Spatial notebook 1: intro text

components/dictionary.txt

@@ -84,6 +84,7 @@ curation
 customizable
 customization
 customizations
+CytAssist
 cytometry
 cytotoxic
 cytotoxicity
@@ -148,9 +149,11 @@ FASTQ
 FastQC
 FCS
 FDR
+FFPE
 fgsea
 fibroblast
 fibrotic
+fiducial
 fiducials
 Figshare
 FLI
@@ -431,6 +434,8 @@ SNE
 snRNA
 Soneson
 SOX
+SpatialExperiment
+SPE
 SRA
 Srivastava
 SRP

scRNA-seq/04-dimension_reduction_scRNA.Rmd

@@ -25,7 +25,7 @@ Visualizing highly dimensional data is a common challenge in genomics, and espec
 The expression of every gene we look at is another dimension describing a sample.
 When we also have hundreds or thousands of individual samples, as in the case of single-cell analysis, figuring out how to clearly display all of the data in a meaningful way is difficult.
 
-A common practice is to common to use dimension reduction techniques so all of the data is in a more manageable form for plotting, clustering, and other downstream analyses.
+A common practice is to use dimension reduction techniques so all of the data is in a more manageable form for plotting, clustering, and other downstream analyses.
 
 ## Set Up
 
@@ -45,7 +45,7 @@ The data we will be using for this module comes from a a 10x Genomics data set o
 The data was generated with the 10Xv3.1 chemistry, and processed with Cell Ranger and 10x Genomics standard pipeline.
 
 
-There are a variety of files that you will often see as part of the standard output from Cell Ranger, which are described in detail in [10x Genomics documentation](https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/output/overview).
+There are a variety of files that you will often see as part of the standard output from Cell Ranger, which are described in detail in [10x Genomics documentation](https://www.10xgenomics.com/support/software/cell-ranger/latest/analysis/outputs/cr-outputs-overview).
 We have included some of these in the `data/hodkins/cellranger` directory, including the `web_summary.html` file that includes some similar QC statistics to those we generated with `alevinQC`.
 The main file we will be working with are the feature by barcode matrices.
 Cell Ranger does some filtering on its own, but we will start with the raw data.