Skip to content

Latest commit

 

History

History
82 lines (59 loc) · 4.22 KB

index.md

File metadata and controls

82 lines (59 loc) · 4.22 KB
Raw

Overview

Using the Mission Bio Tapestri Platform, reagents and the tapestriR package, we explore Single Nucleotide Variants (SNVs), protein expression and Copy Number Variations (CNVs), including loss of heterozygosity (LOH), which plays a large role in cancer evolution and contributes to cancer heterogeneity. More details can be found in the [Application Note] (https://missionbio.com/protein-reva-application-note-form/).

The tapestriR package is an exploratory data analysis tool. Refer to the README.md file for instructions on how to install the tapestriR package. The latest version can be found at https://github.com/MissionBio/tapestriR.

Here we show a few example methods to normalize, cluster and visualize multi-omics data. It is left to the user to explore different methods avaliable in the R community to better explore and interpret their data.

Loading Data

The main value of this package is to load data from these sources and create an R object for use in additional analysis and visualiation.

  • Tapestri H5 file - enable analysis of DNA variants, CNV, and protein expression
  • loom file - enables analysis of DNA variants only
  • Exported data from Tapestri Insights - enables analysis of DNA variants only

Objects

The multiomics object is a structured way to store all of the raw and normalized data as well as the analysis performed on these data. The object ensures that all of the multiomics data is properly aligned for cells and features (variants, protein counts...) of the cells.

  • row = cells
  • columns = features

Multiomics Object

A multiomics object stores a group of assays performed on 1 or more samples.

<root>
+-- metadata                          Experiment meta data. Required to have experiment_name
+-- assays
          +-- dna_variants            DNA Assay object
          +-- dna_read_counts         DNA read counts Assay object
          +-- protein_read_counts     Protein Read counts Assay object
          +--
+-- cell_annotations                  Annotation of each cell, Required to have barcode and sample name columns

Assay Object

an Assay object stores raw and processed data for 1 or more samples.

  • An assay can multiple data layers and analysis layers
  • data layers must have same cell barcodes and features
  • analysis layers must have same cell barcodes, but can have different features ** Typically store clustering and dimension reduction values in the analysis layers

dna_variants Assay Object

<root>
+-- assay_name                        Name of Assay. Same as one of the layers in the assays slot of Multiomics object
+-- data_layers                       1 or more layers of data. each layer must have same dimensions and matching cell barcodes (rows) and features (columns names) 
                +--NGT                Genotype layer. 0=WT, 1=HET, 2=HOM, 3=unknown
                +--AD
                +--GQ
                ...                   additional layers can be added, must have same cell barcodes and features 
+-- analysis_layers                   Additional layers after data is processed. Must have same number of cells (rows) 
                    +--               Examples: umap projection of each cell, or kmeans cluster labels
+-- feature_annotations               Annotations of features. Must have id column.
+-- cell_annotations                  Annotations of cells. Required to have barcode and sample name columns

protein_read_counts Assay Object

<root>
+-- assay_name                        Name of Assay. Same as one of the layers in the assays slot of Multiomics object
+-- metadata                          Assay meta data
+-- data_layers                       1 or more layers of data. each layer must have same dimensions and matching cell barcodes (rows) and features (columns names) 
                +--read_counts        raw read counts per protein
                +--normalized         normalized read counts
+-- analysis_layers                   Additional layers after data is processed. Must have same number of cells (rows) 
                    +--
+-- feature_annotations               Annotations of features. Must have id column.
+-- cell_annotations                  Annotations of cells. Required to have barcode and sample name columns