previous tedana-related questions are available under the `multi-echo tag`_.
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We will also attempt to archive certain common questions and associate answers in the Frequently Asked Questions (FAQ) page.
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.. _multi-echo tag: https://neurostars.org/tags/multi-echo
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.. _NeuroStars: https://neurostars.org

‎docs/usage.rst‎

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and the subsequent calculation of voxelwise T2* values will be distorted.
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See the description of ``tedana``'s :doc:`approach <\approach>` for more details
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on how T2* values are calculated.
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.. _support_ref:
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Support and communication
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-------------------------
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All bugs, concerns and enhancement requests for this software can be submitted here: https://github.com/ME-ICA/tedana/issues.
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If you would like to ask a question about usage or tedana's outputs, please submit a question to `NeuroStars`_ with the ``multi-echo`` tag.
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All previous tedana-related questions are available under the `multi-echo tag`_.
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We will also attempt to archive certain common questions and associate answers in the Frequently Asked Questions (FAQ) section below.
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.. _multi-echo tag: https://neurostars.org/tags/multi-echo
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FAQ
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---
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ICA has failed to converge.
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```````````````````````````
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The TEDICA step may fail to converge if TEDPCA is either too strict
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(i.e., there are too few components) or too lenient (there are too many).
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In our experience, this may happen when preprocessing has not been applied to
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the data, or when improper steps have been applied to the data (e.g., distortion
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correction, rescaling, nuisance regression).
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If you are confident that your data have been preprocessed correctly prior to
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applying tedana, and you encounter this problem, please submit a question to `NeuroStars`_.
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I think that some BOLD ICA components have been misclassified as noise.
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```````````````````````````````````````````````````````````````````````
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``tedana`` allows users to manually specify accepted components when calling the pipeline.
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You can use the ``--manacc`` argument to specify the indices of components to accept.
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Why isn't v3.2 of the component selection algorithm supported in ``tedana``?
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````````````````````````````````````````````````````````````````````````````
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There is a lot of solid logic behind the updated version of the TEDICA component
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selection algorithm, first added to the original ME-ICA codebase `here`_ by Dr. Prantik Kundu.
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However, we (the ``tedana`` developers) have encountered certain difficulties
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with this method (e.g., misclassified components) and the method itself has yet
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to be validated in any papers, posters, etc., which is why we have chosen to archive
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the v3.2 code, with the goal of revisiting it when ``tedana`` is more stable.
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Anyone interested in using v3.2 may compile and install an earlier release (<=0.0.4) of ``tedana``.
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.. _here: https://bitbucket.org/prantikk/me-ica/commits/906bd1f6db7041f88cd0efcac8a74074d673f4f5
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.. _NeuroStars: https://neurostars.org
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.. _fMRIPrep: https://fmriprep.readthedocs.io
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.. _afni_proc.py: https://afni.nimh.nih.gov/pub/dist/doc/program_help/afni_proc.py.html

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