Integrated Method for Predicting Enhancer Targets (IM-PET)
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IM-PET: Integrated Methods for Predicting Enhancer Targets
We devised and tested four features for their abilities to discriminate a set of ~2000 real and non-interacting EP pairs that are selected based on published ChIA-PET data. The four features are 1) distance constraint (DIS); 2) enhancer and target promtoer activity profile correlation (EPC); 3) TF and target promoter correlation (TPC); and 4) co-evolution of enhancer and target promoter (COEV). All these genomic features can be extracted from public database. For genome-wide prediction of EP pairs, we first use CSI-ANN and histone modification ChIP-Seq data (specific to each cell type) to predict enhancers. For each predicted enhancer we extract all candidate promoters within a distance range (e.g. 2M bp) and compute the four feature scores separately for all EP pairs. We next use random forest classifier to integrate the four features for linking enhancers to their target promoters.
Publication: https://www.pnas.org/content/111/21/E2191
I. Preparation of the input files
A tab-delineate file indicate the enhancer positions. Format: [Chr]\t[Start]\t[End]\n
A tab-delineate file indicate the enhancer signals in genome-wide. Format: [Chr]\t[Position\t[Signal]\n
A tab-delineate file indicate the gene expression values. Format: [gene name]\t[FPKM]\n
*Files 1) and 2) are the output files directly from CSI-ANN (Firpi et al, Bioinformatics, 2010). CSI-ANN takes as input ChIP-Seq data of 3 histone modifications (H3K4me1, H3K4me3, H3K27ac) to predict tissue-specific enhancers. The input of CSI-ANN are bowtie aligned files.
II. Usage:
docker run -v "$PWD":/app tanlabcode/im-pet:latest perl /home/IM-PET.pl
-e [enhancers]
-s [enhancer signals]
-x [gene expressions]
III. Example:
A set of example input files are built into the package. Use following command to run IM-PET with the example:
docker run -v "$PWD":/app tanlabcode/im-pet:latest perl /home/IM-PET.pl
-e /home/Input/GM_enh.bed
-s /home/Input/GM_ANN
-x /home/Input/GM_Expr
Content type
Image
Digest
Size
1.2 GB
Last updated
over 7 years ago
docker pull tanlabcode/im-pet