NEWS.md

In thierrygosselin/stackr: Run stacks software pipeline for RADseq analysis inside R

stackr 2.2.0 2020-10-08

• better summary_ functions to help decide thresholds, works with most stacks version.
• started to work with future package for better parallelization with PC.
• run_radproc: new function that will run RADProc and generate ustacks and cstacks file type.
• summary_reads: new function that highlight GC content and INDELs. It can also produce the read depth plot, in parallel for all sample found in the directory.

stackr 2.1.0 2019-11-28

• better summary_cstacks and summary_sstacks functions to help decide thresholds
• work a lot better with paired-end rad and the functionalities will be describe in a vignette.

stackr 2.0.9 2019-11-05

• updated to work with stacks 2.41
• new summary_cstacks and summary_sstacks functions to help decide thresholds

stackr 2.0.8 2019-01-14

• updated to work with stacks 2.3

stackr 2.0.7 2018-10-12

• updated run_gstacks to work with stacks 2.2

stackr 2.0.6 2018-08-23

• updated summary_ustacks to work with non-compressed files

stackr 2.0.5 2018-07-09

• stackr ready for R 3.5.1 "Feather Spray" released on 2018/07/05
• stackr updated to work with ggplot2 3.0.0

stackr 2.0.4 2018-03-02

• normalize_samples: new function to check the impact of biased read numbers per individual. The function normalize the number of reads and generate replicate samples.

stackr 2.0.3 2018-02-05

• stackr is working nice with beta8 and waiting for final and stable version

stackr 2.0.2 2018-01-16

• stackr is working nice with beta7c and waiting for final and stable version

stackr 2.0.1 2017-12-11

• stackr is working nice with beta6 and waiting for final and stable version

stackr 2.0.0 2017-10-11

• updated stackr to follow Stacks Version 2.0Beta1
• run_populations_v2 will replace run_populations in 2 updates
• run_tsv2bam: new function that runs Stacks tsv2bam module. Additionnally, this function will also generate a summary of Stacks tsv2bam and will merge in parallel BAM sample files into a unique BAM catalog file using SAMtools or Sambamba.
• run_gstacks runs Stacks gstacks module.

stackr 1.0.0 2017-08-18

• re-focusing stackr on running stacks pipeline within R.
• moving all non-essential functions in a new package called radiator.

stackr 0.5.9 2017-08-15

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

stackr 0.5.8 2017-08-15

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

stackr 0.5.7 2017-06-17

• stackr works with dplyr 0.7.0

stackr 0.5.6 2017-06-08

• tidy_genomic_data: bug fix that originated with the new version of PEGAS.
• summary_haplotypes : updated codes and output tables.
• pi: a new function to compute Nei's Pi nucleotide diversity from a wide range of input files. The haplotype version is found in summary_haplotypes.
• 2 new functions to work with vcf: merge_vcf and split_vcf.
• run_ustacks: allows to run Stacks ustacks module inside R with the option to run mismatch thresholds testing...

stackr 0.5.5 2017-05-22

• tidy_genomic_data : bug fix introduce with previous commit when fixing LOCUS and COL with stacks version > 1.44. Thanks to Eric Archer for highlighting the bug.

• summary_haplotypes: this function gets a new arguments, keep.consensus, to enable the calculation of pi to include or not the consensus markers presents in stacks haplotype file (e.g. batch_1.haplotypes.tsv). This argument works to circumvent the impact of using a whitelist of markers, that potentially removed those markers in previous versions. Also changed in this function, the summary table include a POLYMORPHISM column that no longer include the artifact marker counts (markers with more than 2 alleles). This information is kept in a separate column (as before).

stackr 0.5.4 2017-04-06

• detect_duplicate_genomes : huge speed bump for pairwise genome similarity method. Instead of hours the range is more in minutes.

stackr 0.5.3 2017-04-05

• stackr_imputations_module : better integration of VCF with haplotypes so that nucleotide information is kept during imputations.
• filter_fis : bug fix when no heterozygote were found. Thanks to Manuel Lamothe.

stackr 0.5.2 2017-03-27

• stackr_imputations_module : work on faster on-the-fly random forest and extreme gradient tree boosting algorithm.

stackr 0.5.1 2017-03-21

Major work on tidy_genomic_data: platypus vcf files are correctly imported more efficient when working with vcf files * better parallelization during parsing and cleaning

stackr 0.5.0

• better parallelization of summary_haplotypes function. With progress bar...
• bug fix with summary_haplotypes not properly summarizing info when no assembly artifacts were found

stackr 0.4.9

• bug fix with detection of mixed bi/multi allelic dataset. The bug was detected in tidy_genomic_data and genomic_converter functions.

stackr 0.4.8

• safer use and better parsing of strataG object to work with tidy data and pass Travis CI.

stackr 0.4.7

• Better parsing of genepop file with 2 characters for allele coding
• Only 10% of markers are now used for increase speed of bi-allelic markers detection
• Work on imputation module that will be functional in the next version bump
• Better code for the progress bar (Linux and Mac only) that now shows an ETA along the progress.

stackr 0.4.6

• I'm pleased to announce that stackr parallel mode now works with Windows! Nothing to install, just need to choose the number of CPU, the rest is done automatically.
• haplo2colony is deprecated. Use the new function called write_colony!
• write_colony: works similarly to the deprecated function haplo2colony,
  • with the major advantage that it's no longer restricted to STACKS haplotypes file.
  • The function is using the tidy_genomic_data module to import files. So you can choose one of the 10 input file formats supported by stackr!
  • other benefits also include the possibility to efficiently test MAF, snp.ld, haplotypes/snp approach, whitelist of markes, blacklist of individuals, blacklist of genotypes, etc. with the buit-it arguments.
  • the function only keeps markers in common between populations/groups and is removing monomorphic markers.
  • Note: there are several defaults in the function and it's a complicated file format, so make sure to read the function documentation, please, and COLONY manual.

stackr 0.4.5

• temporary fix to tidy_genomic_data to read unconventional Tassel VCF
• new function ibdg_fh computes the FH measure that was previously computed in summary_haplotypes. It now works with biallelic and multiallelic data. The FH measure is based on the excess in the observed number of homozygous genotypes within an individual relative to the mean number of homozygous genotypes expected under random mating (see function for details). The IBDg in the name is because the measure is a proxy of the realized proportion of the genome that is identical by descent by reference to the current population under hypothetical random mating.
• missing_visualization now computes the FH measure and look for correlation with average missingness per individual.
• tidy_stacks_haplotypes_vcf is now deprecated in favor of using tidy_genomic_data that will import haplotypic vcf files.

stackr 0.4.4

• several updates to make functions faster.
• stackr_imputations_module no longer imputes globally after imputations by populations. Instead, use common.markers or not to test impacts.
• bug fix with ref_alt_alleles that was not working properly inside the imputation module.
• snp_ld is not a separate module available for users. Check documentation.
• missing_visualization now show the proportion of variance with plot axis text.

stackr 0.4.3

• bug fix in summary_haplotypes stemming from a new readr version
• artifacts replace paralogs in summary_haplotypes

stackr 0.4.2

• gtypes object from [strataG] (https://github.com/EricArcher/strataG) package can now be read/write in/out of Stackr using the tidy_genomic_data and genomic_converter functions.

stackr 0.4.1

• update missing_visualization function to include more PCoA plots

stackr 0.4.0

• couple of bug fix for detecting file formats

stackr 0.3.9

• several performance update
• couple of bug fix for detecting file formats

stackr 0.3.8

• fixed a bug in filter_genotype_likelihood, since the updated function to the interactive mode, some old code where still present in if/else sentences, breaking the code. Thanks to Jaromir Guzinski for the bug report.

stackr 0.3.7

• fixed a bug in write_vcf, the function was using REF/ALT coding in integer not character format. This function is used inside vcf_imputation and sometimes inside genomic_converter. Thanks to @jeansebastienmoore for highlighting the problem.

stackr 0.3.6

• fixed a bug in vcf_imputation, the function now calls genomic_converter with all the bells and whistles of that function (updated vcf import and imputations modules)

stackr 0.3.5

• updated tidy_genepop to read other flavors of the famous file format
• extracted a code block to create a new function called tidy_fstat

stackr 0.3.4

• updated documentation
• bug fix in summary_haplotypes introduced by the new version of dplyr::distinct (0.5.0)
• calculations of Pi is done in parallel inside summary_haplotypes

stackr 0.3.3

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

stackr 0.3.2

• genomic_converter including all the vcf2... function can now use phase/unphase genotypes. Some pyRAD vcf (e.g. 3.0.64) have a mix of GT format with / and |. e.g. missing GT = ./. and genotyped individuals = 0|0. I'm not sure it follows VCF specification, but stackr can now read those vcf files.
• vcf2dadi is more user-friendly for scientist with in- and out-group metadata, using STACKS or not.

stackr 0.3.1

• Bug fix: combined use of if (getRversion() >= "2.15.1") utils::globalVariables("variable") and @inheritParams was not showing all the argument description.

stackr 0.3.0

• Update that makes my coding life easier.
• Several internal functions to convert from a tidy dataframe to: vcf, plink, genind, genlight, gtypes, hierfstat, genepop, structure and betadiv are now separate modules available to users (look for write_... with the outputformat)
• New function genomic_converter: If you want the to convert from the supported input file formats to many output formats, at once, this is the function. With the new function genomic_converter, import and imputations are only done once, saving time if you were generating different output WITH imputations.
• Change: all the vcf2... functions (excep vcf2dadi) are now a shorcut of genomic_converter. This is particularly interesting and faster if you were generating different output WITH imputations. This makes the functions vcf2... and genomic_converter easier to debug for me and more stable for users.
• Deprecated: the haplo2... functions are all deprecated and replaced by genomic_converter, except haplo2colony that requires so many arguments that it would be too complicated, for now, to integrate with genomic_converter.
• New feature: when arguments pop.select, blacklist.id and imputation.method are used, the REF and ALT alleles are now re-computed to account for the filters and imputations.

stackr 0.2.9

• bug fix in tidy_genomic_data
• bug fix between stackr -> devtools -> github -> travis, [this page helped] (http://itsalocke.com/using-travis-make-sure-use-github-pat/)

stackr 0.2.8

• bug fix in tidy_genomic_data while using data.table::melt.data.table instead of tidyr::gather, and forgot to (i) add variable.factor = FALSE when melting the vcf and (ii) use as_data_frame at the end of the melting to be able to continue working with dplyr verbs.

stackr 0.2.7

• Added a NEWS.md file to track changes to the package.
• New function: individuals2strata. Several functions in stackr and [assigner] (https://github.com/thierrygosselin/assigner) requires a strata argument, i.e. a data frame with the individuals and associated groupings. You can do it manually, however, if your individuals have a consistent naming scheme (e.g. SPECIES-POPULATION-MATURITY-YEAR-ID = CHI-QUE-ADU-2014-020), use this function to rapidly create a strata file.
• New function: tidy_genomic_data. Transform common genomic dataset format in a tidy data frame. Used internally in stackr and [assigner] (https://github.com/thierrygosselin/assigner) and might be of interest for users.
• New function: read_long_tidy_wide. Read genomic data frames in long/tidy and wide format. Used internally in stackr and [assigner] (https://github.com/thierrygosselin/assigner) and might be of interest for users.
• New function: stackr_imputations_module. Map-independent imputation of missing genotype using Random Forest or the most frequent category. Impute genotypes or alleles. Used internally in stackr and [assigner] (https://github.com/thierrygosselin/assigner) and might be of interest for users.
• New function: find_duplicate_id Compute pairwise genome similarity to highligh potential duplicate individuals.

stackr 0.2.6

• dart2df_genind_plink: swiss army knife tool to prepare DArT output file (wide or binary format) for population genetics analysis. Import, filter and transform a DArT output file to different format: tidy data frame of genotypes, genind object and/or PLINK tped/tfam format. Map-independent imputation also available.

stackr 0.2.5

• vcf2plink: to easily convert a VCF file created in STACKS to a PLINK input file (tped/tfam format). This function comes with the commonly used arguments in stackr: map-independent imputation, whitelist, blacklist, common marker filtering, etc.

• data_pruning: to prune your dataset with whitelist, blacklist of individuals, erase genotypes, use common markers and other filtering (see function argument while waiting for the upcomming documentation).

stackr 0.2.4

• updated the vcf_imputation function for the commonly used arguments in stackr.

stackr 0.2.3

• vcf2dadi: to easily convert a VCF file created in STACKS to a dadi input file. This function comes with the commonly used arguments in stackr: map-independent imputation, whitelist, blacklist, common marker filtering, etc.

stackr 0.2.2

• vcf2genepop: to easily convert a VCF file created in STACKS to a genepop input file. This function comes with the commonly used arguments in stackr: map-dependent imputation, whitelist, blacklist, etc. For the haplotype version, see haplo2genepop.

stackr 0.2.1

• 'read_stacks_vcf' can now use a whitelist or blacklist of loci that works with CHROM and/or SNP and/or LOCUS.
• 'filter_maf', 'filter_fis', 'filter_het' and 'filter_genotype_likelihood' now works by haplotypes or SNP.

stackr 0.2.0

Introducing several new functions: vcf2betadiv: to easily convert a VCF file created in STACKS to a betadiv input file. vcf2genind: same as haplo2genind but works with SNP instead of haplotypes. * vcf2hierfstat: same as haplo2hierfstat but works with SNP instead of haplotypes.

stackr 0.1.5

Introducing haplo2gsi_sim function. Conversion of STACKS haplotypes file into a gsi_sim data input file. Markers can be subsampled. Map-independent imputations using Random Forest or the most frequent allele are options also available for this function. [gsi_sim] (https://github.com/eriqande/gsi_sim) is a tool developed by Eric C. Anderson for doing and simulating genetic stock identification.

stackr 0.1.4

Introducing haplo2fstat function. Conversion of STACKS haplotypes file into a hierfstat object and fstat file. Access all the functions in the R package [hierfstat] (https://github.com/jgx65/hierfstat).

stackr 0.1.3

Map-independent imputations of a VCF file created by STACKS. Two options are available for imputations: using Random Forest or the most frequent allele.

Before imputations, the VCF file can be filtered with:

• a whitelist of loci (to keep only specific loci...)
• a blacklist of individuals (to remove individuals or entire populations...)
• also, a list of genotypes with bad coverage and/or genotype likelihood can be supplied to erase the genotypes before imputations (for more details look at the function: blacklist_erase_genotype).

stackr 0.1.2

The summary_haplotypes function now outputs: Putative paralogs, consensus, monomorphic and polymorphic loci The haplotype statistics for the observed and expected homozygosity and heterozygosity Wright’s inbreeding coefficient (Fis) Proxy measure of the realized proportion of the genome that is identical by descent (IBDG). The FH measure is based on the excess in the observed number of homozygous genotypes within an individual relative to the mean number of homozygous genotypes expected under random mating (Keller et al., 2011; Kardos et al., 2015). * Nucleotide diversity (Pi), considering the consensus loci in the catalog (i.e. reads with no variation between population). It's Nei & Li (1979) function, adapted to the GBS reality.

Keller MC, Visscher PM, Goddard ME. 2011. Quantification of inbreeding due to distant ancestors and its detection using dense single nucleotide polymorphism data. Genetics, 189, 237–249.

Kardos M, Luikart G, Allendorf FW. 2015. Measuring individual inbreeding in the age of genomics: marker-based measures are better than pedigrees. Heredity, 115, 63–72.

Nei M, Li WH. 1979. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proceedings of the National Academy of Sciences of the United States of America, 76, 5269–5273.

The haplo2colony function Converts the file to the required COLONY input file Can filter the haplotypes file with a whitelist of loci and a blacklist of individuals Can impute the data with Random Forest or the most frequent category Use the print.all.colony.opt to output all COLONY options to the file. This however requires manual curation of the file to work directly with COLONY.

thierrygosselin/stackr documentation built on Nov. 11, 2020, 11 a.m.