z626093820
z626093820
> You can also pass a `Nominal` scale with an explicit ordering: > > ```python > ( > so.Plot(penguins, x="island",y='bill_length_mm', color="species") > .add(so.Range(), so.Est(errorbar="sd"), so.Dodge()) > .add(so.Dot(pointsize=2), so.Jitter(0.2), so.Dodge()) >...
> Hi!I think we might fall in the same hole, I also met this problem but for me the case is I can't get the correct gene name (in my...
python -m jcvi.formats.gff bed --type=gene --key=ID in.gff -o out.bed 是不是应该将type改为mRNA，gene，transcript，一个基因有好几个CDS，为什么单独提取所有CDS
> > python -m jcvi.formats.gff bed --type=gene --key=ID in.gff -o out.bed > > 是不是应该将type改为mRNA，gene，transcript，一个基因有好几个CDS，为什么单独提取所有CDS > > 因为我的gff文件里只有cds信息 提取gene或者mrna的话就会提示Extracted 0 features。 我发现之前这么多warning是因为fasta的基因名和bed文件第四列不符合，修改之后虽然warning数量减少了 但还是有一个not in bed file，后续得到这样的结果： WARNING k141_1388814 not in anme_10_93.bed...
> x2 It would be great to use this tool for cafe v5 output! x2？，is this a software?would you tell me the full name
假如我预测的是uorf,在结果文件里这个Psites_frame0_RPKM计算的是uorf inframe reads （0位）的表达量吗，而不是annotated orf的表达量。请问我的理解是正确的吗？我看结果的表格里也记录了annotated的位置和信息,谢谢您！！ 
> 如果你把row_cluster和col_cluster设置成False，还会报错吗？你这里面虽然没有NAN，但是，对这个数据库进行pivot之后，就可能会有NaN了。比如，pivot到行：Geneid，列：variable，value：value之后的新数据库，里面应该会有NaN。你把row_cluster和col_cluster设置成False后，应该就不会报错 您好，谢谢，可以出图了。不过画出来的图为什么没有黑色边框，和事例中的不同，谢谢  例子：  我的代码： cm = DotClustermapPlotter(data=dfbleedingckx2,x='Geneid',y='variable',value='value',c='value',s='value',row_cluster=False,col_cluster=False,spines=True,show_colnames=True,show_rownames=True) cm.ax_heatmap.grid(which='minor',color='white',linestyle='--',linewidth=1)
> You can get the `ax` object and do whatever you want, see: [#116 (comment)](https://github.com/DingWB/PyComplexHeatmap/issues/116#issuecomment-3130450916) Is there any parameter that can keep the x-axis arrangement of the original df? When...
> Please provide an example for me to reproduce this issue; the version of PyComplexHeatmap should also be reported. Sorry, I got row_cluster and row_dendrogram wrong, I only used row_dendrogram=False...