final ui cleanup

tahirdme · tahirdme · commit fb1e73ca5f95 · 2024-09-13T23:40:22.000-07:00
diff --git a/latch_metadata/__init__.py b/latch_metadata/__init__.py
@@ -8,6 +8,7 @@
     author=LatchAuthor(
         name="nf-core",
     ),
+    repository="https://github.com/latchbio-nfcore/scrnaseq",
     parameters=generated_parameters,
     runtime_resources=NextflowRuntimeResources(
         cpus=4,
diff --git a/latch_metadata/parameters.py b/latch_metadata/parameters.py
@@ -1,16 +1,13 @@
 from dataclasses import dataclass
 from enum import Enum
-from pathlib import Path
 from typing import List, Optional
 
-from flytekit.core.annotation import FlyteAnnotation
 from latch.types.directory import LatchDir, LatchOutputDir
 from latch.types.file import LatchFile
 from latch.types.metadata import (
     Fork,
     ForkBranch,
-    LatchAuthor,
-    NextflowMetadata,
+    LatchRule,
     NextflowParameter,
     Params,
     Section,
@@ -149,6 +146,12 @@ class SampleSheet:
         section_title=None,
         display_name="Run name",
         description="Name of Run",
+        rules=[
+            LatchRule(
+                regex=r"^[a-zA-Z0-9_-]+$",
+                message="Run name must contain only letters, digits, underscores, and dashes. No spaces are allowed.",
+            )
+        ],
     ),
     "email": NextflowParameter(
         type=Optional[str],
diff --git a/version b/version
@@ -1 +1 @@
-0.1.0
+2.7.1
diff --git a/wf/__init__.py b/wf/__init__.py
@@ -1,19 +1,18 @@
-from typing import Annotated, List, Optional
+from typing import List, Optional
 
-from flytekit.core.annotation import FlyteAnnotation
 from latch.resources.launch_plan import LaunchPlan
 from latch.resources.workflow import workflow
 from latch.types import metadata
 from latch.types.directory import LatchDir, LatchOutputDir
 from latch.types.file import LatchFile
 
+from wf.cellxgene import cellxgene_prep
 from wf.entrypoint import (
     Aligner,
     Chemistry,
     Reference_Type,
     SampleSheet,
     STAR_options,
-    cellxgene_prep,
     initialize,
     kb_workflow,
     nextflow_runtime,
@@ -60,12 +59,94 @@ def nf_nf_core_scrnaseq(
     skip_emptydrops: bool = True,
 ) -> LatchOutputDir:
     """
-    nf-core/scrnaseq
+    nf-core/scrnaseq is a bioinformatics best-practice analysis pipeline for processing 10x Genomics single-cell RNA-seq data.
+
+    <html>
+    <p align="center">
+    <img src="https://user-images.githubusercontent.com/31255434/182289305-4cc620e3-86ae-480f-9b61-6ca83283caa5.jpg" alt="Latch Verified" width="100">
+    </p>
+
+    <p align="center">
+    <strong>
+    Latch Verified
+    </strong>
+    </p>
+
+    <p align="center">
+
+    [![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.3568187-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.3568187)
+
+    **nf-core/scrnaseq** is a bioinformatics best-practice analysis pipeline for processing 10x Genomics single-cell RNA-seq data.
+
+    ## Introduction
+
+    This workflow is hosted on Latch Workflows, using a native Nextflow integration, with a graphical interface for accessible analysis by scientists. There is also an integration with Latch Registry so that batched workflows can be launched from “graphical sample sheets” or tables associating raw sequencing files with metadata.
+
+    This is a community effort in building a pipeline capable to support:
+
+    - Alevin-Fry + AlevinQC
+    - STARSolo
+    - Kallisto + BUStools
+
+    ## Documentation
+
+    The nf-core/scrnaseq pipeline comes with documentation about the pipeline [usage](https://nf-co.re/scrnaseq/usage), [parameters](https://nf-co.re/scrnaseq/parameters) and [output](https://nf-co.re/scrnaseq/output).
+
+    ## Usage
+
+    First, prepare a samplesheet with your input data that looks as follows:
+
+    `samplesheet.csv`:
+
+    sample,fastq_1,fastq_2,expected_cells
+    pbmc8k,pbmc8k_S1_L007_R1_001.fastq.gz,pbmc8k_S1_L007_R2_001.fastq.gz,10000
+    pbmc8k,pbmc8k_S1_L008_R1_001.fastq.gz,pbmc8k_S1_L008_R2_001.fastq.gz,10000
+
+    Each row represents a fastq file (single-end) or a pair of fastq files (paired end).
+
+    ## Decision Tree for users
+
+    The nf-core/scrnaseq pipeline features several paths to analyze your single cell data. Future additions will also be done soon, e.g. the addition of multi-ome analysis types. To aid users in analyzing their data, we have added a decision tree to help people decide on what type of analysis they want to run and how to choose appropriate parameters for that.
+
+    Options for the respective alignment method can be found [here](https://github.com/nf-core/scrnaseq/blob/dev/docs/usage.md#aligning-options) to choose between methods.
+
+    ## Pipeline output
+
+    To see the results of an example test run with a full size dataset refer to the [results](https://nf-co.re/scrnaseq/results) tab on the nf-core website pipeline page.
+    For more details about the output files and reports, please refer to the
+    [output documentation](https://nf-co.re/scrnaseq/output).
+
+    ## Credits
+
+    nf-core/scrnaseq was originally written by Bailey PJ, Botvinnik O, Marques de Almeida F, Gabernet G, Peltzer A, Sturm G.
+
+    We thank the following people and teams for their extensive assistance in the development of this pipeline:
+
+    - @heylf
+    - @KevinMenden
+    - @FloWuenne
+    - @rob-p
+    - [GHGA](https://www.ghga.de/)
+
+    ## Contributions and Support
+
+    If you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).
+
+    For further information or help, don't hesitate to get in touch on the [Slack `#scrnaseq` channel](https://nfcore.slack.com/channels/scrnaseq) (you can join with [this invite](https://nf-co.re/join/slack)).
+
+    ## Citations
+
+    If you use nf-core/scrnaseq for your analysis, please cite it using the following doi: [10.5281/zenodo.3568187](https://doi.org/10.5281/zenodo.3568187)
+
+    The basic benchmarks that were used as motivation for incorporating the three available modular workflows can be found in [this publication](https://www.biorxiv.org/content/10.1101/673285v2).
+
+    We offer all three paths for the processing of scRNAseq data so it remains up to the user to decide which pipeline workflow is chosen for a particular analysis question.
+
+    An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.
 
-    Sample Description
     """
 
-    pvc_name: str = initialize()
+    pvc_name: str = initialize(run_name=run_name)
     run_name = nextflow_runtime(
         pvc_name=pvc_name,
         input=input,
diff --git a/wf/entrypoint.py b/wf/entrypoint.py
@@ -9,22 +9,16 @@
 from typing import Any, List, Optional
 
 import requests
-import typing_extensions
-from flytekit.core.annotation import FlyteAnnotation
 from latch.executions import rename_current_execution, report_nextflow_used_storage
 from latch.ldata.path import LPath
 from latch.resources.tasks import custom_task, nextflow_runtime_task
-from latch.resources.workflow import workflow
-from latch.types import metadata
 from latch.types.directory import LatchDir, LatchOutputDir
 from latch.types.file import LatchFile
 from latch_cli.nextflow.utils import _get_execution_name
 from latch_cli.nextflow.workflow import get_flag
 from latch_cli.services.register.utils import import_module_by_path
 from latch_cli.utils import urljoins
 
-from wf.cellxgene import cellxgene_prep
-
 meta = Path("latch_metadata") / "__init__.py"
 import_module_by_path(meta)
 
@@ -142,7 +136,9 @@ def custom_samplesheet_constructor(
 
 
 @custom_task(cpu=0.25, memory=0.5, storage_gib=1)
-def initialize() -> str:
+def initialize(run_name: str) -> str:
+    rename_current_execution(str(run_name))
+
     token = os.environ.get("FLYTE_INTERNAL_EXECUTION_ID")
     if token is None:
         raise RuntimeError("failed to get execution token")
@@ -166,11 +162,6 @@ def initialize() -> str:
     return resp.json()["name"]
 
 
-# input_construct_samplesheet = metadata._nextflow_metadata.parameters[
-#     "input"
-# ].samplesheet_constructor
-
-
 @nextflow_runtime_task(cpu=8, memory=8, storage_gib=500)
 def nextflow_runtime(
     run_name: str,
@@ -212,9 +203,7 @@ def nextflow_runtime(
     skip_emptydrops: bool = True,
 ) -> str:
     shared_dir = Path("/nf-workdir")
-    rename_current_execution(str(run_name))
 
-    # input_samplesheet = input_construct_samplesheet(input)
     # Create custom sample sheet
     input_samplesheet = custom_samplesheet_constructor(
         samples=input, shared_dir=shared_dir
@@ -396,97 +385,3 @@ def nextflow_runtime(
             sys.exit(1)
 
         return str(run_name)
-
-
-@workflow(metadata._nextflow_metadata)
-def nf_nf_core_scrnaseq(
-    run_name: str,
-    input: List[SampleSheet],
-    outdir: LatchOutputDir,
-    email: Optional[str],
-    multiqc_title: Optional[str],
-    barcode_whitelist: Optional[LatchFile],
-    protocol: Chemistry,
-    skip_multiqc: bool,
-    skip_fastqc: bool,
-    genome_source: str,
-    genome: Optional[str],
-    fasta: Optional[LatchFile],
-    transcript_fasta: Optional[LatchFile],
-    gtf: Optional[LatchFile],
-    salmon_index: Optional[LatchDir],
-    txp2gene: Optional[LatchFile],
-    star_index: Optional[LatchDir],
-    star_ignore_sjdbgtf: Optional[LatchFile],
-    seq_center: Optional[str],
-    kallisto_index: Optional[LatchDir],
-    kb_t1c: Optional[LatchFile],
-    kb_t2c: Optional[LatchFile],
-    kb_filter: bool,
-    cellranger_index: Optional[LatchFile],
-    motifs: Optional[str],
-    cellrangerarc_config: Optional[str],
-    cellrangerarc_reference: Optional[str],
-    universc_index: Optional[LatchFile],
-    multiqc_methods_description: Optional[LatchFile],
-    aligner: Aligner = Aligner.alevin,
-    latch_genome: Reference_Type = Reference_Type.hg38,
-    simpleaf_rlen: Optional[int] = 91,
-    star_feature: Optional[STAR_options] = STAR_options.gene,
-    kb_workflow: Optional[kb_workflow] = kb_workflow.std,
-    save_reference: bool = False,
-    skip_emptydrops: bool = True,
-) -> LatchOutputDir:
-    """
-    nf-core/scrnaseq
-
-    Sample Description
-    """
-
-    pvc_name: str = initialize()
-    run_name = nextflow_runtime(
-        pvc_name=pvc_name,
-        input=input,
-        outdir=outdir,
-        run_name=run_name,
-        email=email,
-        multiqc_title=multiqc_title,
-        barcode_whitelist=barcode_whitelist,
-        aligner=aligner,
-        protocol=protocol,
-        skip_multiqc=skip_multiqc,
-        skip_fastqc=skip_fastqc,
-        skip_emptydrops=skip_emptydrops,
-        genome_source=genome_source,
-        genome=genome,
-        latch_genome=latch_genome,
-        fasta=fasta,
-        transcript_fasta=transcript_fasta,
-        gtf=gtf,
-        save_reference=save_reference,
-        salmon_index=salmon_index,
-        txp2gene=txp2gene,
-        simpleaf_rlen=simpleaf_rlen,
-        star_index=star_index,
-        star_ignore_sjdbgtf=star_ignore_sjdbgtf,
-        seq_center=seq_center,
-        star_feature=star_feature,
-        kallisto_index=kallisto_index,
-        kb_t1c=kb_t1c,
-        kb_t2c=kb_t2c,
-        kb_workflow=kb_workflow,
-        kb_filter=kb_filter,
-        cellranger_index=cellranger_index,
-        motifs=motifs,
-        cellrangerarc_config=cellrangerarc_config,
-        cellrangerarc_reference=cellrangerarc_reference,
-        universc_index=universc_index,
-        multiqc_methods_description=multiqc_methods_description,
-    )
-
-    return cellxgene_prep(
-        run_name=run_name,
-        aligner=aligner,
-        skip_emptydrops=skip_emptydrops,
-        outdir=outdir,
-    )
