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Changelog

Source: NEWS.md

assigner 0.7.0 2025-07-01

  • assigner::fst_WC84: work faster and as better reporting

assigner 0.6.0 2024-11-06

  • refresh for new R version

assigner 0.5.9 2023-03-15

  • work on assigner::fst_WC84

assigner 0.5.8 2020-10-20

  • Version bump because it updates numerous packages: tidyr, readr, using future, carrier.
  • GitHub actions to run the R-CMD-check on the 3 OS.

assigner 0.5.7 2020-01-21

  • Bug fix in heatmap: digits was fixed to 5 and when pop.levels = NULL, the heatmap was all mixed up. Thanks to @siberianhigh for highlighting the bug.

assigner 0.5.6 2019-05-01

  • included 2 simulated datasets
  • updated documentation of assignment_ngs
  • vignette to get started with assigner, finally!
  • this is really starting to smell like a CRAN release
  • work on travis CI
  • work on pkgdown

assigner 0.5.5 2019-04-25

  • cosmetic changes to the package: using pkgdown
  • updated documentation of assignment_ngs

assigner 0.5.4 2019-03-12

  • fst_WC84: work faster
  • continue to integrate assigner with SeqArray and GDS object/file

assigner 0.5.3 2019-02-25

  • fst_WC84: work with radiator v.1.0
  • will continue updating fucntions to work with latest radiator release and work toward releasing the official v.1.0 of assigner.
  • Imputation module was removed from assigner and now lives exclusively in package grur

assigner 0.5.2 2018-07-09

  • working to make assigner work correctly with ggplot2 v.3.0.0
  • assigner ready for R 3.5.1 “Feather Spray” released on 2018/07/05

assigner 0.5.1 2018-06-21

  • bug in assignment_mixture generated by purrr::df replaced recently by purrr:dfr. Changed DESCRIPTION field accordingly.

assigner 0.5.0 2017-12-12

  • subsample argument in assignment_ngs and assignment_mixture can now automatically detect the smallest sample size in the data’s grouping. So you can use subsample = "min" to let the function decide (if your not sure).

assigner 0.4.9 2017-08-18

  • migration of assigner from using stackr -> radiator

assigner 0.4.8 2017-08-15

  • restored progress bar when using parallel computing by installing the new dev version of pbmcapply package.

assigner 0.4.7 2017-08-15

  • bug fix: removed the progress bar when using parallel computing. This is temporary, while waiting for a fix with pbmcapply package.

assigner 0.4.6 2017-06-17

  • assigner works with dplyr v.0.7.0

assigner 0.4.5 2017-04-25

  • dlr: simplified arguments, faster function and now creates the Dlr plots
  • dependencies to package SNPRelate are removed until the bugs with Fst calculation are resolved.

assigner 0.4.4 2017-04-12

  • bug fix in assignment_ngs introduced in last commit that was suppose to be fix. Problem introduced by stackr::change_pop_names.

assigner 0.4.3 2017-04-02

  • it’s now official, assigner as a logo
  • faster fst_NEI87
  • unbalanced design impact on estimates can be tested with subsample and iteration.subsample in fst_NEI87 and fst_WC84

assigner 0.4.2

  • until SNPRelate bias issue is resolved the option is unavailable
  • better use of pbmcapply for Windows
  • imputations is being reworked and will be buggy until the next update. The codes are being completely re-written and arguments will change (for the better).

assigner 0.4.1

  • debug code to work in parallel with Windows
  • code cleaning to prep for CRAN

assigner 0.4.0

  • assignment_ngs and assignment_mixture code cleaning to prep for CRAN and make them easier to debug.

assigner 0.3.9

  • I’m pleased to announce that assigner now works in parallel with Windows
  • bug fix introduce in last commit in write_gsi_sim where the file was not created properly from an internal module.

assigner 0.3.8

  • assigner::fst_WC84 can now use SNPRelate to compute Fst. The confidence intervals are not implemented, yet. The speed increase left me speechless, dataset with 30K snp are computed in less than 15 sec!

assigner 0.3.7

assigner 0.3.6

  • bug fix assignment_ngs during imputations, the imputation module could not recognise that REF/ALT alleles are not necessary or usefull for assignment analysis. *enhancement to assignment_ngs and assignment_mixture so that when marker.number include "all" the iteration.method is set automatically to 1 when conducting the assignment with all the markers. Iterations at this point is useless and a waist of time.
  • random seed number is now stored in the appropriate files.
  • assignment_mixture: with assignment.analysis = "gsi_sim the unknown/mixture samples are compared with baseline populations using common markers between the pair. Now, the tables include the number of markers used. The summary provides the mean number of markers. This number will change each time randomness is used.

assigner 0.3.5

  • bug fix in population not recognise properly

assigner 0.3.4

  • fst_NEI87: very fast function that can compute: the overall and pairwise Nei’s (1987) fst and f’st (prime). Bootstrap resampling of markers is avalaible to build Confidence Intervals. The estimates are available as a data frame and a matrix with upper diagonal filled with Fst values and lower diagonal filled with the confidence intervals. Jost’s D is also given ;)

assigner 0.3.3

  • fst_WC84: bug fix, the function was not properly configured for multi-allelic markers (e.g. microsatellite, and haplotype format from STACKS). Thanks to Craig McDougall for catching this.

assigner 0.3.2

  • assignment_mixture: added a check to throw an error when pop.levels != the pop.id in strata

assigner 0.3.1

assignment_mixture: * updated with latest modules from stackr. * simplified the identification of mixture or unknown samples. See doc.

assigner 0.3.0

  • updated vignettes
  • major bug fix that involved dplyr new version (0.5.0) and mostly with the use of dplyr::distinct

assigner 0.2.9

assigner 0.2.8

assigner 0.2.7

  • you need to update [stackr] (https://github.com/thierrygosselin/stackr) to v.0.2.7 to appreciate this new version of assigner.

  • updated assignment_ngs with the separate stackr modules to simplify the function.

  • new data file available for assignment_ngs: genepop and genind object.

  • assignment_ngs now accept any vcf input file! i.e. it’s no longer limited to stacks vcf.

  • new arguments in assignment_ngs. The assignment using dapc can now use the optimized alpha score adegenet.dapc.opt == "optim.a.score" or the cross-validation adegenet.dapc.opt == "xval". This is useful for fine tuning the trade-off between power of discrimination and over-fitting (for stability of group membership probabilities). Cross validation with adegenet.dapc.opt == "xval" doesn’t work with missing data, so it’s only available with imputed data (i.e. imputation.method == "rf" or "max"). With non imputed data or the default: the optimized alpha-score is used (adegenet.dapc.opt == "optim.a.score"). When using adegenet.dapc.opt == "xval", 2 new arguments are available:

  1. adegenet.n.rep and (2) adegenet.training. See documentation for details.

  • removed arguments in assignment_ngs. Removed the pop.id.start and pop.id.end arguments that were confusing people. For those used to these arguments, they are now recycled in the new function individuals2strata in [stackr] (https://github.com/thierrygosselin/stackr). The strata file created by this function can be used with the strata argument in assignment_ngs.

  • 2 modified arguments in assignment_ngs: (1) gsi_sim.filename is now filename; and

  1. if you didn’t use the imputation argument, replace imputation.method = FALSE to imputation.method = NULL or leave the argument missing.

  • simplified sections of codes in assignment_ngs that dealt with strata, pop.levels and pop.labels.

  • new function: write_gsi_sim. Write a gsi_sim file from a data frame (wide or long/tidy). Used internally in [assigner] (https://github.com/thierrygosselin/assigner) and might be of interest for users.

assigner 0.2.6

  • Added a NEWS.md file to track changes to the package.
  • fst_WC84 is now a separate and very fast function that can compute: the overall and pairwise Weir and Cockerham 1984 Theta/Fst. Bootstrap resampling of markers is avalaible to build Confidence Intervals (For Louis Bernatchez and his students;). The estimates are available as a data frame and a matrix with upper diagonal filled with Fst values and lower diagonal filled with the confidence intervals.

assigner 0.2.5

  • cleaner code for strata section
  • bug fix restricted to assignment_ngs + assignment.analysis = "adegenet" + sampling.method = "ranked". A line at the beginning of a gsi_sim code section was deleted makig the assignment with adegenet go through that chunk of code and causing 100% assignment! if (assignment.analysis = “gsi_sim”) {code} prevent this problem…

assigner 0.2.4

  • bug fixed using adegenet that was introduced in v.0.2.3
  • introducing a new function import_subsamples_fst to import the fst ranking results from all the subsample runs inside an assignment folder.

assigner 0.2.3

  • bug fixed in the compilation results section when no pop.id.start and end are used.

assigner 0.2.1

  • updated the function assignment_mixture with sampling.method = "ranked" and assignment.analysis = "adegenet".

assigner 0.2.0

  • new function: assignment_mixture for mixture analysis.

assigner 0.1.9

  • Simplified gsi_sim install

assigner 0.1.8

assigner 0.1.7

  • New input file: Re-introduced the haplotype data frame file from stacks.
  • Argument name change: imputations is now impute.method.
  • New argument: impute with 2 options: impute = "genotype" or impute = "allele".

assigner 0.1.6

  • Input file argument is now data and covers the three types of files the function can use: VCF file, PLINK tped/tfam or data frame of genotypes file.
  • Huge number of markers (> 50 000 markers) can now be imported in PLINK tped/tfam format. The first 2 columns of the tfam file will be used for the strata argument, unless a new one is provided. Columns 1, 3 and 4 of the tped are discarded. The remaining columns correspond to the genotype in the format 01/04 where A = 01, C = 02, G = 03 and T = 04. For A/T format, use PLINK or bash to convert. Use [VCFTOOLS] (http://vcftools.sourceforge.net/) with --plink-tped to convert very large VCF file. For .ped file conversion to .tped use [PLINK] (http://pngu.mgh.harvard.edu/~purcell/plink/) with --recode transpose.

assigner 0.1.5

  • bug fix in method = "random" and imputation

assigner 0.1.4

  • Changed function name, from GBS_assignment to assignment_ngs. Stands for assignment with next-generation sequencing data.
  • New argument df.file if you don’t have a VCF file. See documentation.
  • New argument strata if you don’t have population id or other metadata info in the individual name. See documentation.

assigner 0.1.3

  • Changed arguments THL to thl and snp.LD to snp.ld to follow convention.
  • iterations.subsample changed to iteration.subsample.
  • iterations changed to iteration.method to avoid confusion with other iteration arguments.
  • Removed baseline and mixture arguments from the function GBS_assignment. These options will be re-introduce later in a separate function.
  • Using marker.number higher than the number of markers in the data set was causing problems. This could arise when using arguments that removed markers from the dataset (e.g. snp.ld, common.markers, and maf filters).

assigner 0.1.2

  • new version to update with gsi_sim new install instruction for Linux and Mac. After re-installing assigner package, follow the instruction to re-install the new [gsi_sim] (https://github.com/eriqande/gsi_sim). And delete the old binary ‘gsisim’ in the /usr/local/bin folder with the following Terminal command: sudo rm /usr/local/bin/gsisim