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FIREcaller: an R package for detecting frequently interacting regions from Hi-C data

Downloadable Terminals (use "save as"):
  • FIREcaller Version 1.40 released (December 16, 2020)
          FIREcaller_1.40
        The R package can be downloaded from Github webpage yycunc/FIREcaller

  • Here is an example of Hi-C input files of Hippocampus dataset from Schmitt et al. (Cell Reports, 2016), which contains Hi-C contact matrices of 22 autosomes, and the mappability file required by the FIRE calling. Users can also use their own mappability file in the same format.
          Hippo_Hi-C_inputs_chr1_22.tar.gz
          Hind3_hg19_40Kb_encodeBL_F_GC_M_auto.txt.gz

  • Fetal and adult brain FIREs and SuperFIREs called by FIREcaller on Won et al. (2016) and Wang et al. (2018).
          humanCortex.FIRE_SUPERFIRE
          Shared.FIRE.GE
          Fetal.FIRE.GE
          Adult.FIRE.GE

  • All the ChIP-seq peaks from Schmitt et al., 2016.
          ChIP-seq_peaks_Schmitt_et_al_2016

  • Gene expression data from Schmitt et al., 2016.
          RPKM_matrix_strend_TSS_021116.txt

  • Codes and input files for the line plot showing relationship between FIREs and histone marks (H3K27ac or H3K4me3), in DLPFC (Schmitt et al., 2016).
          convert_narrowPeak_into_Bin.R: The code for converting H3K27ac/H3K4me3 narrow peaks into bed format.
          Schmitt_DLPFC_H3K4ME3_H3K27ac_line_plot.R: The code for line plot.
          hg19_DLPFC_H3K27ac.1e5_peaks.narrowPeak.gz: Narrow peaks for H3K27ac in DLPFC.
          hg19_DLPFC_H3K4me3.1e5_peaks.narrowPeak.gz: Narrow peaks for H3K4me3 in DLPFC.
          Schmitt_FIRE_tissue_DLPFC.txt.gz: FIREs in DLPFC.
          Schmitt_primary_cohort_FIREscore.csv: The entire list of FIRE scores for all the primary cohort in Schmitt et al. (2016).

  • Mappability Files
          hind3_grch38.zip
          hind3_hg19.zip
          hind3_mm10.zip
          hind3_mm9.zip
          ncoI_grch38.zip
          ncoI_hg19.zip
          ncoI_mm10.zip
          ncoI_mm9.zip
          mboI_grch38.zip
          mboI_hg19.zip
          mboI_mm10.zip
          mboI_mm9.zip



    • REFERENCES
    Schmitt, A.D., Hu, M., Jung, I., Xu, Z., Qiu, Y., Tan, C.L., Li, Y., Lin, S., Lin, Y., Barr, C.L. and Ren, B. (2016) A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell reports, 17: 2042-2059.
    Wang, D., Liu, S., Warrell, J., Won, H., Shi, X., Navarro, F.C., Clarke, D., Gu, M., Emani, P., Yang, Y.T., Xu, M., Gandal, M.J., Lou, S., Zhang, J., Park, J.J., Yan, C., Rhie, S.K., Manakongtreecheep, K., Zhou, H., Nathan, A., Peters, M., Mattei, E., Fitzgerald, D., Brunetti, T., Moore, J., Jiang, Y., Girdhar, K., Hoffman, G.E., Kalayci, S., Gümüş, Z.H., Crawford, G.E.; PsychENCODE Consortium, Roussos, P., Akbarian, S., Jaffe, A.E., White, K.P., Weng, Z., Sestan, N., Geschwind, D.H., Knowles, J.A. and Gerstein, M.B. (2018) Comprehensive functional genomic resource and integrative model for the human brain. Science, 362: eaat8464.
    Won, H., de La Torre-Ubieta, L., Stein, J.L., Parikshak, N.N., Huang, J., Opland, C.K., Gandal, M.J., Sutton, G.J., Hormozdiari, F., Lu, D., Lee, C., Eskin, E., Voineagu, I., Ernst, J. and Geschwind, D.H. (2016) Chromosome conformation elucidates regulatory relationships in developing human brain. Nature, 538: 523.
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