
Repository containing all the code necessary for reproducing the paper "Filtering cells with high mitochondrial content removes viable metabolically altered malignant cell populations in cancer single-cell studies" (Yates, Kraft, and Boeva). First, you will have to create a conda environment with the correct requirements. You will find a YAML file with the environment used to run the analysis. If you do not have Anaconda, you can download it here. You can create then a conda environment from the file using conda env create --name mtrna-env --file mtrna-env.yml Activate the conda environment with conda activate mtrna-env The first step of the analysis consists in downloading the data from the original source and transforming it so that it is saved as an .h5ad file to preprocess it. Details are given in preprocessing. Then, you can run the notebooks in the order indicated. Placeholders must be replaced in the files - description of the placeholders can be found in notebooks.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
