{
  "_id": "6a1adaf01d7bb097a09e8d3a",
  "Package": "designit",
  "Title": "Blocking and Randomization for Experimental Design",
  "Version": "0.5.0.9000",
  "Authors@R": "c(\nperson(given = c(first = \"Iakov\", middle = \"I.\"),\nfamily = \"Davydov\",\nrole = c(\"aut\", \"cre\", \"cph\"),\nemail = \"iakov.davydov@roche.com\",\ncomment = c(ORCID = \"0000-0003-3510-3926\")),\nperson(given = \"Juliane\",\nfamily = \"Siebourg-Polster\",\nrole = c(\"aut\", \"cph\"),\nemail = \"juliane.siebourg-polster@roche.com\",\ncomment = c(ORCID = \"0000-0002-1759-3223\")),\nperson(given = \"Guido\",\nfamily = \"Steiner\",\nrole = c(\"aut\", \"cph\"),\nemail = \"guido.steiner@roche.com\",\ncomment = c(ORCID = \"\")),\nperson(given = \"Konrad\",\nfamily = \"Rudolph\",\nrole = \"ctb\",\nemail = \"konrad.rudolph@roche.com\",\ncomment = c(ORCID = \"0000-0002-9866-7051\")),\nperson(given = \"Jitao David\",\nfamily = \"Zhang\",\nrole = c(\"aut\", \"cph\"),\nemail = \"jitao_david.zhang@roche.com\",\ncomment = c(ORCID=\"0000-0002-3085-0909\")),\nperson(given = \"Balazs\",\nfamily = \"Banfai\",\nrole = c(\"aut\", \"cph\"),\nemail = \"balazs.banfai@roche.com\",\ncomment = c(ORCID = \"0000-0003-0422-7977\")),\nperson(given = \"F. Hoffman-La Roche\", role = c(\"cph\", \"fnd\")))",
  "Description": "Intelligently assign samples to batches in order to reduce\nbatch effects. Batch effects can have a significant impact on\ndata analysis, especially when the assignment of samples to\nbatches coincides with the contrast groups being studied. By\ndefining a batch container and a scoring function that reflects\nthe contrasts, this package allows users to assign samples in a\nway that minimizes the potential impact of batch effects on the\ncomparison of interest. Among other functionality, we provide\nan implementation for OSAT score by Yan et al. (2012,\n<doi:10.1186/1471-2164-13-689>).",
  "License": "MIT + file LICENSE",
  "URL": "https://bedapub.github.io/designit/,\nhttps://github.com/BEDApub/designit/",
  "BugReports": "https://github.com/BEDApub/designit/issues",
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  "Config/pak/sysreqs": "libicu-dev",
  "Repository": "https://bedapub.r-universe.dev",
  "Date/Publication": "2026-03-27 15:38:22 UTC",
  "RemoteUrl": "https://github.com/bedapub/designit",
  "RemoteRef": "HEAD",
  "RemoteSha": "47079e63f925c352146298a97d708b54d2369391",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-30 09:13:26 UTC",
    "User": "root"
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  "Author": "Iakov I. Davydov [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0003-3510-3926>),\nJuliane Siebourg-Polster [aut, cph] (ORCID:\n<https://orcid.org/0000-0002-1759-3223>),\nGuido Steiner [aut, cph],\nKonrad Rudolph [ctb] (ORCID: <https://orcid.org/0000-0002-9866-7051>),\nJitao David Zhang [aut, cph] (ORCID:\n<https://orcid.org/0000-0002-3085-0909>),\nBalazs Banfai [aut, cph] (ORCID:\n<https://orcid.org/0000-0003-0422-7977>),\nF. Hoffman-La Roche [cph, fnd]",
  "Maintainer": "Iakov I. Davydov <iakov.davydov@roche.com>",
  "MD5sum": "bf7bbc81748e951a6281145fe10bc89a",
  "_user": "bedapub",
  "_type": "src",
  "_file": "designit_0.5.0.9000.tar.gz",
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  "_created": "2026-05-30T09:13:26.000Z",
  "_published": "2026-05-30T12:41:20.834Z",
  "_distro": "noble",
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    "author": "julianesiebourg <51031392+julianesiebourg@users.noreply.github.com>",
    "committer": "GitHub <noreply@github.com>",
    "message": "Merge pull request #49 from bedapub/hotfix_plate_wrapper\n\nhotfix plate wrapper",
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  "_selfowned": true,
  "_usedby": 0,
  "_updates": [
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      "week": "2026-13",
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  "_tags": [],
  "_topics": [
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    "randomization"
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  "_stars": 8,
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    "name": "BEDApub",
    "description": "Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070 Basel"
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  "_exports": [
    "accept_leftmost_improvement",
    "assign_from_table",
    "assign_in_order",
    "assign_random",
    "batch_container_from_table",
    "BatchContainer",
    "BatchContainerDimension",
    "compile_possible_subgroup_allocation",
    "complete_random_shuffling",
    "drop_order",
    "first_score_only",
    "form_homogeneous_subgroups",
    "generate_terms",
    "get_order",
    "L1_norm",
    "L2s_norm",
    "mk_exponentially_weighted_acceptance_func",
    "mk_plate_scoring_functions",
    "mk_simanneal_acceptance_func",
    "mk_simanneal_temp_func",
    "mk_subgroup_shuffling_function",
    "mk_swapping_function",
    "optimize_design",
    "optimize_multi_plate_design",
    "osat_score",
    "osat_score_generator",
    "plot_plate",
    "shuffle_grouped_data",
    "shuffle_with_constraints",
    "shuffle_with_subgroup_formation",
    "sum_scores",
    "worst_score"
  ],
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      "name": "invivo_study_samples",
      "title": "A sample list from an in vivo experiment with multiple treatments and 2 strains",
      "object": "invivo_study_samples",
      "class": [
        "data.frame"
      ],
      "fields": [
        "AnimalID",
        "Strain",
        "Sex",
        "BirthDate",
        "Earmark",
        "ArrivalWeight",
        "Arrival.weight.Unit",
        "Litter"
      ],
      "rows": 59,
      "table": true,
      "tojson": true
    },
    {
      "name": "invivo_study_treatments",
      "title": "A treatment list together with additional constraints on the strain and sex of animals",
      "object": "invivo_study_treatments",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Treatment",
        "Strain",
        "Sex"
      ],
      "rows": 59,
      "table": true,
      "tojson": true
    },
    {
      "name": "longitudinal_subject_samples",
      "title": "Subject sample list with group and time plus controls",
      "object": "longitudinal_subject_samples",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "SampleID",
        "SampleType",
        "SubjectID",
        "Group",
        "Week",
        "Sex",
        "Age",
        "BMI",
        "SamplesPerSubject"
      ],
      "rows": 230,
      "table": true,
      "tojson": true
    },
    {
      "name": "multi_trt_day_samples",
      "title": "Unbalanced treatment and time sample list",
      "object": "multi_trt_day_samples",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "SampleName",
        "Well",
        "Time",
        "Treatment"
      ],
      "rows": 32,
      "table": true,
      "tojson": true
    },
    {
      "name": "plate_effect_example",
      "title": "Example dataset with a plate effect",
      "object": "plate_effect_example",
      "class": [
        "tbl_df",
        "tbl",
        "data.frame"
      ],
      "fields": [
        "row",
        "column",
        "conc",
        "log_conc",
        "treatment",
        "readout"
      ],
      "rows": 54,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "accept_leftmost_improvement",
      "title": "Alternative acceptance function for multi-dimensional scores in which order (left to right, e.g. first to last) denotes relevance.",
      "topics": [
        "accept_leftmost_improvement"
      ]
    },
    {
      "page": "assign_from_table",
      "title": "Distributes samples based on a sample sheet.",
      "topics": [
        "assign_from_table"
      ]
    },
    {
      "page": "assign_in_order",
      "title": "Distributes samples in order.",
      "topics": [
        "assign_in_order"
      ]
    },
    {
      "page": "assign_random",
      "title": "Assignment function which distributes samples randomly.",
      "topics": [
        "assign_random"
      ]
    },
    {
      "page": "batch_container_from_table",
      "title": "Creates a BatchContainer from a table (data.frame/tibble::tibble) containing sample and location information.",
      "topics": [
        "batch_container_from_table"
      ]
    },
    {
      "page": "BatchContainer",
      "title": "R6 Class representing a batch container.",
      "topics": [
        "BatchContainer"
      ]
    },
    {
      "page": "BatchContainerDimension",
      "title": "R6 Class representing a batch container dimension.",
      "topics": [
        "BatchContainerDimension"
      ]
    },
    {
      "page": "compile_possible_subgroup_allocation",
      "title": "Compile list of all possible ways to assign levels of the allocation variable to a given set of subgroups",
      "topics": [
        "compile_possible_subgroup_allocation"
      ]
    },
    {
      "page": "complete_random_shuffling",
      "title": "Reshuffle sample indices completely randomly",
      "topics": [
        "complete_random_shuffling"
      ]
    },
    {
      "page": "drop_order",
      "title": "Drop highest order interactions",
      "topics": [
        "drop_order"
      ]
    },
    {
      "page": "first_score_only",
      "title": "Aggregation of scores: take first (primary) score only",
      "topics": [
        "first_score_only"
      ]
    },
    {
      "page": "form_homogeneous_subgroups",
      "title": "Form groups and subgroups of 'homogeneous' samples as defined by certain variables and size constraints",
      "topics": [
        "form_homogeneous_subgroups"
      ]
    },
    {
      "page": "generate_terms",
      "title": "Generate 'terms.object' (formula with attributes)",
      "topics": [
        "generate_terms"
      ]
    },
    {
      "page": "get_order",
      "title": "Get highest order interaction",
      "topics": [
        "get_order"
      ]
    },
    {
      "page": "invivo_study_samples",
      "title": "A sample list from an in vivo experiment with multiple treatments and 2 strains",
      "topics": [
        "invivo_study_samples"
      ]
    },
    {
      "page": "invivo_study_treatments",
      "title": "A treatment list together with additional constraints on the strain and sex of animals",
      "topics": [
        "invivo_study_treatments"
      ]
    },
    {
      "page": "L1_norm",
      "title": "Aggregation of scores: L1 norm",
      "topics": [
        "L1_norm"
      ]
    },
    {
      "page": "L2s_norm",
      "title": "Aggregation of scores: L2 norm squared",
      "topics": [
        "L2s_norm"
      ]
    },
    {
      "page": "locations_table_from_dimensions",
      "title": "Create locations table from dimensions and exclude table",
      "topics": [
        "locations_table_from_dimensions"
      ]
    },
    {
      "page": "longitudinal_subject_samples",
      "title": "Subject sample list with group and time plus controls",
      "topics": [
        "longitudinal_subject_samples"
      ]
    },
    {
      "page": "mk_exponentially_weighted_acceptance_func",
      "title": "Alternative acceptance function for multi-dimensional scores with exponentially downweighted score improvements from left to right",
      "topics": [
        "mk_exponentially_weighted_acceptance_func"
      ]
    },
    {
      "page": "mk_plate_scoring_functions",
      "title": "Create a list of scoring functions (one per plate) that quantify the spatially homogeneous distribution of conditions across the plate",
      "topics": [
        "mk_plate_scoring_functions"
      ]
    },
    {
      "page": "mk_simanneal_acceptance_func",
      "title": "Generate acceptance function for an optimization protocol based on simulated annealing",
      "topics": [
        "mk_simanneal_acceptance_func"
      ]
    },
    {
      "page": "mk_simanneal_temp_func",
      "title": "Create a temperature function that returns the annealing temperature at a given step (iteration)",
      "topics": [
        "mk_simanneal_temp_func"
      ]
    },
    {
      "page": "mk_subgroup_shuffling_function",
      "title": "Created a shuffling function that permutes samples within certain subgroups of the container locations",
      "topics": [
        "mk_subgroup_shuffling_function"
      ]
    },
    {
      "page": "mk_swapping_function",
      "title": "Create function to propose swaps of samples on each call, either with a constant number of swaps or following a user defined protocol",
      "topics": [
        "mk_swapping_function"
      ]
    },
    {
      "page": "multi_trt_day_samples",
      "title": "Unbalanced treatment and time sample list",
      "topics": [
        "multi_trt_day_samples"
      ]
    },
    {
      "page": "optimize_design",
      "title": "Generic optimizer that can be customized by user provided functions for generating shuffles and progressing towards the minimal score",
      "topics": [
        "optimize_design"
      ]
    },
    {
      "page": "optimize_multi_plate_design",
      "title": "Convenience wrapper to optimize a typical multi-plate design",
      "topics": [
        "optimize_multi_plate_design"
      ]
    },
    {
      "page": "osat_score",
      "title": "Compute OSAT score for sample assignment.",
      "topics": [
        "osat_score"
      ]
    },
    {
      "page": "osat_score_generator",
      "title": "Convenience wrapper for the OSAT score",
      "topics": [
        "osat_score_generator"
      ]
    },
    {
      "page": "plate_effect_example",
      "title": "Example dataset with a plate effect",
      "topics": [
        "plate_effect_example"
      ]
    },
    {
      "page": "plot_plate",
      "title": "Plot plate layouts",
      "topics": [
        "plot_plate"
      ]
    },
    {
      "page": "shuffle_grouped_data",
      "title": "Generate in one go a shuffling function that produces permutations with specific constraints on multiple sample variables and group sizes fitting one specific allocation variable",
      "topics": [
        "shuffle_grouped_data"
      ]
    },
    {
      "page": "shuffle_with_constraints",
      "title": "Shuffling proposal function with constraints.",
      "topics": [
        "shuffle_with_constraints"
      ]
    },
    {
      "page": "shuffle_with_subgroup_formation",
      "title": "Compose shuffling function based on already available subgrouping and allocation information",
      "topics": [
        "shuffle_with_subgroup_formation"
      ]
    },
    {
      "page": "sum_scores",
      "title": "Aggregation of scores: sum up all individual scores",
      "topics": [
        "sum_scores"
      ]
    },
    {
      "page": "validate_samples",
      "title": "Validates sample data.frame.",
      "topics": [
        "validate_samples"
      ]
    },
    {
      "page": "worst_score",
      "title": "Aggregation of scores: take the maximum (i.e. worst score only)",
      "topics": [
        "worst_score"
      ]
    }
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