CD-Loop

CD-Loop: A chromatin loop detection method based on the diffusion model

Install

git clone https://github.com/wangyang199897/CD-Loop.git

python library

pytorch
numpy
PIL
sklearn
pandas

other tools

juicer_tools

Usage

First -- Use juicer tools

Perform normalization processing to obtain the interaction frequency matrix

juicer_tools  dump  observed  KR  [.hic file]  [chromosome] [chromosome]  BP 5000  output [output file path]

Get norm factor

juicer_tools  dump  norm  KR  [.hic file] [chromosome] [chromosome]  BP  5000  [output file path]

Second -- Use CD-Loop

python CD_Loop.py -inf [Interaction frequency file path] -nof [norm factor file path] -chr [chromosome name(only one)] -lcps [lower center point scope def 30000] -hcps [high center point scope def 3000000] -outpath [output directory]

input

[Interaction frequency file path]  The Interaction frequency file generate with juicer_tools

[norm factor file path]  The norm factor file generate with juicer_tools

[chromosome name(only one)] The chromosome which you want to predict

[lower center point scope def 30000] Predict the left endpoint of the range of interaction points, default 30000

[high center point scope def 3000000] Predict the right endpoint of the range of interaction points, default 3000000

output

[output directory]  Output file saving path

There are seven subfolders in the output folder

/bigmatrix                              Convert interaction frequencies to a large matrix

/interactionPointInformation            Interaction point information within a limited range

/deleteInteractionPointInformation      Cleaned interaction point information

/subMatrix                              Input sub-matrix required by the model

/deleteSubMatrix                        Cleaned submatrix

/beforeClustering                       Files to be clustered

/result                                 final output result

TestData

dataset	link
GM12878 Hi-C	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE63525
K562 Hi-C	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE63525
IMR90 Hi-C	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE63525
mESC Hi-C	https://data.4dnucleome.org/experiment-set-replicates/4DNESUCLJAZ8
GM12878 CTCF ChIA-PET	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi
GM12878 RAD21 ChIA-PET	https://www.encodeproject.org/publication-data/ENCSR727WCB
GM12878 H3k27ac HiChIP	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE101498
GM12878 SMC1 HiCHIP	https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE80820
GM12878 CTCF ChIP-Seq	https://www.encodeproject.org/files/ENCFF963PJY
K562 CTCF ChIP-Seq	https://www.encodeproject.org/files/ENCFF085HTY
IMR-90 CTCF ChIP-Seq	https://www.encodeproject.org/files/ENCFF453XKM
mESC CTCF ChIP-Seq	https://www.encodeproject.org/files/ENCFF508CKL
K562 CTCF ChIA-PET	https://www.encodeproject.org/files/ENCFF001THV
K562 RAD21 ChIA-PET	https://www.encodeproject.org/files/ENCFF002ENT
mESC CTCF ChIA-PET	https://www.encodeproject.org/files/ENCFF550QMW
mESC CTCF ChIA-PET	https://www.encodeproject.org/files/ENCFF963PJY