docs: Update 4_1__Hosted Tutorials.mdx (#7356)

frontend/doc-site/04__Analyze Public Data/4_1__Hosted Tutorials.mdx

@@ -14,39 +14,39 @@ CELLxGENE Explorer's user interface organizes single cell data similarly to how
 
 **Key Concepts**: User Interface Explanation
 
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 ## Examining Categorical Metadata
 
 Categorical metadata (such as tissue of origin or cell type) can be used in a number of ways within Explorer including coloring embedding plots (i.e. color UMAP by cell type), looking at cell counts, within a categorical metadata field, making selections of cells or viewing the interaction between different categorical metadata fields.
 
 **Key Concepts**: Categorical Metadata, Selecting Cells by Category (i.e. cell type), Interaction Between Categorical Metadata Fields
 
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 ## Find Cells Where a Gene is Expressed
 
 Numerical metadata (such gene expression features or QC metrics such as number of genes) can be examined on the embedding plot and be used to filter and select cells. Additionally tools like the clip tool can give us control over how these attributes are displayed on the embedding plot.
 
 **Key Concepts**: Numerical Metadata, Cell Filtering and Selection, Interaction Between Numerical Metadata, Categorical Metadata Fields
 
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 ## Selecting and Subsetting Cells
 
 Explorer allows for the complex selection of cells via selection directly on the embedding, gene expression cutoffs, and based on categorical metadata attributes.
 
 **Key Concepts**: Categorical Metadata Selection, Numerical Metadata Selection, Complex Selection (combining selection methods)
 
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 ## Compare Expression of Multiple Genes
 
 Explorer allows you to compare the expression of multiple genes via bivariate plots.
 
 **Key Concepts**: Gene Expression, Co-expression, Cell Selection, Subsetting
 
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 ## Using Gene Sets to Learn About Cell Population Functional Characteristics
 
@@ -58,14 +58,14 @@ _Listed below is a comma separated gene set list for use with this tutorial._
 
 ACAA1, ACAA2, ACADL, ACADM, ACADS, ACADSB, ACADVL, ACAT1, ACAT2, ACOX1, ACOX3, ACSL1, ACSL3, ACSL4, ACSL5, ACSL6, ADH1A, ADH1B, ADH1C, ADH4, ADH5, ADH6, ADH7, ALDH1B1, ALDH2, ALDH3A2, ALDH7A1, ALDH9A1, CPT1A, CPT1B, CPT1C, CPT2, CYP4A11, CYP4A22, ECHS1, ECI1, ECI2, EHHADH, GCDH, HADH, HADHA, HADHB
 
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 ## Find Marker Genes
 
 Explorer allows you to find marker genes between selected cell populations.
 
 **Key Concepts**: Gene Expression, Differential Expression, Cell Selection, Subsetting
 
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 Note: You can find more information <NextLink href="/docs/04__Analyze%20Public%20Data/4_3__Algorithms%20and%20Ontologies#differential-expression">here</NextLink> about how our differential expression is calculated. In brief, we use a Welch's t-test. While we are aware that single cell data does not always meet the assumptions imposed by this test, we utilize it because it performs well at identifying the _most_ differentially expressed genes, and this is what our feature returns.