Package: diffDomain-py3
diffDomainA short descriptiondiffDomain is a new computational method for identifying reorganized
TADs using chromatin contact maps from two biological conditions.A long description diffDomainThe workflow of diffDomain is illustrated down below.The goal is to test if a TAD identified in one biological condition has
structural changes in another biological condition.The core of diffDomain is formulating the problem as a hypothesis
testing problem where the null hypothesis is that the TAD doesn’t
undergo significant structural reorganization at later condition. The
input are Hi-C contact matrices of the TAD region in the two biological
conditions (A). The Hi-C contact matrices are log-transformed to
adjust for the exponential decay of Hi-C contacts between chromosome
bins with increased distances.Their entry-wise difference is calculated (B).The difference matrixDis normalized by iteratively standardizing itsk-off diagonal parts,-N+2 <= k <= N-2, adjusting absolute
differences in contact frequencies due to different sequencing depths in
the two biological conditions (C).Note that, standardization is TAD-specific. Each TAD has its own
parameters that are only estimated from its contact matrices in a pair
of biological conditions.Intuitively, if a TAD is not significantly reorganized, normalizedDwould resemble a random matrix with white noise entries, enabling us to
borrow theoretical results in random matrix theory. Indeed, normalizedDis a generalized Wigner matrix (D), a well studied high-dimensional
random matrices.Its largest singular value is proved to be fluctuating around 2 under
the null hypothesis. Armed with the fact, diffDomain reformulates the
reorganized TAD identification problem into a hypothesis testing
problem:1. H0: the largest singular value equals to 2;2. H1: the largest singular value is greater than 2.For a user given set of TADs,Pvalues are adjusted for multiple
comparisons usingBHmethod as default.Once we identify the subset of reorganized TADs, we classify them into
six subtypes to aid biological analysis and interpretations.Installation instructionsdiffDomain is tested on MacOS & Linux (Centos).DependencesdiffDomain-py3 is dependent on - Python 3 - hic-straw 1.3.1 - TracyWidom
- pandas  - numpy  - docopt  -tqdm  - matplotlib  - statsmodelsInstallationDownload diffDomain source package by running following command in a
terminal:git clone https://github.com/Tian-Dechao/diffDomain.gitor :pip install diffDomain-py3Get started with example usageWe downloaded dataGEO:GSE63525from Rao et al(2014)for standalone example usage of diffDomain. Example data saved in<data/>: 1. GM12878 TADs. 2. GM12878 combined Hi-C data on Chr1 that
is extracted byJuiceboxwith
resolution at 10 kb and normalization method at KR. The produced Hi-C
data is 3-column: column 1 and column 2 are chromosomal bins, column 3
is KR normalized contact frequencies between the two bins. 3. K562
combined Hi-C data on Chr1. Settings are the same as GM12878.Testing if one TAD is reorganizedIn this example, we tested the GM12878 TAD that is reorganized in K562
(Chr1:163500000-165000000,Ref). Data are
saved in<data/single-TAD/>.Running the commandUsage: scriptname dvsd one <chr> <start> <end> <hic0> <hic1>
[options]python diffdomain/diffdomains.py dvsd one 1 163500000 165000000 data/single-TAD/GM12878_chr1_163500000_165000000_res_10k.txt data/single-TAD/K562_chr1_163500000_165000000_res_10k.txt --reso 10000 --ofile res/chr1_163500000_165000000.txtdiffDomain also provide visualization function to visualize Hi-C
matrices side-by-side.Usage: scriptname visualization <chr> <start> <end> <hic0> <hic1>
[options]Figure are saved in<res/images/>.python diffdomain/diffdomains.py visualization 1 163500000 165000000 data/single-TAD/GM12878_chr1_163500000_165000000_res_10k.txt data/single-TAD/K562_chr1_163500000_165000000_res_10k.txt --reso 10000 --ofile res/images/side_by_sideNote: in this example, there is no need to do multiple comparison
adjustment. Multiple comparisons adjustment byBHwill be demonstrated
in the next example.Identifying the reorganized TADs on a 50 Mb region (Chr1:1-50,000,000)In this example, multiple comparison adjustment is requried to adjust
theP-values. chr1_50M_domainlist are saved in<data/TADs_chr1/>.Usage: scriptname dvsd multiple <hic0> <hic1> <bed> [options]python diffdomain/diffdomains.py dvsd multiple data/TADs_chr1/chr1_50M_GM12878.h5 data/TADs_chr1/chr1_50M_K562.h5 data/TADs_chr1/GM12878_chr1_50M_domainlist.txt --reso 10000 --ofile res/temp/GM12878_vs_K562_chr1_50M_temp.txtThe function pydiff.diffdomain_multiple will return the dataframe of
result_mul.Adjusting multiple comparisons byBHmethod (default, Optional
parameters:fdr_by,bonferroni,holm,hommeletc.) and
Filtering out reorganized TADs withBH < 0.05Usage: scriptname adjustment <method> <input> <output>python diffdomain/diffdomains.py adjustment fdr_bh res/temp/GM12878_vs_K562_chr1_50M_temp.txt res/GM12878_vs_K562_chr1_50M_adjusted_filter.tsv --filter trueFor interactive integrative analysis, we recommend using theNucleome
Browser. Example visualization outputs are
shown below.reorganized TADs on chr1Identifying GM12878 TADs that are reorganized in K562, using all TADs.Data is using Amazon.Identify TADs in multiple chromosomes simultaneously.python diffdomain/diffdomains.py dvsd multiple https://hicfiles.s3.amazonaws.com/hiseq/gm12878/in-situ/combined.hic https://hicfiles.s3.amazonaws.com/hiseq/k562/in-situ/combined.hic data/GSE63525_GM12878_primary+replicate_Arrowhead_domainlist.txt --ofile res/temp/temp.txtMultiComparison adjustment.python diffdomain/diffdomains.py adjustment fdr_bh res/temp/GM12878_vs_K562_chr1_50M_temp.txt res/adjusted_TADs2.txtoptional parameter[–filter], Filtering out reorganized TADs withBH < 0.05.python diffdomain/diffdomains.py adjustment fdr_bh res/temp/GM12878_vs_K562_chr1_50M_temp.txt res/reorganized_TADs_GM12878_K562.tsv --filter trueThe final output is saved to<res/reorganized_TADs_GM12878_K562.tsv>.Classification of TADsRunning the command:python diffdomain/classificattion.py -d adjusted_TADs2.txt -t GSE63525_K562_Arrowhead_domainlist.txtContact informationMore information please contact Dunming Hua athuadm@mail2.sysu.edu.cn, Ming Gu atguming5@mail2.sysu.edu.cnor Dechao Tian attiandch@mail.sysu.edu.cn.