changing default color of cells - st.pl.cluster_scatter

[vkjain006]

Hi,

I am new to analyzing data via scanpy/squidpy and stlearn. I have been using Stlearn xenium tutorial to analyze some xenium spatial data. I have been able to add cell type annotation as separate column in my adata.obs[]

I am using below mention quote to generate spatial plot

colors = ['skyblue','cyan','lightskyblue','steelblue','deepskyblue', 'lightblue','turquoise','dodgerblue','lime','lightsteelblue', 'deeppink','cornflowerblue','royalblue','red','orangered', 'lavender','tomato','green','blue','mediumpurple','hotpink', 'slateblue','rebeccapurple','darkslateblue','yellowgreen', 'peru','darkblue','gray','mediumvioletred','olive','midnightblue', 'indigo', 'yellow','darksalmon','blueviolet']

from matplotlib.colors import LinearSegmentedColormap

cmap1 = LinearSegmentedColormap.from_list("mycmap", colors) cmap1

st.pl.cluster_plot(adata,use_label="celltype", image_alpha=0,size=5,

zoom_coord=[1500,8000,2500,5000],

               show_color_bar=True,cmap=cmap1)

Code generates the plot, but doesn't change colors of cells. It still shows default colors.

Can you please share how I can give a specific color to each cell type and then generate a plot.

Also I would like to use same color scheme when I would do further down stream analysis like trajectory and cell cell interaction analysis.

Thank you so much.

[duypham2108]

Sorry for the delay a bit. You can change the colors in adata.uns['celltype_colors]. I'm not sure it works with color name, but if not, you can use hex code instead

[vkjain006]

Thanks for your reply.

I am new to python.

When you say change colors in adata.uns['celltype_colors'] , can you please share how would the code for it be like. I want to change color by celltype. What I have is something like this where I define color for each cell type.

palette = { "Neuron-1":"skyblue", "Endothelial-1":"cyan", "Neuron-2":"lightskyblue","Neuron-3":"steelblue", "Neuron-4":"deepskyblue","Neuron-5":"lightblue", "Neuron-6":"turquoise","Neuron-7":"dodgerblue", "NSPC-1":"lime","Neuron-8":"lightsteelblue", "OPC-1":"deeppink","Neuron-9":"cornflowerblue", "Neuron-10":"royalblue","Astrocyte-1":"red", "Astrocyte-2":"orangered","Neuron-11":"lavender", "Astrocyte-3":"tomato","NSPC-2":"green", "Neuron-12":"blue","Neuron-13":"mediumpurple", "OPC-2":"hotpink","Neuron-14":"slateblue", "Neuron-15":"rebeccapurple","Neuron-16":"darkslateblue", "NSPC-3":"yellowgreen","Monocyte":"peru", "Neuron-17":"darkblue","Cajal-Retzius-cells":"gray", "Neuron-18":"mediumvioletred","NP-PPP":"olive", "Neuron-19":"midnightblue","Neuron-20":"indigo", "VLMC":"yellow","Astrocyte-4":"darksalmon", "Neuron-21":"blueviolet", }

Now how can I add this info to adata.uns['celltype_colors']

This is my first time analyzing xenium spatial data. There are lot of new analysis to do. One of them is to merge/integrate different tissue sections for xenium data. At some point I need to compare differences between cell types from different tissue sections. I have been able to run squidpy/stlearn on each tissue section individually.

I may have more questions later as I would continue to work on this data. Thanks for all your help.

[duypham2108]

You need to look at the order of clusters in this adata.obs.celltype.cat.categories and then you replace the list of colors to adata.uns['celltype_colors'] that follows the order of the clusters.

Example:

# You can try with your color name first. If it doesn't work, then use hex code like this
adata.uns['celltype_colors'] = ['#87CEEB','#00FFFF',...]