{ "_id": "6a197f11acfb0bcc41df7df1", "Package": "fMRItools", "Type": "Package", "Title": "Routines for Common fMRI Processing Tasks", "Version": "0.7.2", "Authors@R": "c(\nperson(given = \"Amanda\",\nfamily = \"Mejia\",\nemail = \"mandy.mejia@gmail.com\",\nrole = c(\"aut\", \"cre\")),\nperson(given = \"Damon\",\nfamily = \"Pham\",\nemail = \"damondpham@gmail.com\",\nrole = c(\"aut\"),\ncomment = c(ORCID = \"0000-0001-7563-4727\")),\nperson(given = \"Mark\",\nfamily = \"Fiecas\",\nemail = \"mfiecas@umn.edu\",\nrole = c(\"ctb\"))\n)", "Maintainer": "Amanda Mejia ", "Description": "Supports fMRI (functional magnetic resonance imaging)\nanalysis tasks including reading in 'CIFTI', 'GIFTI' and\n'NIFTI' data, temporal filtering, nuisance regression, and\naCompCor (anatomical Components Correction) (Muschelli et al.\n(2014) ).", "License": "GPL-3", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "URL": "https://github.com/mandymejia/fMRItools", "BugReports": "https://github.com/mandymejia/fMRItools/issues", "Repository": "https://mandymejia.r-universe.dev", "Date/Publication": "2025-12-30 03:03:15 UTC", "RemoteUrl": "https://github.com/mandymejia/fmritools", "RemoteRef": "HEAD", "RemoteSha": "8792a7f6fe382d66eec2021f709fc0fdf5e019de", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-29 11:29:05 UTC", "User": "root" }, "Author": "Amanda Mejia [aut, cre],\nDamon Pham [aut] (ORCID: ),\nMark Fiecas [ctb]", "MD5sum": "543d2b8bf2d68904e1e4b068ffe6607a", "_user": "mandymejia", "_type": "src", "_file": "fMRItools_0.7.2.tar.gz", "_fileid": "be5919910bce9b367ce0b7b01efab0ff8a366d5770f44092b47a49f49fc621ec", "_filesize": 336944, "_sha256": "be5919910bce9b367ce0b7b01efab0ff8a366d5770f44092b47a49f49fc621ec", "_created": "2026-05-29T11:29:05.000Z", "_published": "2026-05-29T11:57:05.785Z", "_distro": "noble", "_jobs": [ { "job": 78491967717, "time": 147, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7289650516" }, { "job": 78491967730, "time": 123, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7289643903" }, { "job": 78491967633, "time": 118, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7290073356" }, { "job": 78491967642, "time": 127, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7290066455" }, { "job": 78491522352, "time": 185, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7289607954" }, { "job": 78491967640, "time": 119, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7289642697" }, { "job": 78491967626, "time": 89, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7289633894" }, { "job": 78491967664, "time": 96, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7289636248" }, { "job": 78491967659, "time": 104, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7289638413" } ], "_buildurl": "https://github.com/r-universe/mandymejia/actions/runs/26634563324", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/mandymejia/fmritools", "_commit": { "id": "8792a7f6fe382d66eec2021f709fc0fdf5e019de", "author": "Damon Đ Phạm ", "committer": "GitHub ", "message": "Merge pull request #3 from mandymejia/7.0\n\n7.0", "time": 1767063795 }, "_maintainer": { "name": "Amanda Mejia", "email": "mandy.mejia@gmail.com", "login": "mandymejia", "twitter": "@mandyfmejia", "description": "Associate Professor in the Department of Statistics at Indiana University. PI of the StatMIND (Statistical Methods for Individualized Neuro-Discovery) lab.", "uuid": 5199186 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "stats", "role": "Imports" }, { "package": "matrixStats", "role": "Imports" }, { "package": "ciftiTools", "role": "Suggests" }, { "package": "corpcor", "role": "Suggests" }, { "package": "expm", "role": "Suggests" }, { "package": "gifti", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "robustbase", "role": "Suggests" }, { "package": "pesel", "role": "Suggests" }, { "package": "RNifti", "role": "Suggests" }, { "package": "oro.nifti", "role": "Suggests" }, { "package": "gsignal", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "covr", "role": "Suggests" }, { "package": "fda", "role": "Suggests" }, { "package": "quantreg", "role": "Suggests" }, { "package": "graphics", "role": "Suggests" }, { "package": "grDevices", "role": "Suggests" }, { "package": "RColorBrewer", "role": "Suggests" }, { "package": "viridis", "role": "Suggests" }, { "package": "ggcorrplot", "role": "Suggests" }, { "package": "ggplot2", "role": "Suggests" }, { "package": "scales", "role": "Suggests" } ], "_owner": "mandymejia", "_selfowned": true, "_usedby": 5, "_updates": [ { "week": "2026-01", "n": 1 } ], "_tags": [ { "name": "0.7.0", "date": "2025-12-30" } ], "_stars": 2, "_contributors": [ { "user": "damondpham", "count": 172, "uuid": 14958204 }, { "user": "mandymejia", "count": 6, "uuid": 5199186 }, { "user": "noheliadasilvas", "count": 1, "uuid": 65466801 } ], "_userbio": { "uuid": 5199186, "type": "user", "name": "Mandy Mejia", "description": "Associate Professor in the Department of Statistics at Indiana University. PI of the StatMIND (Statistical Methods for Individualized Neuro-Discovery) lab." }, "_downloads": { "count": 226, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/fMRItools" }, "_devurl": "https://github.com/mandymejia/fmritools", "_searchresults": 44, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/fMRItools.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/mandymejia/fmritools", "_realowner": "mandymejia", "_cranurl": true, "_releases": [ { "version": "0.1.3", "date": "2022-11-10" }, { "version": "0.2.2", "date": "2023-01-24" }, { "version": "0.3.1", "date": "2023-06-29" }, { "version": "0.3.3", "date": "2023-09-29" }, { "version": "0.4.2", "date": "2023-11-21" }, { "version": "0.4.7", "date": "2024-05-30" }, { "version": "0.5.3", "date": "2025-03-04" }, { "version": "0.6.0", "date": "2025-05-20" }, { "version": "0.7.2", "date": "2025-12-23" } ], "_exports": [ "all_binary", "all_integers", "as.matrix_ifti", "bandstop_filter", "carpetplot", "carpetplot_stack", "colCenter", "color_palette", "CompCor", "CompCor_HCP", "coordlist_to_vol", "crop_vol", "dct_bases", "dct_convert", "despike_3D", "detrend", "dilate_mask_vol", "dual_reg", "dual_reg_parc", "erode_mask_vol", "expand_RPs", "fsl_bptf", "hat_matrix", "infer_format_ifti", "infer_format_ifti_vec", "is_1", "is_constant", "is_integer", "is_posNum", "mat2UT", "match_exactly", "match_input", "mean_squares", "Mode", "norm_BOLD", "nuisance_regression", "pad_vol", "PCA", "pct_sig", "plot_FC", "plot_FC_gg", "read_nifti", "scale_design_mat", "scale_med", "scale_timeseries", "sign_flip", "skew_pos", "sum_neighbors_vol", "temporal_filter", "unmask_mat", "unvec_mat", "unvec_vol", "UT2mat", "validate_design_mat", "var_decomp", "vox_locations" ], "_help": [ { "page": "all_binary", "title": "All binary?", "topics": [ "all_binary" ] }, { "page": "all_integers", "title": "All integers?", "topics": [ "all_integers" ] }, { "page": "as.matrix_ifti", "title": "Convert CIFTI, NIFTI, or GIFTI input to T \\times V matrix", "topics": [ "as.matrix_ifti" ] }, { "page": "bandstop_filter", "title": "Bandstop filter", "topics": [ "bandstop_filter" ] }, { "page": "carpetplot", "title": "Carpetplot", "topics": [ "carpetplot" ] }, { "page": "carpetplot_stack", "title": "Stacked carpetplot", "topics": [ "carpetplot_stack" ] }, { "page": "colCenter", "title": "Center matrix columns", "topics": [ "colCenter" ] }, { "page": "color_palette", "title": "Color palette", "topics": [ "color_palette" ] }, { "page": "CompCor", "title": "Anatomical CompCor", "topics": [ "CompCor" ] }, { "page": "CompCor_HCP", "title": "Anatomical CompCor for HCP NIFTI and CIFTI data", "topics": [ "CompCor_HCP" ] }, { "page": "coordlist_to_vol", "title": "Convert coordinate list to 3D array", "topics": [ "coordlist_to_vol" ] }, { "page": "crop_vol", "title": "Crop a 3D array", "topics": [ "crop_vol" ] }, { "page": "dct_bases", "title": "Generate cosine bases for the DCT", "topics": [ "dct_bases" ] }, { "page": "dct_convert", "title": "DCT and frequency conversion", "topics": [ "dct2Hz", "dct_convert", "Hz2dct" ] }, { "page": "despike_3D", "title": "3dDespike from AFNI", "topics": [ "despike_3D" ] }, { "page": "dice_overlap", "title": "Dice overlap", "topics": [ "dice_overlap" ] }, { "page": "dilate_mask_vol", "title": "Dilate 3D mask", "topics": [ "dilate_mask_vol" ] }, { "page": "dual_reg", "title": "Dual Regression", "topics": [ "dual_reg" ] }, { "page": "dual_reg_parc", "title": "Multiple regression for parcel data", "topics": [ "dual_reg_parc" ] }, { "page": "erode_mask_vol", "title": "Erode 3D mask", "topics": [ "erode_mask_vol" ] }, { "page": "expand_RPs", "title": "Expand realignment parameters (RPs)", "topics": [ "expand_RPs" ] }, { "page": "fMRItools", "title": "fMRItools: Routines for Common fMRI Processing Tasks", "topics": [ "fMRItools-package", "fMRItools" ] }, { "page": "fsl_bptf", "title": "'bptf' function from FSL", "topics": [ "fsl_bptf" ] }, { "page": "hat_matrix", "title": "Hat matrix", "topics": [ "hat_matrix" ] }, { "page": "infer_format_ifti", "title": "Infer fMRI data format", "topics": [ "infer_format_ifti" ] }, { "page": "infer_format_ifti_vec", "title": "Infer fMRI data format for several inputs", "topics": [ "infer_format_ifti_vec" ] }, { "page": "is_1", "title": "Is this object the expected data type, and length one?", "topics": [ "is_1" ] }, { "page": "is_constant", "title": "Is this numeric vector constant?", "topics": [ "is_constant" ] }, { "page": "is_integer", "title": "Is this an integer?", "topics": [ "is_integer" ] }, { "page": "is_posNum", "title": "Is this object a positive number? (Or non-negative)", "topics": [ "is_posNum" ] }, { "page": "mat2UT", "title": "Matrix to Upper Triangular Vector", "topics": [ "mat2UT" ] }, { "page": "match_exactly", "title": "Do these character vectors match exactly?", "topics": [ "match_exactly" ] }, { "page": "match_input", "title": "Match user inputs to expected values", "topics": [ "match_input" ] }, { "page": "mean_squares", "title": "Compute mean squares from variance decomposition", "topics": [ "mean_squares" ] }, { "page": "Mode", "title": "Mode of data vector", "topics": [ "Mode" ] }, { "page": "norm_BOLD", "title": "Normalize BOLD data", "topics": [ "norm_BOLD" ] }, { "page": "nuisance_regression", "title": "Nuisance regression", "topics": [ "nuisance_regression" ] }, { "page": "pad_vol", "title": "Pad 3D Array", "topics": [ "pad_vol", "uncrop_vol" ] }, { "page": "PCA", "title": "PCA for tall matrix", "topics": [ "PCA" ] }, { "page": "pct_sig", "title": "Convert data values to percent signal.", "topics": [ "pct_sig" ] }, { "page": "plot_FC", "title": "Plot FC", "topics": [ "plot_FC" ] }, { "page": "plot_FC_gg", "title": "Plot FC with ggplot2", "topics": [ "plot_FC_gg" ] }, { "page": "read_nifti", "title": "Wrapper to functions for reading NIFTIs", "topics": [ "read_nifti" ] }, { "page": "scale_design_mat", "title": "Scale a design matrix", "topics": [ "scale_design_mat" ] }, { "page": "scale_med", "title": "Robust scaling", "topics": [ "scale_med" ] }, { "page": "scale_timeseries", "title": "Scale the BOLD timeseries", "topics": [ "scale_timeseries" ] }, { "page": "sign_flip", "title": "Sign match ICA results", "topics": [ "sign_flip" ] }, { "page": "skew_pos", "title": "Positive skew?", "topics": [ "skew_pos" ] }, { "page": "sum_neighbors_vol", "title": "Sum of each voxel's neighbors", "topics": [ "sum_neighbors_vol" ] }, { "page": "temporal_filter", "title": "Temporal filtering (bandpass, highpass, lowpass) with DCT or FFT", "topics": [ "detrend", "temporal_filter" ] }, { "page": "unmask_mat", "title": "Unmask matrix data", "topics": [ "unmask_mat" ] }, { "page": "unvec_mat", "title": "Transform vector data to image", "topics": [ "unvec_mat" ] }, { "page": "unvec_vol", "title": "Convert vectorized data back to volume", "topics": [ "unvec_vol" ] }, { "page": "UT2mat", "title": "Upper Triangular Vector to Matrix", "topics": [ "UT2mat" ] }, { "page": "validate_design_mat", "title": "Validate design matrix", "topics": [ "validate_design_mat" ] }, { "page": "var_decomp", "title": "Compute variance decomposition", "topics": [ "var_decomp" ] }, { "page": "vox_locations", "title": "Get coordinates of each voxel in a mask", "topics": [ "vox_locations" ] } ], "_readme": "https://github.com/mandymejia/fmritools/raw/HEAD/README.md", "_rundeps": [ "matrixStats" ], "_score": 5.1205739312058505, "_indexed": true, "_nocasepkg": "fmritools", "_universes": [ "mandymejia" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.7.2", "date": "2026-05-29T11:31:34.000Z", "distro": "noble", "commit": "8792a7f6fe382d66eec2021f709fc0fdf5e019de", "fileid": "f2dd0979ec17768e5f218010994087c75805060413dd07196e9e86731e39baf4", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/mandymejia/actions/runs/26634563324" }, { "r": "4.6.0", "os": "linux", "version": "0.7.2", "date": "2026-05-29T11:31:13.000Z", "distro": "noble", "commit": "8792a7f6fe382d66eec2021f709fc0fdf5e019de", "fileid": "b86d9fafb4684f3c5b217dedd3d7f7897f885824af86435ce58403d2fb0d19ff", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/mandymejia/actions/runs/26634563324" }, { "r": "4.5.3", "os": "mac", "version": "0.7.2", "date": "2026-05-29T11:56:32.000Z", "commit": "8792a7f6fe382d66eec2021f709fc0fdf5e019de", "fileid": "a90bf0177ecd9a7d2330a37b3dd5e07e24cb73d86099a88ad58434c573323bfc", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/mandymejia/actions/runs/26634563324" }, { "r": "4.6.0", "os": "mac", "version": "0.7.2", "date": "2026-05-29T11:56:00.000Z", "commit": "8792a7f6fe382d66eec2021f709fc0fdf5e019de", "fileid": "d11e152a3701c00aff1c3a65df825c46147e6373314a0aac65c01413a5779b6a", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/mandymejia/actions/runs/26634563324" }, { "r": "4.6.0", "os": "wasm", "version": "0.7.2", "date": "2026-05-29T11:31:27.000Z", "commit": "8792a7f6fe382d66eec2021f709fc0fdf5e019de", "fileid": "e8598ecf4b79fef2f37d419775083ed0b3da3352781d556ba46426bcd2aa3517", "status": "success", "buildurl": "https://github.com/r-universe/mandymejia/actions/runs/26634563324" }, { "r": "4.7.0", "os": "win", "version": "0.7.2", "date": "2026-05-29T11:30:30.000Z", "commit": "8792a7f6fe382d66eec2021f709fc0fdf5e019de", "fileid": "253c103e25554baa8115ea973852d7cfaec6345ff6283421313d06188f735e7e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/mandymejia/actions/runs/26634563324" }, { "r": "4.5.3", "os": "win", "version": "0.7.2", "date": "2026-05-29T11:30:39.000Z", "commit": "8792a7f6fe382d66eec2021f709fc0fdf5e019de", "fileid": "d706519d2c93387f0e4a16a2464d30eb4d4ac3a19037c2e08023f5579f45bc93", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/mandymejia/actions/runs/26634563324" }, { "r": "4.6.0", "os": "win", "version": "0.7.2", "date": "2026-05-29T11:30:49.000Z", "commit": "8792a7f6fe382d66eec2021f709fc0fdf5e019de", "fileid": "b6c5b8ea6c87d465b390af9480c584744baac6e0863375c066e9cbf87e1091ab", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/mandymejia/actions/runs/26634563324" } ] }