nextflow-development

Name: nextflow-development
Author: anthropics

1.7kinstalls2.7kforks

How to install nextflow-development?

anthropics/knowledge-work-plugins/nextflow-development

$npx -y skills add anthropics/knowledge-work-plugins --skill nextflow-development

Installs into the current project.

Summary

Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differenti

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SKILL.md

1	# nf-core Pipeline Deployment
2
3	Run nf-core bioinformatics pipelines on local or public sequencing data.
4
5	Target users: Bench scientists and researchers without specialized bioinformatics training who need to run large-scale omics analyses—differential expression, variant calling, or chromatin accessibility analysis.
6
7	## Workflow Checklist
8
9	```
10	- [ ] Step 0: Acquire data (if from GEO/SRA)
11	- [ ] Step 1: Environment check (MUST pass)
12	- [ ] Step 2: Select pipeline (confirm with user)
13	- [ ] Step 3: Run test profile (MUST pass)
14	- [ ] Step 4: Create samplesheet
15	- [ ] Step 5: Configure & run (confirm genome with user)
16	- [ ] Step 6: Verify outputs
17	```
18
19	---
20
21	## Step 0: Acquire Data (GEO/SRA Only)
22
23	Skip this step if user has local FASTQ files.
24
25	For public datasets, fetch from GEO/SRA first. See [references/geo-sra-acquisition.md](references/geo-sra-acquisition.md) for the full workflow.
26
27	Quick start:
28
29	```bash
30	# 1. Get study info
31	python scripts/sra_geo_fetch.py info GSE110004
32
33	# 2. Download (interactive mode)
34	python scripts/sra_geo_fetch.py download GSE110004 -o ./fastq -i
35
36	# 3. Generate samplesheet
37	python scripts/sra_geo_fetch.py samplesheet GSE110004 --fastq-dir ./fastq -o samplesheet.csv
38	```
39
40	DECISION POINT: After fetching study info, confirm with user:
41	- Which sample subset to download (if multiple data types)
42	- Suggested genome and pipeline
43
44	Then continue to Step 1.
45
46	---
47
48	## Step 1: Environment Check
49
50	Run first. Pipeline will fail without passing environment.
51
52	```bash
53	python scripts/check_environment.py
54	```
55
56	All critical checks must pass. If any fail, provide fix instructions:
57
58	### Docker issues
59
60	\| Problem \| Fix \|
61	\|---------\|-----\|
62	\| Not installed \| Install from https://docs.docker.com/get-docker/ \|
63	\| Permission denied \| `sudo usermod -aG docker $USER` then re-login \|
64	\| Daemon not running \| `sudo systemctl start docker` \|
65
66	### Nextflow issues
67
68	\| Problem \| Fix \|
69	\|---------\|-----\|
70	\| Not installed \| `curl -s https://get.nextflow.io \\| bash && mv nextflow ~/bin/` \|
71	\| Version < 23.04 \| `nextflow self-update` \|
72
73	### Java issues
74
75	\| Problem \| Fix \|
76	\|---------\|-----\|
77	\| Not installed / < 11 \| `sudo apt install openjdk-11-jdk` \|
78
79	Do not proceed until all checks pass. For HPC/Singularity, see [references/troubleshooting.md](references/troubleshooting.md).
80
81	---
82
83	## Step 2: Select Pipeline
84
85	DECISION POINT: Confirm with user before proceeding.
86
87	\| Data Type \| Pipeline \| Version \| Goal \|
88	\|-----------\|----------\|---------\|------\|
89	\| RNA-seq \| `rnaseq` \| 3.22.2 \| Gene expression \|
90	\| WGS/WES \| `sarek` \| 3.7.1 \| Variant calling \|
91	\| ATAC-seq \| `atacseq` \| 2.1.2 \| Chromatin accessibility \|
92
93	Auto-detect from data:
94	```bash
95	python scripts/detect_data_type.py /path/to/data
96	```
97
98	For pipeline-specific details:
99	- [references/pipelines/rnaseq.md](references/pipelines/rnaseq.md)
100	- [references/pipelines/sarek.md](references/pipelines/sarek.md)
101	- [references/pipelines/atacseq.md](references/pipelines/atacseq.md)
102
103	---
104
105	## Step 3: Run Test Profile
106
107	Validates environment with small data. MUST pass before real data.
108
109	```bash
110	nextflow run nf-core/<pipeline> -r <version> -profile test,docker --outdir test_output
111	```
112
113	\| Pipeline \| Command \|
114	\|----------\|---------\|
115	\| rnaseq \| `nextflow run nf-core/rnaseq -r 3.22.2 -profile test,docker --outdir test_rnaseq` \|
116	\| sarek \| `nextflow run nf-core/sarek -r 3.7.1 -profile test,docker --outdir test_sarek` \|
117	\| atacseq \| `nextflow run nf-core/atacseq -r 2.1.2 -profile test,docker --outdir test_atacseq` \|
118
119	Verify:
120	```bash
121	ls test_output/multiqc/multiqc_report.html
122	grep "Pipeline completed successfully" .nextflow.log
123	```
124
125	If test fails, see [references/troubleshooting.md](references/troubleshooting.md).
126
127	---
128
129	## Step 4: Create Samplesheet
130
131	### Generate automatically
132
133	```bash
134	python scripts/generate_samplesheet.py /path/to/data <pipeline> -o samplesheet.csv
135	```
136
137	The script:
138	- Discovers FASTQ/BAM/CRAM files
139	- Pairs R1/R2 reads
140	- Infers sample metadata
141	- Validates before writing
142
143	For sarek: Script prompts for tumor/normal status if not auto-detected.
144
145	### Validate existing samplesheet
146
147	```bash
148	python scripts/generate_samplesheet.py --validate samplesheet.csv <pipeline>
149	```
150
151	### Samplesheet formats
152
153	rnaseq:
154	```csv
155	sample,fastq_1,fastq_2,strandedness
156	SAMPLE1,/abs/path/R1.fq.gz,/abs/path/R2.fq.gz,auto
157	```
158
159	sarek:
160	```csv
161	patient,sample,lane,fastq_1,fastq_2,status
162	patient1,tumor,L001,/abs/path/tumor_R1.fq.gz,/abs/path/tumor_R2.fq.gz,1
163	patient1,normal,L001,/abs/path/normal_R1.fq.gz,/abs/path/normal_R2.fq.gz,0
164	```
165
166	atacseq:
167	```csv
168	sample,fastq_1,fastq_2,replicate
169	CONTROL,/abs/path/c

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Type

nextflow-development

1.7kinstalls2.7kforks

View on GitHub

How to install nextflow-development?

anthropics/knowledge-work-plugins/nextflow-development

$npx -y skills add anthropics/knowledge-work-plugins --skill nextflow-development

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# nf-core Pipeline Deployment
2
3	Run nf-core bioinformatics pipelines on local or public sequencing data.
4
5	Target users: Bench scientists and researchers without specialized bioinformatics training who need to run large-scale omics analyses—differential expression, variant calling, or chromatin accessibility analysis.
6
7	## Workflow Checklist
8
9	```
10	- [ ] Step 0: Acquire data (if from GEO/SRA)
11	- [ ] Step 1: Environment check (MUST pass)
12	- [ ] Step 2: Select pipeline (confirm with user)
13	- [ ] Step 3: Run test profile (MUST pass)
14	- [ ] Step 4: Create samplesheet
15	- [ ] Step 5: Configure & run (confirm genome with user)
16	- [ ] Step 6: Verify outputs
17	```
18
19	---
20
21	## Step 0: Acquire Data (GEO/SRA Only)
22
23	Skip this step if user has local FASTQ files.
24
25	For public datasets, fetch from GEO/SRA first. See [references/geo-sra-acquisition.md](references/geo-sra-acquisition.md) for the full workflow.
26
27	Quick start:
28
29	```bash
30	# 1. Get study info
31	python scripts/sra_geo_fetch.py info GSE110004
32
33	# 2. Download (interactive mode)
34	python scripts/sra_geo_fetch.py download GSE110004 -o ./fastq -i
35
36	# 3. Generate samplesheet
37	python scripts/sra_geo_fetch.py samplesheet GSE110004 --fastq-dir ./fastq -o samplesheet.csv
38	```
39
40	DECISION POINT: After fetching study info, confirm with user:
41	- Which sample subset to download (if multiple data types)
42	- Suggested genome and pipeline
43
44	Then continue to Step 1.
45
46	---
47
48	## Step 1: Environment Check
49
50	Run first. Pipeline will fail without passing environment.
51
52	```bash
53	python scripts/check_environment.py
54	```
55
56	All critical checks must pass. If any fail, provide fix instructions:
57
58	### Docker issues
59
60	\| Problem \| Fix \|
61	\|---------\|-----\|
62	\| Not installed \| Install from https://docs.docker.com/get-docker/ \|
63	\| Permission denied \| `sudo usermod -aG docker $USER` then re-login \|
64	\| Daemon not running \| `sudo systemctl start docker` \|
65
66	### Nextflow issues
67
68	\| Problem \| Fix \|
69	\|---------\|-----\|
70	\| Not installed \| `curl -s https://get.nextflow.io \\| bash && mv nextflow ~/bin/` \|
71	\| Version < 23.04 \| `nextflow self-update` \|
72
73	### Java issues
74
75	\| Problem \| Fix \|
76	\|---------\|-----\|
77	\| Not installed / < 11 \| `sudo apt install openjdk-11-jdk` \|
78
79	Do not proceed until all checks pass. For HPC/Singularity, see [references/troubleshooting.md](references/troubleshooting.md).
80
81	---
82
83	## Step 2: Select Pipeline
84
85	DECISION POINT: Confirm with user before proceeding.
86
87	\| Data Type \| Pipeline \| Version \| Goal \|
88	\|-----------\|----------\|---------\|------\|
89	\| RNA-seq \| `rnaseq` \| 3.22.2 \| Gene expression \|
90	\| WGS/WES \| `sarek` \| 3.7.1 \| Variant calling \|
91	\| ATAC-seq \| `atacseq` \| 2.1.2 \| Chromatin accessibility \|
92
93	Auto-detect from data:
94	```bash
95	python scripts/detect_data_type.py /path/to/data
96	```
97
98	For pipeline-specific details:
99	- [references/pipelines/rnaseq.md](references/pipelines/rnaseq.md)
100	- [references/pipelines/sarek.md](references/pipelines/sarek.md)
101	- [references/pipelines/atacseq.md](references/pipelines/atacseq.md)
102
103	---
104
105	## Step 3: Run Test Profile
106
107	Validates environment with small data. MUST pass before real data.
108
109	```bash
110	nextflow run nf-core/<pipeline> -r <version> -profile test,docker --outdir test_output
111	```
112
113	\| Pipeline \| Command \|
114	\|----------\|---------\|
115	\| rnaseq \| `nextflow run nf-core/rnaseq -r 3.22.2 -profile test,docker --outdir test_rnaseq` \|
116	\| sarek \| `nextflow run nf-core/sarek -r 3.7.1 -profile test,docker --outdir test_sarek` \|
117	\| atacseq \| `nextflow run nf-core/atacseq -r 2.1.2 -profile test,docker --outdir test_atacseq` \|
118
119	Verify:
120	```bash
121	ls test_output/multiqc/multiqc_report.html
122	grep "Pipeline completed successfully" .nextflow.log
123	```
124
125	If test fails, see [references/troubleshooting.md](references/troubleshooting.md).
126
127	---
128
129	## Step 4: Create Samplesheet
130
131	### Generate automatically
132
133	```bash
134	python scripts/generate_samplesheet.py /path/to/data <pipeline> -o samplesheet.csv
135	```
136
137	The script:
138	- Discovers FASTQ/BAM/CRAM files
139	- Pairs R1/R2 reads
140	- Infers sample metadata
141	- Validates before writing
142
143	For sarek: Script prompts for tumor/normal status if not auto-detected.
144
145	### Validate existing samplesheet
146
147	```bash
148	python scripts/generate_samplesheet.py --validate samplesheet.csv <pipeline>
149	```
150
151	### Samplesheet formats
152
153	rnaseq:
154	```csv
155	sample,fastq_1,fastq_2,strandedness
156	SAMPLE1,/abs/path/R1.fq.gz,/abs/path/R2.fq.gz,auto
157	```
158
159	sarek:
160	```csv
161	patient,sample,lane,fastq_1,fastq_2,status
162	patient1,tumor,L001,/abs/path/tumor_R1.fq.gz,/abs/path/tumor_R2.fq.gz,1
163	patient1,normal,L001,/abs/path/normal_R1.fq.gz,/abs/path/normal_R2.fq.gz,0
164	```
165
166	atacseq:
167	```csv
168	sample,fastq_1,fastq_2,replicate
169	CONTROL,/abs/path/c

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