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**nf-core/resolvinf** is a comprehensive bioinformatics pipeline that integrates **ResolVI** (Resolution of Variational Inference) and **scVIVA** (single-cell Variational Inference for Variational Analysis) for advanced spatial transcriptomics data analysis. This dual-method approach provides state-of-the-art noise correction, cell type prediction, and niche-aware differential expression analysis.
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**nf-core/parallax** is a comprehensive bioinformatics pipeline that integrates **ResolVI** (Resolution of Variational Inference) and **scVIVA** (single-cell Variational Inference for Variational Analysis) for advanced spatial transcriptomics data analysis. This dual-method approach provides state-of-the-art noise correction, cell type prediction, and niche-aware differential expression analysis.
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### Key Technologies
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3. Download the pipeline and test it on a minimal dataset with a single command:
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```bash
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nextflow run nf-core/resolvinf -profile test,docker --outdir <OUTDIR>
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nextflow run nf-core/parallax -profile test,docker --outdir <OUTDIR>
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```
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Note that some form of configuration will be needed so that Nextflow knows how to fetch the required software. This is usually done in the form of a config profile (`YOURPROFILE` in the example command above). You can chain multiple config profiles in a comma-separated string.
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4. Start running your own analysis!
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```bash
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nextflow run nf-core/resolvinf --input samplesheet.csv --outdir <OUTDIR> -profile <docker/singularity/podman/shifter/charliecloud/conda/institute>
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nextflow run nf-core/parallax --input samplesheet.csv --outdir <OUTDIR> -profile <docker/singularity/podman/shifter/charliecloud/conda/institute>
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```
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## Input Requirements
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### Condition Types
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#### 1. **Cell Type Comparisons** (Simple)
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Compare different cell types without specific conditions:
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```json
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```
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#### 2. **Treatment/Disease Conditions**
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Compare the same cell type across different treatments or disease states:
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```json
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```
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#### 3. **Spatial Region Conditions**
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Compare cell types or conditions across different spatial regions:
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```json
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```
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#### 4. **Sample-Based Conditions**
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Map specific samples to conditions when metadata isn't directly encoded:
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```json
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```
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#### 5. **Cross-Condition Cell Type Comparisons**
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Compare different cell types across different conditions:
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```json
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The pipeline automatically detects and establishes conditions using the following priority order:
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1.**Explicit condition column**: Uses the column specified in ```condition_column```
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2.**Sample mapping**: Creates conditions from ```samples_condition1``` and ```samples_condition2``` lists
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3.**Spatial regions**: Uses ```spatial_region``` column if available
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4.**Common metadata columns**: Automatically detects ```treatment```, ```tissue_type```, etc.
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5.**Sample ID fallback**: Uses ```sample_id``` as conditions if no other method works
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1.**Explicit condition column**: Uses the column specified in `condition_column`
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2.**Sample mapping**: Creates conditions from `samples_condition1` and `samples_condition2` lists
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3.**Spatial regions**: Uses `spatial_region` column if available
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4.**Common metadata columns**: Automatically detects `treatment`, `tissue_type`, etc.
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5.**Sample ID fallback**: Uses `sample_id` as conditions if no other method works
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### Required Data Preparation
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Ensure your AnnData objects contain the necessary metadata:
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#### Essential Columns
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-**Cell type predictions**: ```resolvi_predicted``` (automatically generated by ResolVI)
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-**Sample information**: ```sample_id``` (automatically added during preprocessing)
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-**Cell type predictions**: `resolvi_predicted` (automatically generated by ResolVI)
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-**Sample information**: `sample_id` (automatically added during preprocessing)
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#### Optional Condition Columns
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-```condition```: General condition labels
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-```treatment```: Treatment/control labels
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-```tissue_type```: Tissue or disease state labels
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-```spatial_region```: Spatial region annotations
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-```timepoint```: Temporal conditions
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-`condition`: General condition labels
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-`treatment`: Treatment/control labels
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-`tissue_type`: Tissue or disease state labels
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-`spatial_region`: Spatial region annotations
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-`timepoint`: Temporal conditions
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- Custom condition columns as specified in your comparisons
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### File Formats
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#### JSON Format (Recommended)
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```json
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[
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{
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"name": "comparison_name",
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"group1": "Cell_Type_1",
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"group2": "Cell_Type_2",
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"group2": "Cell_Type_2",
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"condition1": "condition_A",
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"condition2": "condition_B",
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"condition_column": "metadata_column",
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## Credits
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nf-core/resolvinf was originally written by Christopher Tastad.
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nf-core/parallax was originally written by Christopher Tastad.
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We thank the following people for their extensive assistance in the development of this pipeline:
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If you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md).
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For further information or help, don't hesitate to get in touch on the [Slack `#resolvinf` channel](https://nfcore.slack.com/channels/resolvinf) (you can join with [this invite](https://nf-co.re/join/slack)).
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For further information or help, don't hesitate to get in touch on the [Slack `#parallax` channel](https://nfcore.slack.com/channels/parallax) (you can join with [this invite](https://nf-co.re/join/slack)).
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## Citations
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If you use nf-core/resolvinf for your analysis, please cite:
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If you use nf-core/parallax for your analysis, please cite:
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### Pipeline
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<!-- TODO: Add DOI after first release -->
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<!-- > **nf-core/resolvinf: A Nextflow implementation of ResolVI and scVIVA for comprehensive spatial transcriptomics analysis**
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<!-- > **nf-core/parallax: A Nextflow implementation of ResolVI and scVIVA for comprehensive spatial transcriptomics analysis**
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