This repo records the notebooks that are used in the off-cloud analysis of the targeted APA study of TCGA samples.
Notebooks that related to result reproduction are mostly in
analysis-notebooks. For details, please see the README.md inside each
folder.
<a href=https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4903-7 , target=_blank> Xue Z, Warren RL, Gibb EA, MacMillan D, Wong J, Chiu R, et al. Recurrent tumor-specific regulation of alternative polyadenylation of cancer-related genes. BMC Genomics. 2018;19:536
Most of the codes are run in jupyter notebooks format. Most of the packages used
are listed in eda_import.py. Some extra include pysam, etc.
To get started, you may not need all the packages. I used Miniconda to manage python environments. Try getting start with
conda create -p venv -y python=3 pandas jupyter matplotlib scikit-learn
source activate venv
To run jupyter notebook server
jupyter notebook --no-browser --ip 0.0.0.0
The data used as input to the off-cloud analysis are produced by on-cloud run with tasrkleat. All (i.e. 10K-TCGA-sample run) are generated with tasrkleat-v0.1 except the benchmark part which used tasrkleat-0.1.1 with adjustment in the reads2genome alignment step. The reads2genome alignment step doesn't affect the results of KLEAT, but may have an effect for the other tools.
If you have any question, please ask by opening a new issue.