@@ -18,7 +18,7 @@ primary focus of the library is to provide pre-built processes and processing se
1818technologies and made easily available to pipeline's developers through the ` nf-core `
1919framework.
2020
21- # WHY ? ` nf-neuro `
21+ # WHY ? ` nf-neuro ` <!-- omit in toc -->
2222
2323** Let's say you develop a pipeline for neuroimaging** . You want to make it the more _ efficient,_
2424_ reliable, reproducible_ and also be able to _ evaluate it_ and _ control the quality_ of its outputs.
@@ -30,7 +30,7 @@ closely aligned with [nf-core](), but we'll make you adapt to them slowly as you
3030haven't finished complying to all of them ourselves). Using ` nf-neuro ` helps accelerate
3131development in ** neuroimaging** and produces better research outcomes for all !
3232
33- # Where do I start ?
33+ # Where do I start ?<!-- omit in toc -->
3434
3535Well, it depends on what you want to do. If you want to :
3636
@@ -46,7 +46,6 @@ Well, it depends on what you want to do. If you want to :
4646
4747- [ Discovering ` nf-neuro ` ] ( #discovering-nf-neuro )
4848 - [ Getting info on components from ` nf-neuro ` ] ( #getting-info-on-components-from-nf-neuro )
49- - [ Using the information from the ` info ` command] ( #using-the-information-from-the-info-command )
5049- [ Pipeline creation with ` nf-neuro ` ] ( #pipeline-creation-with-nf-neuro )
5150 - [ Prototyping using components from ` nf-neuro ` ] ( #prototyping-using-components-from-nf-neuro )
5251 - [ Porting prototypes to ` nf- ` ready pipelines] ( #porting-prototypes-to-nf--ready-pipelines )
@@ -62,20 +61,46 @@ extensive guidelines to do it in [this guide](./docs/environment/NFCORE.md).
6261
6362## Getting info on components from ` nf-neuro `
6463
65- With your environment ready, you can list ` nf-neuro ` modules and subworkflows with :
64+ With your environment ready, you can list ` nf-neuro ` modules available with a simple command :
6665
6766``` bash
6867nf-core modules list remote
68+ ```
69+
70+ <p align =" center " >
71+ <img src =" docs/images/cli/nfcore_modules_list.png " alt =" nf-core modules list remote " />
72+ </p > <!-- omit in toc -->
73+
74+ The same goes for ` subworkflows ` :
75+
76+ ``` bash
6977nf-core subworkflows list remote
7078```
7179
72- To get more information on a module (say ` denoising/nlmeans ` ) or a subworkflow (say ` preproc_t1 ` ), use :
80+ <p align =" center " >
81+ <img src =" docs/images/cli/nfcore_subworkflows_list.png " alt =" nf-core subworkflows list remote " />
82+ </p > <!-- omit in toc -->
83+
84+ To get more information on a module (say ` denoising/nlmeans ` ) use :
7385
7486``` bash
7587nf-core modules info denoising/nlmeans
88+ ```
89+
90+ <p align =" center " >
91+ <img src =" docs/images/cli/nfcore_modules_info.png " alt =" nf-core modules info " />
92+ </p > <!-- omit in toc -->
93+
94+ or for a subworkflow (say ` preproc_t1 ` ) :
95+
96+ ``` bash
7697nf-core subworkflows info preproc_t1
7798```
7899
100+ <p align =" center " >
101+ <img src =" docs/images/cli/nfcore_subworkflows_info.png " alt =" nf-core subworkflows info " />
102+ </p > <!-- omit in toc -->
103+
79104> [ !NOTE]
80105> Additionally, ` VS Code ` users can install the [ nextflow extension] ( https://marketplace.visualstudio.com/items?itemName=nextflow.nextflow ) ,
81106> which contains a language server that helps you in real time when coding. It gives you useful tooltips on modules inputs and outputs, commands
@@ -86,101 +111,7 @@ nf-core subworkflows info preproc_t1
86111> description of modules and workflows prescribed by ` nf-core ` and shown below. Thus, we highly recommend its use.
87112
88113You'll get a good description of the modules's or subworkflow's ` behavior ` and ` dependencies ` , as well as a
89- thorough description of its ` inputs ` and ` outputs ` . To use them in your own pipeline, you need first to
90- install them locally :
91-
92- ``` bash
93- nf-core modules install denoising/nlmeans
94- nf-core subworkflows install preproc_t1
95- ```
96-
97- > [ !WARNING]
98- > You need to be at the root of your ` pipeline directory ` when calling this command ! ` nf-core ` installs
99- > locally to your pipeline's ` modules ` and ` subworkflows ` , not in a special hidden place !
100-
101- > [ !NOTE]
102- > On the first run of the ` install ` command, select ` pipeline ` as an install setup. The interactive prompt
103- > will also ask you to create multiple files and directories. Say yes to everything !
104-
105- > [ !IMPORTANT]
106- > The installation procedure will provide you an ` include ` line to add to your pipeline's ` main.nf `
107- > file, which will import the module or subworkflow at runtime.
108-
109- ### Using the information from the ` info ` command
110-
111- For a ` module ` , the list of ` inputs ` tell you the content to provide in ` a single channel ` , usually
112- as a list of lists, each starting with a ` meta ` , a map ` [:] ` of metadata containing a mandatory ` id ` :
113-
114- ``` nextflow
115- // Example for denoising/nlmeans
116- input = Channel.of( [
117- [ [id: "sub-1"], file("image1.nii.gz"), file("mask1.nii.gz") ],
118- [ [id: "sub-2"], file("image2.nii.gz"), file("mask2.nii.gz") ]
119- ] )
120-
121- DENOSING_NLMEANS( input )
122- ```
123-
124- > [ !WARNING]
125- > There are some exceptions here, due to limitations in current ` nf-core ` tools and standards.
126- >
127- > 1 . some inputs could be associated to different channels. It's almost never the case, but it happens.
128- > We are working hard at changing the behavior of those modules, and at improving the metadata to
129- > help you better. For now, please refer to their implementation in the ` modules/nf-neuro/ `
130- > directory as well, through the ` main.nf ` file, or given by the ` nextflow language server tooltips ` .
131-
132- For the ` module's ` list of ` outputs ` , each corresponds to its own ` named channel ` :
133-
134- ``` nextflow
135- // Example for denoising/nlmeans
136- DENOISING_NLMEANS.out.image.view() // [ [ [id: "sub-1"], "sub-1_denoised.nii.gz" ],
137- // [ [id: "sub-2"], "sub-2_denoised.nii.gz" ] ]
138- DENOISING_NLMEANS.out.versions.first().view() // [ "versions.yml" ]
139- ```
140-
141- > [ !WARNING]
142- > There are some exceptions here, due to limitations in current ` nf-core ` tools and standards.
143- >
144- > 1 . ` meta ` output ** is not a channel** but accompanies all files, produced by other channels.
145- > 2 . ` versions ` is a channel, but its output is not accompanied by ` meta `
146- > 3 . Some other outputs are not accompanied by ` meta ` also. We are currently improving the metadata
147- > files to make it apparent. For now, please refer to their implementation in the ` modules/nf-neuro/ `
148- > directory, through the ` main.nf ` file.
149-
150- For ` subworkflows ` there are no exceptions, nor differences between ` inputs ` and ` outputs ` ; they are all
151- ` named channels ` . Each comes with a ` Structure ` description, telling you the content to put in the ` list of lists ` .
152- For ` preproc_t1 ` , a simple example would be :
153-
154- ``` nextflow
155- ch_image = Channel.of( [
156- [ [id: "sub-1"], file("image1.nii.gz") ],
157- [ [id: "sub-2"], file("image2.nii.gz") ]
158- ] )
159-
160- ch_template = Channel
161- .of( [ [id: "sub-1"], [id: "sub-2"] ] )
162- .combine( [ file("template.nii.gz") ] )
163- .view() // [ [ [id: "sub-1"], "template.nii.gz" ],
164- // [ [id: "sub-2"], "template.nii.gz" ] ]
165-
166- ch_probability_map = Channel
167- .of( [ [id: "sub-1"], [id: "sub-2"] ] )
168- .combine( [ file("probmap.nii.gz") ] )
169- .view() // [ [ [id: "sub-1"], "probmap.nii.gz" ],
170- // [ [id: "sub-2"], "probmap.nii.gz" ] ]
171-
172- PREPROC_T1(
173- ch_image
174- ch_template,
175- ch_probability_map
176- )
177-
178- PREPROC_T1.out.t1_final.view() // [ [ [id: "sub-1"], "sub-1_t1_cropped.nii.gz" ],
179- // [ [id: "sub-2"], "sub-2_t1_cropped.nii.gz" ] ]
180- PREPROC_T1.out.mask_final.view() // [ [ [id: "sub-1"], "sub-1_t1_mask_cropped.nii.gz" ],
181- // [ [id: "sub-2"], "sub-2_t1_mask_cropped.nii.gz" ] ]
182- PREPROC_T1.out.versions.first().view() // [ "versions.yml" ]
183- ```
114+ thorough description of its ` inputs ` and ` outputs ` .
184115
185116# Pipeline creation with ` nf-neuro `
186117
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