8/10/2023 0 Comments Harmony health studioYou can run Harmony with functions from the MUDAN package. SeuratObj <- RunUMAP(seuratObj, reduction = "harmony") seuratObj <- RunHarmony(seuratObj, "dataset") In downstream analyses, use the Harmony embeddings instead of PCA.įor example, run Harmony and then UMAP in two lines.Run Harmony with the RunHarmony() function.You'll only need to make two changes to your code. You can run Harmony within your Seurat workflow. My_harmony_embeddings <- HarmonyMatrix(normalized_counts, meta_data, "dataset") Seurat Harmony will scale these counts, run PCA, and finally perform integration. You can also run Harmony on a sparse matrix of library size normalized expression counts. My_harmony_embeddings <- HarmonyMatrix(my_pca_embeddings, meta_data, "dataset", do_pca=FALSE) Normalized gene matrix Harmony is packaged with a small dataset library(harmony) To input your own low dimensional embeddings directly, set do_pca=FALSE. The Harmony algorithm iteratively corrects PCA embeddings. Quick StartĬheck out this vignette for a quick start tutorial. We made it easy to run Harmony in most common R analysis pipelines. Installation may include compiling C++ code from source, so it can take a few minutes. To run Harmony, open R and install directly from github using the following commands: library(devtools) Harmony has been tested on Linux, OS X, and Windows platforms. Please consult the DESCRIPTION file for more details on required R packages. Harmony has been tested on R versions >= 3.4. Fast, sensitive and accurate integration of single-cell data with HarmonyĬheck out the manuscript in Nature Methods:įor Python users, check out the harmonypy package by Kamil Slowikowski.
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