Multi-scale footprinting
Creators
- Hu, Yan1
-
Horlbeck, Max1, 2
-
Zhang, Ruochi1, 3
- Ma, Sai1
- Shrestha, Rojesh1
- Kartha, Vinay1
- Duarte, Fabiana1
- Hock, Conrad1
- Savage, Rachel1
- Labade, Ajay1
- Kletzien, Heidi1
- Meliki, Alia1
- Castillo, Andrew1
- Durand, Neva3
- Mattei, Eugenio3
- Anderson, Lauren3
- Tay, Tristan1
- Earl, Andrew1
- Shoresh, Noam3
- Epstein, Charles3
- Wagers, Amy1
- Buenrostro, Jason1
- 1. Harvard University
-
2.
Boston Children's Hospital
- 3. Broad Institute
Description
Data associated with the multi-scale footprinting project.
(1) Tn5_NN_model.h5
Pre-trained CNN-based Tn5 bias model implemented with Keras. Takes local DNA sequence context as input and predicts Tn5 insertion bias. See tutorial for how to use this model.
(2) Tn5ModelTutorial.ipynb
Tutorial showing how to use the pre-trained Tn5 bias model to score input sequences.
(3) hg38Tn5Bias.tar.gz, hg19Tn5Bias.tar.gz, mm10Tn5Bias.tar.gz, panTro6Tn5Bias.tar.gz, sacCer3Tn5Bias.tar.gz, dm6Tn5Bias.tar.gz, danRer11Tn5Bias.tar.gz, ce11Tn5Bias.tar.gz
h5 files containing the genome-wide Tn5 bias pre-computed using our convolutional neural net model.
(4) dispModel.tar.gz
Zipped folder containing Tn5 cutting dispersion models for each footprint window radius. The footprint window size in our paper refers to the diameter the footprint window, which is twice the number listed here. During footprinting, these models are loaded into the footprintingProject object and then used for footprinting.
(5) cisBP_mouse_pwms_2021.rds, cisBP_human_pwms_2021.rds
Motif PWMs used in our study.
(6) TFBS_model.h5
Pre-trained footprint-to-TF binding prediction models. The models takes local multi-scale footprints as input and predict whether a genomic position is bound by a TF if the corresponding motif is present. This is obsolete. For the best performance of TF binding prediction, please use our seq2PRINT-based TF binding prediction.
(7) clusterLabels.txt, clusterLabelsAllTFs.txt
Cluster labels of TFs. clusterLabels.txt is the clustering result directly obtained from clustering multi-scale footprints of all TFs with ChIP data. clusterLabelsAllTFs.txt includes other TFs without ChIP data. The cluster membership of these TFs were assigned based on motif homology among TFs.
(8) BMMCTutorial.tar.gz
Data needed for our R version tutorial. Content of this foder can be put into the /data/BMMCTutorial folder.
Files
Tn5ModelTutorial.ipynb
Files
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