Reference
An overview of the workflows and modules in OpenPipelines
Workflows
Name | Namespace | Description |
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BD Rhapsody | Workflows/ingestion | BD Rhapsody Sequence Analysis CWL pipeline v2.2.1 |
Bbknn leiden | Workflows/integration | Run bbknn followed by leiden clustering and run umap on the result. |
Cell Ranger mapping | Workflows/ingestion | A pipeline for running Cell Ranger mapping. |
Cell Ranger multi | Workflows/ingestion | A pipeline for running Cell Ranger multi. |
Cell Ranger post-processing | Workflows/ingestion | Post-processing Cell Ranger datasets. |
Convert to MuData | Workflows/ingestion | A pipeline to convert different file formats to .h5mu. |
Demux | Workflows/ingestion | A generic pipeline for running bcl2fastq, bcl-convert or Cell Ranger mkfastq. |
Dimensionality reduction | Workflows/multiomics | Run calculations that output information required for most integration methods: PCA, nearest neighbour and UMAP. |
GDO Singlesample | Workflows/gdo | Processing unimodal single-sample guide-derived oligonucleotide (GDO) data. |
Harmony integration followed by KNN label transfer | Workflows/annotation | Cell type annotation workflow by performing harmony integration of reference and query dataset followed by KNN label transfer. |
Harmony leiden | Workflows/integration | Run harmony integration followed by neighbour calculations, leiden clustering and run umap on the result. |
Make reference | Workflows/ingestion | Build a transcriptomics reference into one of many formats |
Neighbors leiden umap | Workflows/multiomics | Performs neighborhood search, leiden clustering and run umap on an integrated embedding. |
Process batches | Workflows/multiomics | This workflow serves as an entrypoint into the ‘full_pipeline’ in order to re-run the multisample processing and the integration setup. |
Process samples | Workflows/multiomics | A pipeline to analyse multiple multiomics samples. |
Prot multisample | Workflows/prot | Processing unimodal multi-sample ADT data. |
Prot singlesample | Workflows/prot | Processing unimodal single-sample CITE-seq data. |
Qc | Workflows/qc | A pipeline to add basic qc statistics to a MuData |
Rna multisample | Workflows/rna | Processing unimodal multi-sample RNA transcriptomics data. |
Rna singlesample | Workflows/rna | Processing unimodal single-sample RNA transcriptomics data. |
Scanorama leiden | Workflows/integration | Run scanorama integration followed by neighbour calculations, leiden clustering and run umap on the result. |
Scgpt leiden | Workflows/integration | Run scGPT integration (cell embedding generation) followed by neighbour calculations, leiden clustering and run umap on the result. |
Scvi leiden | Workflows/integration | Run scvi integration followed by neighbour calculations, leiden clustering and run umap on the result. |
Split h5mu | Workflows/multiomics | Split the samples of a single modality from a .h5mu (multimodal) sample into seperate .h5mu files based on the values of an .obs column of this modality |
Split modalities | Workflows/multiomics | A pipeline to split a multimodal mudata files into several unimodal mudata files. |
Totalvi leiden | Workflows/integration | Run totalVI integration followed by neighbour calculations, leiden clustering and run umap on the result. |
scANVI - scArches workflow | Workflows/annotation | Cell type annotation workflow using ScanVI with scArches for reference mapping. |
scGPT Annotation | Workflows/annotation | Cell type annotation workflow using scGPT. |
scVI Annotation | Workflows/annotation | Cell type annotation workflow that performs scVI integration of reference and query dataset followed by KNN label transfer. |
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Modules
Name | Namespace | Description |
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Add id | Metadata | Add id of .obs. |
Align query reference | Feature annotation | Alignment of a query and reference dataset by: * Alignment of layers * Harmonization of .obs field names for batch and cell type labels * Harmonization of .var field name for gene names * Sanitation of gene names * Cross-checking of genes * Assignment of an id to the query and reference datasets |
Bbknn | Neighbors | BBKNN network generation |
Bcftools | Genetic demux | Filter the variants called by freebayes or cellSNP |
Bcl convert | Demux | Convert bcl files to fastq files using bcl-convert. |
Bcl2fastq | Demux | Convert bcl files to fastq files using bcl2fastq |
Bd rhapsody | Mapping | BD Rhapsody Sequence Analysis CWL pipeline v2.2.1 This pipeline performs analysis of single-cell multiomic sequence read (FASTQ) data. |
Binning | Scgpt | Conversion of (pre-processed) expression count data into relative values (bins) to address scale differences across sequencing batches |
Bpcells regress out | Transform | Regress out the effects of confounding variables using a linear least squares regression model with BPCells |
Build bdrhap reference | Reference | The Reference Files Generator creates an archive containing Genome Index and Transcriptome annotation files needed for the BD Rhapsody Sequencing Analysis Pipeline. |
Build cellranger arc reference | Reference | Build a Cell Ranger-arc and -atac compatible reference folder from user-supplied genome FASTA and gene GTF files. |
Build cellranger reference | Reference | Build a Cell Ranger-compatible reference folder from user-supplied genome FASTA and gene GTF files. |
Build star reference | Reference | Create a reference for STAR from a set of fasta files. |
Calculate atac qc metrics | Qc | Add basic ATAC quality control metrics to an .h5mu file. |
Calculate qc metrics | Qc | Add basic quality control metrics to an .h5mu file. |
Cell type annotation | Scgpt | Annotate gene expression data with cell type classes through the scGPT model |
Cellbender remove background | Correction | Eliminating technical artifacts from high-throughput single-cell RNA sequencing data. |
Cellbender remove background v0 2 | Correction | Eliminating technical artifacts from high-throughput single-cell RNA sequencing data. |
Cellranger atac count | Mapping | Align fastq files using Cell Ranger ATAC count. |
Cellranger atac mkfastq | Demux | Demultiplex raw sequencing data for ATAC experiments |
Cellranger count | Mapping | Align fastq files using Cell Ranger count. |
Cellranger count split | Mapping | Split 10x Cell Ranger output directory into separate output fields. |
Cellranger mkfastq | Demux | Demultiplex raw sequencing data |
Cellranger mkgtf | Reference | Make a GTF file - filter by a specific attribute. |
Cellranger multi | Mapping | Align fastq files using Cell Ranger multi. |
Cellsnp | Genetic demux | cellSNP aims to pileup the expressed alleles in single-cell or bulk RNA-seq data. |
Celltypist | Annotate | Automated cell type annotation tool for scRNA-seq datasets on the basis of logistic regression classifiers optimised by the stochastic gradient descent algorithm. |
Cellxgene census | Query | Query cells from a CellxGene Census or custom TileDBSoma object. |
Clr | Transform | Perform CLR normalization on CITE-seq data (Stoeckius et al., 2017) |
Compress h5mu | Compression | Compress a MuData file. |
Concatenate h5mu | Dataflow | Concatenate observations from samples in several (uni- and/or multi-modal) MuData files into a single file |
Cross check genes | Scgpt | Cross-check genes with pre-trained scGPT model |
Delete layer | Transform | Delete an anndata layer from one or more modalities |
Delimit fraction | Filter | Turns a column containing values between 0 and 1 into a boolean column based on thresholds |
Demuxlet | Genetic demux | Demuxlet is a software tool to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing. |
Densmap | Dimred | A modification of UMAP that adds an extra cost term in order to preserve information about the relative local density of the data. |
Do filter | Filter | Remove observations and variables based on specified .obs and .var columns |
Download file | Download | Download a file |
Dsc pileup | Genetic demux | Dsc-pileup is a software tool to pileup reads and corresponding base quality for each overlapping SNPs and each barcode. |
Embedding | Scgpt | Generation of cell embeddings for the integration of single cell transcriptomic count data using scGPT |
Fastqc | Qc | Fastqc component, please see https://www.bioinformatics.babraham.ac.uk/projects/fastqc/. |
Filter 10xh5 | Process 10xh5 | Filter a 10x h5 dataset |
Filter with counts | Filter | Filter scRNA-seq data based on the primary QC metrics. |
Filter with scrublet | Filter | Doublet detection using the Scrublet method (Wolock, Lopez and Klein, 2019). |
Find neighbors | Neighbors | Compute a neighborhood graph of observations [McInnes18]. |
Freebayes | Genetic demux | Freebayes is a Bayesian genetic variant detector designed to find small polymorphisms, specifically SNPs |
Freemuxlet | Genetic demux | Freemuxlet is a software tool to deconvolute sample identity and identify multiplets when multiple samples are pooled by barcoded single cell sequencing. |
From 10xh5 to h5mu | Convert | Converts a 10x h5 into an h5mu file |
From 10xmtx to h5mu | Convert | Converts a 10x mtx into an h5mu file |
From bd to 10x molecular barcode tags | Convert | Convert the molecular barcode sequence SAM tag from BD format (MA) to 10X format (UB) |
From bdrhap to h5mu | Convert | Convert the output of a BD Rhapsody pipeline v2.x to a MuData h5 file |
From cellranger multi to h5mu | Convert | Converts the output from cellranger multi to a single .h5mu file. |
From h5ad to h5mu | Convert | Converts a single layer h5ad file into a single MuData object |
From h5ad to seurat | Convert | Converts an h5ad file into a Seurat file |
From h5mu to h5ad | Convert | Converts a h5mu file into a h5ad file |
From h5mu to seurat | Convert | Converts an h5mu file into a Seurat file. |
Grep annotation column | Metadata | Perform a regex lookup on a column from the annotation matrices .obs or .var. |
Harmonypy | Integrate | Performs Harmony integration based as described in https://github.com/immunogenomics/harmony. |
Highly variable features scanpy | Feature annotation | Annotate highly variable features [Satija15] [Zheng17] [Stuart19]. |
Htseq count | Mapping | Quantify gene expression for subsequent testing for differential expression. |
Htseq count to h5mu | Mapping | Convert the htseq table to a h5mu |
Intersect obs | Filter | Create an intersection between two or more modalities. |
Join csv | Metadata | Join a csv containing metadata to the .obs or .var field of a mudata file. |
Join uns to obs | Metadata | Join a data frame of length 1 (1 row index value) in .uns containing metadata to the .obs of a mudata file. |
Knn | Labels transfer | This component performs label transfer from reference to query using a K-Neirest Neighbors classifier |
Leiden | Cluster | Cluster cells using the [Leiden algorithm] [Traag18] implemented in the [Scanpy framework] [Wolf18]. |
Lianapy | Interpret | Performs LIANA integration based as described in https://github.com/saezlab/liana-py |
Log1p | Transform | Logarithmize the data matrix. |
Lsi | Dimred | Runs Latent Semantic Indexing. |
Make params | Files | Looks for files in a directory and turn it in a params file. |
Make reference | Reference | Preprocess and build a transcriptome reference. |
Merge | Dataflow | Combine one or more single-modality .h5mu files together into one .h5mu file |
Mermaid | Report | Generates a network from mermaid code |
Move layer | Transform | Move a data matrix stored at the .layers or .X attributes in a MuData object to another layer. |
Move obsm to obs | Metadata | Move a matrix from .obsm to .obs. |
Multi star | Mapping | Align fastq files using STAR. |
Multi star to h5mu | Mapping |
Convert the output of multi_star to a h5mu
|
Multiqc | Qc | MultiQC aggregates results from bioinformatics analyses across many samples into a single report. |
Normalize total | Transform | Normalize counts per cell. |
Onclass | Annotate | OnClass is a python package for single-cell cell type annotation. |
Pad tokenize | Scgpt | Tokenize and pad a batch of data for scGPT integration zero-shot inference or fine-tuning |
Pca | Dimred | Computes PCA coordinates, loadings and variance decomposition. |
Popv | Annotate | Performs popular major vote cell typing on single cell sequence data using multiple algorithms. |
Publish | Transfer | Publish an artifact and optionally rename with parameters |
Random forest annotation | Annotate | Automated cell type annotation tool for scRNA-seq datasets on the basis of random forest. |
Regress out | Transform | Regress out (mostly) unwanted sources of variation. |
Remove modality | Filter | Remove a modality from a .h5mu file |
Samtools | Genetic demux | Filter the BAM according to the instruction of scSplit via Samtools. |
Samtools sort | Mapping | Sort and (optionally) index alignments. |
Scale | Transform | Scale data to unit variance and zero mean |
Scanorama | Integrate | Use Scanorama to integrate different experiments |
Scanvi | Annotate | scANVI () is a semi-supervised model for single-cell transcriptomics data. |
Scarches | Integrate | Performs reference mapping with scArches |
Score genes cell cycle scanpy | Feature annotation | Calculates the score associated to S phase and G2M phase and annotates the cell cycle phase for each cell, as implemented by scanpy. |
Scsplit | Genetic demux | scsplit is a genotype-free demultiplexing methode of pooled single-cell RNA-seq, using a hidden state model for identifying genetically distinct samples within a mixed population. |
Scvelo | Velocity |
ID: scvelo Namespace: velocity
|
Scvi | Integrate | Performs scvi integration as done in the human lung cell atlas https://github.com/LungCellAtlas/HLCA |
Souporcell | Genetic demux | souporcell is a method for clustering mixed-genotype scRNAseq experiments by individual. |
Split h5mu | Dataflow | Split the samples of a single modality from a .h5mu (multimodal) sample into seperate .h5mu files based on the values of an .obs column of this modality. |
Split h5mu train test | Dataflow | Split mudata object into training and testing (and validation) datasets based on observations into separate mudata objects. |
Split modalities | Dataflow | Split the modalities from a single .h5mu multimodal sample into seperate .h5mu files. |
Star align | Mapping | Align fastq files using STAR. |
Star align v273a | Mapping | Align fastq files using STAR. |
Subset h5mu | Filter | Create a subset of a mudata file by selecting the first number of observations |
Subset obsp | Filter | Create a subset of an .obsp field in a mudata file, by filtering the columns based on the values of an .obs column. |
Svm annotation | Annotate | Automated cell type annotation tool for scRNA-seq datasets on the basis of SVMs. |
Sync test resources | Download | Sync test resources to the local filesystem |
Tar extract | Compression | Extract files from a tar archive |
Tfidf | Transform | Perform TF-IDF normalization of the data (typically, ATAC). |
Totalvi | Integrate | Performs mapping to the reference by totalvi model: https://docs.scvi-tools.org/en/stable/tutorials/notebooks/scarches_scvi_tools.html#Reference-mapping-with-TOTALVI |
Tsne | Dimred | t-SNE (t-Distributed Stochastic Neighbor Embedding) is a dimensionality reduction technique used to visualize high-dimensional data in a low-dimensional space, revealing patterns and clusters by preserving local data similarities |
Umap | Dimred | UMAP (Uniform Manifold Approximation and Projection) is a manifold learning technique suitable for visualizing high-dimensional data. |
Velocyto | Velocity | Runs the velocity analysis on a BAM file, outputting a loom file. |
Velocyto to h5mu | Convert | Convert a velocyto loom file to a h5mu file. |
Vireo | Genetic demux | Vireo is primarily designed for demultiplexing cells into donors by modelling of expressed alleles. |
Xgboost | Labels transfer | Performs label transfer from reference to query using XGBoost classifier |
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