Add utility functions for PPI analysis and functional enrichment visualization #1
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不要到处copy-paste代码，像最新的这个upsetplot，调用aplotExtra即可。 |
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其它代码，也检查确认，尽量调用，不要copy。 如果是没有export的函数，可以用 |
R/PPI_utils.R
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| ppi_subset <- function(ppi_obj, n = NULL, score_cutoff = 0.7) { | ||
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| library(igraph) |
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在R包中的函数里不要library，而是相应的在上面的Rd中用#'@importFrom igraph degree induced_subgraph这种写法，然后在DESCRIPITION文件中的import里去声明igraph等相应你要导入的包
R/PPI_utils.R
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| #' @param score_cutoff Minimum edge score to keep. Default is 0.7. | ||
| #' | ||
| #' @return A subgraph of the original PPI network | ||
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R/PPI_utils.R
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| stop("Edges must have a 'score' attribute.") | ||
| } | ||
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| ppi_filtered <- subgraph.edges(ppi_obj, eids = E(ppi_obj)[score >= score_cutoff], delete.vertices = TRUE) |
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这个score是哪个向量？前面的E(ppi_obj)$score？没有定义的话会报错的
R/PPI_utils.R
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| # 1. extract top n pathways | ||
| enrich_df <- enrich_obj@result %>% | ||
| dplyr::arrange(p.adjust) %>% |
R/gglollipop.R
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| plot_title = NULL) | ||
| { | ||
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| library(ggplot2) |
R/gglollipop.R
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| df, | ||
| aes(RichFactor, stats::reorder(Description, RichFactor)) | ||
| ) + | ||
| geom_segment(aes(xend = 0, yend = Description)) + |
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ggplot2语法封装进函数里，也是不能直接用交互式的语法，参考https://github.com/YuLab-SMU/SVP/blob/main/R/methods-plot.R#L155
R/gglollipop.R
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| } | ||
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| df <- df %>% | ||
| arrange(p.adjust) %>% |
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tidyverse框架，在函数内部的使用.data$p.adjust，其他地方我没有发现的也得自己调整
R/gglollipop.R
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| df$RichFactor <- df$RichFactor %>% round(digits = 2) | ||
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| label_wrap <- function(labels) str_wrap(labels, width = text.width) |
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这个str_wrap用yulab.utils::str_wrap代替，stringr软件包太多依赖，有些平台很难安装下载，开发时尽量考虑不调用它，而是用base一些函数自己写一些基础功能
R/gglollipop.R
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| p <- ggplot( | ||
| df, | ||
| aes(RichFactor, stats::reorder(Description, RichFactor)) |
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这个写法也是不行的，RichFactor参考下面的，stats::reorder(Description, RichFactor)参考https://github.com/YuLab-SMU/ggtree/blob/devel/R/geom_tiplab.R#L162-L170
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lollipop图，用 代码尽量简单，能调用我们已有代码的尽量调用，这样方便维护。 |
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lollipop已进一步使用enrichplot完善 |
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其它的代码也要查一下，不要到处copy。你看我公众号，也知道以前有个人，到处copy了，要建立良好的习惯。 |
use 'aplotExtra:::get_all_subsets_items' as default for getting the intersection result
老师好，目前函数能调用的都调用了。之前是因为upset_plot还没有merge，所以就先source()源码拿来测试了，现已删除，并在新示例中改为aplotExtra::upset_plot()进行调用。 |
PPI_utils.R now includes 'PPI_subset()' and 'getPieData()' functions:
'PPI_subset()' : Subsets STRING PPI network data based on a selected gene list and confidence score.
'getpiedata()': Generates summary data for pie chart visualization based on PPI results.
gglollipop.R now includes 'gglollipop()':
'gglollipop()' : Generates lollipop plots for enrichment results.