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single cell Galaxy{:.sc-intro-left}

Welcome to the world of Single Cell Omics

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The Single Cell Omics workbench is a comprehensive set of analysis tools and consolidated workflows. The workbench is based on the Galaxy framework{:target="_blank"}, which guarantees simple access, easy extension, flexible adaption to personal and security needs, and sophisticated analyses independent of command-line knowledge.

The current implementation comprises more than 20 bioinformatics tools dedicated to different research areas of single cell biology.

This service is a joint project between different groups from the Earlham Institute{:target="_blank"}, the EMBL-EBI{:target="_blank"}, EMBL{:target="_blank"} the Sorbonne University{:target="_blank"}, Peter MacCallum Cancer Centre{:target="_blank"} and the University of Freiburg{:target="_blank"}. The server is part if the European Galaxy server and is maintained by the RNA Bioinformatics Center (RBC){:target="_blank"} as part of de.NBI{:target="_blank"} and ELIXIR{:target="_blank"}.

Content

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  1. TOC {:toc}

Get started

Are you new to Galaxy, or returning after a long time, and looking for help to get started? Take [a guided tour]({{ page.website }}/tours/core.galaxy_ui){:target="_blank"} through Galaxy's user interface.

Training and Workshops

Want to learn more about single cell analyses? Check out the following hands-on tutorials from the Galaxy Training Network{:target=_"blank"}, or come to one of our workshops.

We are passionate about training. So we are working in close collaboration with the Galaxy Training Network (GTN){:target="_blank"} to develop training materials of data analyses based on Galaxy {% cite batut2017community %}. These materials hosted on the GTN GitHub repository are available online at https://training.galaxyproject.org{:target="_blank"}.

Material

Lesson Slides Hands-on Input dataset Workflows Galaxy History
Introduction to Transcriptomics {:target="_blank"}
Plates, Batches, and Barcodes {:target="_blank"}
Understanding Barcodes {:target="_blank"} {:target="_blank"} []({{ page.website }}/workflows/run?id=d7aa4c258e2edc95){:target="_blank"} []({{ page.website }}/u/mehmet-tekman/h/understanding-barcodes){:target="_blank"}
Pre-processing of Single-Cell RNA Data {:target="_blank"} {:target="_blank"} []({{ page.website }}/workflows/run?id=49073a24429d93d6){:target="_blank"} []({{ page.website }}/workflows/run?id=76a6330d5fc241c7){:target="_blank"} []({{ page.website }}/u/mehmet-tekman/h/celseq2-single-batch-mm10){:target="_blank"} []({{ page.website }}/u/mehmet-tekman/h/celseq2-multi-batch-workflow){:target="_blank"}
Pre-processing of 10X Single-Cell RNA Datasets {:target="_blank"} {:target="_blank"} []({{ page.website }}/workflows/run?id=d79309343e2a5d62){:target="_blank"} []({{ page.website }}/u/mehmet-tekman/h/pre-processing-of-10x-single-cell-rna-star-278a){:target="_blank"}
Single-Cell Quality Control with Scater {:target="_blank"} {:target="_blank"} []({{ page.website }}/workflows/run?id=f055b8fa294d4be8){:target="_blank"} []({{ page.website }}/u/mehmet-tekman/h/single-cell-quality-control-with-scater){:target="_blank"}
Downstream Single-cell RNA analysis with RaceID {:target="_blank"} {:target="_blank"} []({{ page.website }}/workflows/run?id=2f8d9fb85242eca7){:target="_blank"} []({{ page.website }}/u/mehmet-tekman/h/raceid-training-material){:target="_blank"}
Clustering 3K PBMCs with ScanPy {:target="_blank"} {:target="_blank"} []({{ page.website }}/workflows/run?id=921cab3e6faf30be){:target="_blank"} []({{ page.website }}/u/mehmet-tekman/h/clustering-3k-pbmcs-with-scanpy){:target="_blank"}
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Available tools

In this section we list all tools that have been integrated in the the single cell workbench. The list is likely to grow as soon as further tools and workflows are contributed. To ease readability, we divided them into categories.

Preprocessing

Formats QC Demultiplexing Mapping Quantification References
AnnData / Loom Suite CSV LOOM H5 AnnData Documentation
{% include tool.html id="crosscontamination_barcode_filter" label="Cross Contamination Barcode Filter" title="QC tool for inspecting raw count matrices and determining the level of contamination between neighbouring sequencing wells" %} CSV Freiburg Galaxy Team, 2019
{% include tool.html id="fastp" label="Fastp" title="Fast all-in-one preprocessing for FASTQ files" %} FASTA/Q Shifu et al. 2018{:target="_blank"}
{% include tool.html id="fastqc" label="FastQC" title="A quality control tool for high throughput sequence data" %} / {% include tool.html id="multiqc" label="MultiQC" title="MultiQC aggregates results from bioinformatics analyses into a single report" %} FASTQ Ewels et al. 2016{:target="_blank"}
{% include tool.html id="htseq-count" label="htseq-count" title="Tool for counting reads in features" %} BAM Anders et al. 2015{:target="_blank"}
Je Suite FASTA/Q BAM Filtering Girardot at al. 2016
UMI-tools Suite FASTQ Filtering Smith et al. 2017{:target="_blank"}
{% include tool.html id="RNA STAR" label="RNA STAR" title="Rapid spliced aligner for RNA-seq data, performs single-cell quantification only when used with featureCounts" %} FASTA/Q Filtering Dobin et al. 2013{:target="_blank"}
{% include tool.html id="RNA STAR Solo" label="RNA STAR Solo" title="Supports Droplet (Drop-seq, 10X) protocols, and can emulate CellRanger pipeline" %} FASTA/Q Filtering Dobin et al. 2013{:target="_blank"}
{% include tool.html id="bowtie2" label="Bowtie2" title="Fast and sensitive read alignment" %} FASTA/Q Filtering Langmead et al. 2012{:target="_blank"}
{% include tool.html id="hisat2" label="HISAT2" title="Hierarchical indexing for spliced alignment of transcripts" %} FASTA/Q Filtering Pertea et al. 2016{:target="_blank"}
{% include tool.html id="sailfish" label="Sailfish" title="Rapid Alignment-free Quantification of Isoform Abundance" %} FASTA/Q BAM Filtering Patro et al. 2014{:target="_blank"}
{% include tool.html id="alevin" label="Alevin" %} / {% include tool.html id="salmon" label="Salmon" title="Fast, accurate and bias-aware transcript quantification" %} FASTA/Q BAM Filtering Salmon Salmon Patro et al. 2017{:target="_blank"}
{% include tool.html id="scpipe" label="scPipe" title="Preprocessing pipeline for single cell RNA-seq. Also performs downstream analysis via Scater and SCRAN." %} FASTQ BAM Filtering Subread Subread Tian et al. 2018{:target="_blank"}
{% include tool.html id="featurecounts" label="FeatureCounts" title="Ultrafast and accurate read summarization program" %} BAM Subread Subread Liao et al. 2014{:target="_blank"}
{% include tool.html id="bwa" label="BWA" title="Software package for mapping low-divergent sequences against a large reference genome" %} FASTA/Q not splice-aware Li and Durbin 2009{:target="_blank"}, Li and Durbin 2010{:target="_blank"}
{: .table.table-striped .tooltable}

Downstream

Formats Filtering Normalisation Batch / Confounder Removal Clustering Embedding Lineage/Pseudotime Classification / Marker Description
SC3 Suite SCE Consensus K-means PCA Kiselev et al
ScanPy Suite AnnData CSV LOOM excel mtx umi-tools CPM Cell Cycle ComBat MNNCorrect BBKNN PCA leiden louvain PCA tSNE UMAP dendrogram PAGA Wolf at al. 2018
Scater Suite SCE SC3 CPM FPKM TPM PCA PCA tSNE UMAP PHATE diffmap McCarthy et al. 2017
Seurat Suite CSV 10X H5 Alevin Log-Normalise Centered-log Relative-counts SCTransform SNNAnchor SharedNN PCA tSNE UMAP Satija et al. 2015
RaceID Suite CSV SCSeq Library Size Linear CCcorrect (Cell cycle) k-means k-medians hclust PCA tSNE UMAP Fruchterman-Rheingold StemID FateID Herman et al. 2018
{% include tool.html id="table_compute" label="Table Compute" title="A tool to perform complex operations upon single or multiple tables using the pandas framework." %} CSV user-defined function user-defined function Freiburg Galaxy Team, 2019
{% include tool.html id="deseq2" label="DESeq2" title="Differential gene expression analysis based on the negative binomial distribution" %} CSV htseq-count summarizedexperiment DESeq2 Love et al. 2014{:target="_blank"}
{% include tool.html id="scpipe" label="scPipe" title="CelSeq2, etc. Uses Scater and SCRAN for downstream, that also performs pre-processing." %} CSV AnnData Tian et al. 2018
{: .table.table-striped .tooltable}

Suites Mentioned

Suite Name Tools
AnnData / Loom {% include tool.html id="anndata_export" label="Export" %}, {% include tool.html id="anndata_import" label="Import" %}, {% include tool.html id="anndata_inspect" label="Inspect" %}, {% include tool.html id="anndata_manipulate" label="Manipulate" %}, {% include tool.html id="modify_loom" label="Modify Loom" %}
Je {% include tool.html id="je_clip" label="Clip" %}, {% include tool.html id="je_demultiplex" label="Demultiplex" %}, {% include tool.html id="je_demultiplex_illu" label="Demultiplex Illumina" %}, {% include tool.html id="je_markdupes" label="MarkDuplicates" %}
UMI-tools {% include tool.html id="umi_tools_count" label="Count" %}, {% include tool.html id="umi_tools_dedup" label="Deduplicate" %}, {% include tool.html id="umi_tools_extract" label="Extract" %}, {% include tool.html id="umi_tools_group" label="Group" %}, {% include tool.html id="umi_tools_whitelist" label="Whitelist" %}
SC3 {% include tool.html id="sc3_calc_consens" label="Calculate Consensus" %}, {% include tool.html id="sc3_prepare" label="Prepare" %}, {% include tool.html id="sc3_calc_transfs" label="Calculate Transformations" %}, {% include tool.html id="sc3_calc_biology" label="DiffExp" %}, {% include tool.html id="sc3_estimate_k" label="Estimate" %}, {% include tool.html id="sc3_calc_dists" label="Calculate Distances" %}, {% include tool.html id="sc3_kmeans" label="K-means" %}
ScanPy {% include tool.html id="scanpy_read_10x" label="Read 10X" %}, {% include tool.html id="scanpy_scale_data" label="Scale Data" %}, {% include tool.html id="scanpy_find_cluster" label="Find Cluster" %}, {% include tool.html id="scanpy_run_pca" label="Run PCA" %}, {% include tool.html id="scanpy_run_tsne" label="Run tSNE" %}, {% include tool.html id="scanpy_run_umap" label="Run UMAP" %}, {% include tool.html id="scanpy_compute_graph" label="Compute Graph" %}, {% include tool.html id="scanpy_find_variable_genes" label="Find Variable Genes" %}, {% include tool.html id="scanpy_normalise_data" label="Normalise Data" %}, {% include tool.html id="scanpy_filter_genes" label="Filter genes" %}, {% include tool.html id="scanpy_find_markers" label="Find Markers" %}, {% include tool.html id="scanpy_filter_cells" label="Filter Cells" %}, {% include tool.html id="scanpy_parameter_iterator" label="Parameter Iterator" %}
Scater {% include tool.html id="scater_create_qcmetric_ready_sce" label="Calculate QC Metrics" %}, {% include tool.html id="scater_filter" label="Filter" %}, {% include tool.html id="scater_normalize" label="Normalize" %}, {% include tool.html id="scater_plot_dist_scatter" label="Plot Scatter" %}, {% include tool.html id="scater_plot_exprs_freq" label="Plot Expression Frequency" %}, {% include tool.html id="scater_plot_pca" label="Plot PCA" %}, {% include tool.html id="scater_plot_tsne" label="Plot tSNE" %}
Seurat {% include tool.html id="seurat_read10x" label="Read 10X" %}, {% include tool.html id="seurat_run_pca" label="Run PCA" %}, {% include tool.html id="seurat_scale_data" label="Scale Data" %}, {% include tool.html id="seurat_filter_cells" label="Filter Cells" %}, {% include tool.html id="seurat_find_markers" label="Find Markers" %}, {% include tool.html id="seurat_dim_plot" label="Dim. Plot" %}, {% include tool.html id="seurat_normalise_data" label="Normalise Data" %}, {% include tool.html id="seurat_create_seurat_object" label="Create Seurat Object" %}, {% include tool.html id="seurat_export_cellbrowser" label="Export CellBrowser" %}, {% include tool.html id="seurat_run_tsne" label="Run tSNE" %}, {% include tool.html id="seurat_find_variable_genes" label="Find Variable Genes" %}, {% include tool.html id="seurat_find_clusters" label="Find Clusters" %}
RaceID {% include tool.html id="raceid_clustering" label="Clustering" %}, {% include tool.html id="raceid_filtnormconf" label="Filter Normalize Confounder" %}, {% include tool.html id="raceid_trajectory" label="Trajectory" %}, {% include tool.html id="raceid_inspectclusters" label="Inspect Clusters" %}, {% include tool.html id="raceid_inspecttrajectory" label="Inspect Trajectory" %}
{: .table.table-striped .tooltable}

Contributors