This repository contains the source code for analysis for analysis of TEX, 5-CAP-PD and 3-PD experiments.
- Install required python packages:
pip install -r requirements.txt - Get required metadata:
- In directory data run:
get_data.sh - Alternatively download manually the following files to data directory:
- knownGene.hg19.txt.gz - http://hgdownload.cse.ucsc.edu/goldenpath/hg19/database/knownGene.txt.gz
- kgXreg.hg19.txt.gz - http://hgdownload.cse.ucsc.edu/goldenpath/hg19/database/kgXref.txt.gz
- In directory data run:
- hmm_frag_fit.py - Fits a 2-state Gaussian HMM to each transcript
- usage:
hmm_frag_fit.py [-norm_type CONTROL] [-non_discrete] EXP_NAME bigwig1 [bigwig2 ...]- EXP_NAME: Name of experiment (input type)
- bigwigs: bigwig files of RNA-seq (both treated and control) as input
- -norm_type NORM_TYPE: Substring appears in the control files
- -non_discrete: Whether to use continuous HMM or discrete
- Usage example:
python hmm_frag_fit.py U2OS_5prime_fit_hmm -non_discrete -norm_type Total data/*_TEX.bigwig data/*_Total.bigwig
- usage:
- comapre_3seq.py - For comparing HMM points to peaks in 3'-seq
- cds_vs_tUTR.py - Compare CDS and 3UTR
- hmm_frag_multichannel.py - Similar to hmm_frag_fit.py but works on a multichannel
- create_illustration - illustrate the output based on the HMM output and the read data (bigwigs)
- scripts for generating debug tracks:
- zscore_track.py
- regression_fit_track.py
- Malka, Y., Steiman-Shimony, A., Rosenthal, E., Argaman, L., Cohen-Daniel, L., Arbib, E., Margalit, H., Kaplan, T. & Berger, M. (2017). Post-transcriptional 3´-UTR cleavage of mRNA transcripts generates thousands of stable uncapped autonomous RNA fragments. Nature communications, 8(1), 2029.
- GSE84068 - The samples contain the original bigwig files used by the above paper.