rgmap R topics documented: June 12, 2018 Type Package
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1 Type Package rgmap June 12, 2018 Title Call hierarchical chromatin domains from HiC matrix by GMAP Version 1.3 Date Author Wenbao Yu Maintainer Wenbao Yu Call hierarchical chromatin domains from HiC contact matrix by Gaussian Mixture model And Proportion test BugReports License GPL (>= 2) LazyData TRUE Imports data.table, ggplot2, mclust, EMD, catools, Matrix, Rcpp (>= ) LinkingTo Rcpp RoxygenNote Suggests knitr, rmarkdown VignetteBuilder knitr R topics documented: data_simu hic_rao_imr90_chr plotdom rgmap Index 5 1
2 2 hic_rao_imr90_chr15 data_simu generate simulated hic_mat and true tads generate simulated hic_mat and true tads data_simu(stype = "poisson-dist", nratio = 2.5, mu0 = 200, resl = 1) Value stype nratio One of four types of simulated data in the manuscript: poission-dist, poissiondist-hier, nb-dist, nb-dist-hier; poission- or nb- indicates poission distribution or negative bionomial distribution -hier indicated subtads are generated nestly The effect size between intra- and inter domain, larger means higher intra-tad contacts mu0 The mean parameter, default 200 resl Resolution, default set to 1 A list includes following elements: hic_mat hiertads tads_true n by n contact matrix True heirarchical domains True TADs hic_rao_imr90_chr15 Normalized Hi-C data for IMR90, chr15 with resolution 10kb. Normalized Hi-C data for IMR90, chr15 with resolution 10kb. hic_rao_imr90_chr15 Format A data table with 3 variables: n1 bin 1 n2 bin 2 count normalized counts
3 plotdom 3 Source Rao et al., Cell 2014, A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping plotdom visualize hierarchical domains visualize hierarchical domains plotdom(hic_dat, hiertads_gmap, start_bin, end_bin, cthr = 20, kb_resl = 10) hic_dat hic contact matrix for a given chromosome with 3 columns matrix or data.frame with columns: bin1, bin2, counts hiertads_gmap the hierarchical domains called by GMAP start_bin end_bin the start bin of the genome the end bin of the genome cthr the upper bound count threshold for color, default 20 kb_resl reslution of Hi-C data in kb rgmap Detect hierarchical choromotin domains by GMAP Detect hierarchical choromotin domains by GMAP rgmap(hic_mat, resl = 10 * 10^3, logt = T, dom_order = 2, maxdistinbin = min(200, 2 * 10^6/resl), min_d = 25, max_d = 100, min_dp = 5, max_dp = 10, hthr = 0.95, t1thr = 0.5)
4 4 rgmap Value hic_mat resl logt dom_order Either a 3 columns Hi-C contact matrix for a given chromosome, with each row corrsponding to the start bin, end bin and the contact number; or a n by n matrix, n is the number of bins for a given chromosom The resolution (bin size), default 10kb Do log-transformation or not, default TRUE Maximum level of hierarchical structures, default 2 (call TADs and subtads) maxdistinbin Only consider contact whose distance is not greater than maxdistinbin bins, default 200 bins (or 2Mb) min_d The minimum d (d: window size), default 25 max_d The maximum d (d: window size), default 100 min_dp The minmum dp (dp: lower bound of tad size), defalt 5 max_dp The maximum dp (dp: lower bound of tad size), defalt 10. min_d, max_d, min_dp and max_dp should be specified in number of bins hthr The lower bound cutoff for posterior probability, default 0.95 t1thr A list includes following elements: Lower bound for t1 for calling TAD, default 0.5 quantile of test statistics of TADs, 0.9 of subtads tads hiertads params A data frame with columns start, end indicates the start and end coordinates of each domain, respectively A data frame with columns start, end, dom_order, where dom_order indicates the hierarchical status of a domain, 1 indicates tads, 2 indicates subtads, and so on A data frame gives the final parameters for calling TADs Examples ## On simulated data: library(rgmap) simu_res = data_simu('poisson-dist-hier') true_domains = simu_res$hiertads simu_mat = simu_res$hic_mat predicted_domains = rgmap(simu_mat, resl = 1)$hierTads true_domains predicted_domains ## On an real data example hic_rao_imr90_chr15 # normalized Hi-C data for IMR90, chr15 with resolution 10kb res = rgmap(hic_rao_imr90_chr15, resl = 10 * 1000, dom_order = 2) names(res) #quickly visualize some hierarchical domains pp = plotdom(hic_rao_imr90_chr15, res$hiertads, 6000, 7000, 30, 10) pp$p2
5 Index Topic datasets hic_rao_imr90_chr15, 2 data_simu, 2 hic_rao_imr90_chr15, 2 plotdom, 3 rgmap, 3 5
Package FitHiC. October 16, 2018
Type Package Package FitHiC October 16, 2018 Title Confidence estimation for intra-chromosomal contact maps Version 1.6.0 Date 2017-04-12 Description Fit-Hi-C is a tool for assigning statistical confidence
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