Open the Project Achilles gene essentiality scores under the preloaded datasets section. By default, values in the heat map are mapped to colors using the minimum and maximum of each row independently.
Median Absolute Deviation (MAD)
Click the tools icon
and select "Create Calculated Annotation".
Enter "MAD" for
the "Annotation name".
Enter "MAD()" for "Formula" and
click "OK".
A new row annotation named "MAD" will appear to
the right of the heat map.
Show only the top 500 most variable genes by the median absolute
deviation
Click the filter icon
.
Click the "Add" button and set the field name to "MAD".
Click
"Switch to top N filter" and enter "500" for "N". Note that 523
rows are now shown because of ties in the median absolute
deviation.
Click the tools icon
and select "Hierarchical Clustering". Change "Cluster" to "Rows and
columns". Click "OK" to run the analysis.
Do haematopoietic
cell lines cluster together? Hover over the primary_site
annotations to highlight cell lines from the same primary site. You
can dynamically cut the dendrogram by dragging the dashed line at
the top of the dendrogram.
Hierarchical clustering
recursively merges objects based on their pair-wise distance.
Objects closest together are merged first, objects furthest apart
are merged last. The result is a tree structure, referred to as a
dendogram, where the leaf nodes represent the original items and
internal (higher) nodes represent the merges that occurred. Click here
for a more detailed description of the hierarchical clustering
algorithm and here
for a comparison of the Pearson and Spearman correlation methods.
Click the fit to window icon to fit compress the heat map. Click to return to the normal heat map size.
Remove Row FilterClick the filter icon and delete the median absolute deviation filter to show all rows.
Remove DendrogramsRight-click on the column dendrogram and select "Delete". Do the same for the row dendrogram.
Sort RowsClick the MAD row annotation header in the heat map once to sort the heat map in ascending order by the median absolute deviation. Click it again to sort the heat map in descending order. Note that you can shift-click to sort multiple columns simultaneously. Alternatively, you can click to open a sort dialog.
Search Results To Top
Enter "BRAF" in the row search box.
Click
to bring the matches to the top of the heat map.
Double-click on BRAF row to sort by dependency score.
Search columns for "skin".
Do skin cell lines seem to be
more dependent on BRAF than cell lines from other lineages?
You can optionally limit your search to within a field by typing
the field name followed by a colon ":" and then the term you are
looking for.
Click the tools icon
and select "Nearest Neighbors". Click "OK" to run the analysis.
A new row annotation named "Pearson correlation" will appear.
What genes correlate with BRAF?
Select the first three rows in order to select the top 3 most correlated genes with BRAF and all samples. Click the chart icon . Change the chart type to "row scatter" to assess the relationships between BRAF, FXR2, and ZNF781 simultaneously.
Append Mutations
Click
to bring up the file open window.
Check "Append rows to
current dataset" and select the file CCLE Mutations dataset. Change
"Current dataset annotation name" and "New dataset annotation name"
to "id" to match the ids in the existing dataset with the id in the
mutational dataset. Scroll down to see the mutational data.
Click
to open the color key.
Click the "Synonymous" check box to
visually hide synonymous mutations (note the matrix values are left
unchanged).
Enter "BRAF" in the row search box.
Click
to bring the matches to the top of the heat map. Double-click to
sort the heat map by the BRAF dependency score. Select the seven
cell lines that have a dependency score less than or equal to -2.
Right-click and select "Annotate Selection". Enter "BRAF_sensitive"
for "Annotation name" and "y" for "Annotation value".
Enter "CCLE" in the row search box to select the CCLE mutation
data.
Right-click on the columns and select "Clear
Selection" to clear the column selection.
Click the tools
icon
and select "New Heat Map". A new tab will open that contains the
selected subset of the heat map.
Click the tools icon
and select "Marker Selection". Change "Metric" to "Fisher Exact
Test". Change "Field" to "BRAF_sensitive". Set "Class a" to
"BRAF_sensitive" and "Class b" to "". Set "Grouping value" to "4"
to group missense, splice site, frame shift, and nonsense mutations
together and no mutation, synonymous, in-frame indels, and other
non-synonymous mutations together (Click
to see the numerical values used to encode mutation type). Click
"OK" to run the analysis.
A new row annotation named
"Fisher Exact Test" will appear.
What mutations distinguish
BRAF sensitive cell lines from the other cell lines?