Open wang0430 opened 1 year ago
Raw count or data normalized with library size, which one do you use as input?
我使用的是sample@assays$SCT@counts,我使用seurat的SCTransform函数对原始spatial数据进行了处理,然后用了SCT里面的counts
font{
line-height: 1.6;
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ul,ol{
padding-left: 20px;
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谢谢您的提醒,我等会尝试一下给您反馈,麻烦啦
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Date
3/17/2023 15:49
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Re: [xzhoulab/SPARK] result (Issue #8)
我自己试过无论什么方法,例如SpatialDE还是SPARK-gaussian或SPARK-X,你只要用raw count进去它的基因数量都很大
所以我觉得这里应该要用nomalized过后的数据进去作为SPARK-X的输入
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主题: Re: [xzhoulab/SPARK] result (Issue #8)
@.**@.,我使用seurat的SCTransform函数对原始spatial数据进行了处理,然后用了SCT里面的counts
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font{
line-height: 1.6;
}
ul,ol{
padding-left: 20px;
list-style-position: inside;
}
***@***.***$data),但是获得的空间变异基因还是特别多,调整后的P值设置为0.01,仍有1W多基因。
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---- Replied Message ----
From
Kelvin ***@***.***>
Date
3/17/2023 15:49
To
***@***.***>
Cc
***@***.***>
,
***@***.***>
Subject
Re: [xzhoulab/SPARK] result (Issue #8)
我自己试过无论什么方法,例如SpatialDE还是SPARK-gaussian或SPARK-X,你只要用raw count进去它的基因数量都很大
所以我觉得这里应该要用nomalized过后的数据进去作为SPARK-X的输入
←
@.***
------------------ 原始邮件 ------------------
发件人: "xzhoulab/SPARK" @.***>;
发送时间: 2023年3月17日(星期五) 下午3:47
@.***>;
@.**@.>;
主题: Re: [xzhoulab/SPARK] result (Issue #8)
@.**@.,我使用seurat的SCTransform函数对原始spatial数据进行了处理,然后用了SCT里面的counts
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Hello, Recently, I tried the SparkX developed in your laboratory, and found that its computing efficiency is much higher than Spark. However, I saw the article that SVG was extracted from normal brain tissues of mice, and there were only more than 200 genes with the adjusted p-value was 0.01, but when i tried it, there were more than 10000 genes with the adjusted p-value was 0.01. I looked at some SVGs, and found that they did not show a spatial trend, and there were no errors reported during the operation process. Now I do not know where the problem occurred, and I wonder if I can help to look at it? Good luck! Look forward to your reply!