3.2 Resources

Databases

• Rfam: (https://rfam.xfam.org/)

• Compative RNA Web: (http://www.rna.icmb.utexas.edu/)

• RNA STRAND: (http://www.rnasoft.ca/strand/)

• bpRNA: (http://bprna.cgrb.oregonstate.edu/)

• RNAStralign: (https://rna.urmc.rochester.edu/pub/RNAStralign.tar.gz)

• JASPAR (TF motifs): (http://jaspar.genereg.net/)

Data

• Known structure: /BioII/lulab_b/shared/projects/RNA_known_structure

• icSHAPE: /BioII/lulab_b/shared/projects/icSHAPE

• RNAex (DMS-seq, PARS, icSHAPE): /BioII/lulab_b/shared/projects/RNAex

• SHAPE-MaP: /BioII/lulab_b/shared/projects/shape-map

• RNAStralign: /BioII/lulab_b/shared/projects/RNA_stralign

Software

• icSHAPE pipeline: (https://github.com/qczhang/icSHAPE)
• ShapeMapper 2: (https://github.com/Weeks-UNC/shapemapper2)
• ShaperMapper: (https://weeks.chem.unc.edu/software-files/ShapeMapper_v1.2.tar.gz)
• Superfold (SHAPE-MaP): (https://weeks.chem.unc.edu/software-files/Superfold_v1.0.tar.gz)

Scripts

Predict SHAPE data

Project directory: /Share2/home/lulab/shibinbin/projects/Deepfold2

Files:

• Scripts: bin/

• icSHAPE data preprocessing: Jobs/icSHAPE_*.sh

• Notes: notes/*.md

• Processed icSHAPE data: output/icSHAPE_preprocess/

• icSHAPE reactivities in HDF5 format: data/icSHAPE/

• Prediction using neural network: bin/predict_reactivity.py

• Neural network models (keras): models/

• Workflows using snakemake: workflows/

• Predict RNA-protein binding: output/motif_ionmf

• Jupyter notebooks: jupyter/

Motif discovery

Project directory: /Share2/home/lulab/shibinbin/projects/DeepShape

• Scripts: bin/

• Notes: notes/

• Training and test data: output/rfam/, output/jaspar/

Work reports

Tsinghua Cloud (https://cloud.tsinghua.edu.cn):

Summary slide: DeepShape summary 20190622.pptx

Lu Lab / Lu Lab Shared / 1.Project Progress / 14' Shi Binbin / DeepShape