Introduction to Chipster (2025)
9:47
Introduction to Chipster (2025)
Conversion of microarray input tables to Chipster format
3:06
Conversion of microarray input tables to Chipster format
scRNA-seq -Integrated analysis: Introduction, preprocessing and combining samples (Seurat v5)
2:52
scRNA-seq -Integrated analysis: Introduction, preprocessing and combining samples (Seurat v5)
scRNA-seq -Integrated analysis: Aligning samples and clustering
6:14
scRNA-seq -Integrated analysis: Aligning samples and clustering
scRNA-seq -Integrated analysis: Conserved markers and differentially expressed genes (Seurat v5)
5:03
scRNA-seq -Integrated analysis: Conserved markers and differentially expressed genes (Seurat v5)
scRNAseq: Pseudobulk analysis
4:00
scRNAseq: Pseudobulk analysis
8 Visium data (2024): Integration with single-cell RNA-seq reference data
5:02
8 Visium data (2024): Integration with single-cell RNA-seq reference data
7 Visium data (2024): Subsetting out anatomical regions
1:14
7 Visium data (2024): Subsetting out anatomical regions
6 Visium data (2024): Visualizing gene expression and identifying spatially variable genes
5:56
6 Visium data (2024): Visualizing gene expression and identifying spatially variable genes
9 Visium data (2024): Analysis with multiple samples
4:27
9 Visium data (2024): Analysis with multiple samples
5 Visium data (2024): Clustering
3:16
5 Visium data (2024): Clustering
4 Visium data (2024): Normalization and PCA
4:10
4 Visium data (2024): Normalization and PCA
3 Visium data (2024): Filtering
1:12
3 Visium data (2024): Filtering
2 Visium data (2024): Setup and quality control
3:19
2 Visium data (2024): Setup and quality control
scRNA-seq: Remove background contamination with CellBender
11:44
scRNA-seq: Remove background contamination with CellBender
8 Visium data: Subset and integrate with single-cell data (update, August 2023)
4:38
8 Visium data: Subset and integrate with single-cell data (update, August 2023)
5b. Trimming and filtering single-end reads (Ion Torrent data)
11:19
5b. Trimming and filtering single-end reads (Ion Torrent data)
scRNA-seq: Quality control and filtering cells (update, July 2023)
15:56
scRNA-seq: Quality control and filtering cells (update, July 2023)
5a. Filter contigs and remove identical sequences
3:57
5a. Filter contigs and remove identical sequences
4b. Converting VSEARCH contigs for Mothur analysis
1:58
4b. Converting VSEARCH contigs for Mothur analysis
4a. Expected error filtering with VSEARCH
3:47
4a. Expected error filtering with VSEARCH
3. Combine paired reads to contigs with VSEARCH
7:25
3. Combine paired reads to contigs with VSEARCH
scRNA-seq: Normalize gene expression values with SCTransform
5:36
scRNA-seq: Normalize gene expression values with SCTransform
scRNA-seq: SingleR annotations
4:06
scRNA-seq: SingleR annotations
scRNA-seq: Extract information from Seurat object
7:06
scRNA-seq: Extract information from Seurat object
scRNA-seq: Quality control and filtering cells (update, June 2023)
15:05
scRNA-seq: Quality control and filtering cells (update, June 2023)
9 Visium data: Identifying cell types using deconvolution
5:31
9 Visium data: Identifying cell types using deconvolution
8 Make a phyloseq object for ASV data in Chipster
7:51
8 Make a phyloseq object for ASV data in Chipster
6 Make an ASV table and remove chimeras with DADA2
8:25
6 Make an ASV table and remove chimeras with DADA2
7 Assign Taxonomy with DADA2
6:07
7 Assign Taxonomy with DADA2