2018年1月5日 · if LogFC if 0.05, then your actual fold change is 1.0353... which is effectively 1, or rather, no significant change. To convert a logFC value, simply use it as the exponent of two: 2 …

2023年8月26日 · Increasing log2(?)-FC from 0.5 to 2 will diminish the number of genes, not increase. Most tend to go with logFC of 0.26-0.58 which represents a FC of 1.2 and 1.5 …

2020年5月30日 · If i take logFc > 1 , there is a significant number . But how can i say that those genes are differentially expressed, they can be in their normal range of expression. Just …

2022年5月18日 · If you don’t have access to the code and someone else ran in it then you can try the following: use the normalized table, take the mean for each group to get 2 vectors, log2 …

2023年3月13日 · This is the correct answer. MA plots were initially developed for microarrays, where M is a symbol for log ratio (or log2 fold change) and A is the mean average of log …

2022年8月1日 · I’ve used this metric, but more recently switched over to using -log(raw p value)*sign(logFC) because I generally have a lot of ties in the adjP values (which leads to …

2021年12月1日 · Hello, Previously when using fgsea I have ran it using genes based on a composite score: -log10(padj) * log2fc.

2021年6月28日 · This is available under lFC.Av, but under logFC, I get back another value. According to the test.results definition, it is the "log fold change estimated by fitting the given …

2018年1月5日 · Posted by u/AnonBiomed - 5 votes and 7 comments

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