Title: | A Shiny App to Visualize Genetic Maps and QTL Analysis in Polyploid Species |
Version: | 0.4.1 |
Maintainer: | Cristiane Taniguti <chtaniguti@tamu.edu> |
Description: | Provides a graphical user interface to integrate, visualize and explore results from linkage and quantitative trait loci analysis, together with genomic information for autopolyploid species. The app is meant for interactive use and allows users to optionally upload different sources of information, including gene annotation and alignment files, enabling the exploitation and search for candidate genes in a genome browser. In its current version, 'VIEWpoly' supports inputs from 'MAPpoly', 'polymapR', 'diaQTL', 'QTLpoly', 'polyqtlR', 'GWASpoly', and 'HIDECAN' packages. |
License: | GPL (≥ 3) |
Depends: | R (≥ 4.0) |
Imports: | shiny (≥ 1.6.0), shinyjs, shinythemes, shinyWidgets, shinydashboard, config (≥ 0.3.1), golem (≥ 0.3.1), JBrowseR, dplyr, tidyr, DT, ggplot2, ggpubr, plotly, vroom, abind, reshape2, markdown, stats, hidecan, purrr |
URL: | https://github.com/mmollina/viewpoly |
BugReports: | https://github.com/mmollina/viewpoly/issues |
Encoding: | UTF-8 |
RoxygenNote: | 7.2.3 |
Suggests: | testthat (≥ 3.0.0), shinytest, rlang, pkgload, vdiffr |
Config/testthat/edition: | 3 |
Language: | en-US |
NeedsCompilation: | no |
Packaged: | 2024-03-28 22:16:27 UTC; chtan |
Author: | Cristiane Taniguti [aut, cre], Gabriel de Siqueira Gesteira [aut], Jeekin Lau [aut], Olivia Angelin-Bonnet [aut], Susan Thomson [ctb], Guilherme da Silva Pereira [ctb], David Byrne [ctb], Zhao-Bang Zeng [ctb], Oscar Riera-Lizarazu [ctb], Marcelo Mollinari [aut] |
Repository: | CRAN |
Date/Publication: | 2024-03-28 22:30:02 UTC |
Estimate breeding values - Adapted function from QTLpoly
Description
Estimate breeding values - Adapted function from QTLpoly
Usage
breeding_values(qtl_info, probs, selected_mks, blups, beta.hat, pos)
Arguments
qtl_info |
data.frame with: LG - linkage group ID; Pos - position in linkage map (cM); Pheno - phenotype ID; Pos_lower - lower position of confidence interval; Pos_upper - upper position of the confidence interval; Pval - QTL p-value; h2 - herdability |
probs |
data.frame with first column (named 'ind') as individuals ID and next columns named with markers ID and containing the genotype probability at each marker |
selected_mks |
data.frame with: LG - linkage group ID; mk - marker ID; pos - position in linkage map (cM) |
blups |
data.frame with: haplo - haplotype ID; pheno - phenotype ID; qtl - QTL ID; u.hat - QTL estimated BLUPs |
beta.hat |
data.frame with: pheno - phenotype ID; beta.hat - estimated beta |
pos |
selected QTL position (cM) |
Value
data.frame containing breeding values
Calculates homologues probabilities - Adapted from MAPpoly
Description
Calculates homologues probabilities - Adapted from MAPpoly
Usage
calc_homologprob(probs, selected_mks, selected_lgs)
Arguments
probs |
data.frame with first column (named 'ind') as individuals ID and next columns named with markers ID and containing the genotype probability at each marker |
selected_mks |
data.frame with: LG - linkage group ID; mk - marker ID; pos - position in linkage map (cM) |
selected_lgs |
vector containing selected LGs ID |
Value
object of class mappoly.homoprob
Viewmap object sanity check
Description
Viewmap object sanity check
Usage
check_viewmap(viewmap_obj)
Arguments
viewmap_obj |
an object of class |
Value
if consistent, returns 0. If not consistent, returns a
vector with a number of tests, where TRUE
indicates
a failed test.
Author(s)
Cristiane Taniguti, chtaniguti@tamu.edu
Viewpoly object sanity check
Description
Viewpoly object sanity check
Usage
check_viewpoly(viewpoly_obj)
Arguments
viewpoly_obj |
an object of class |
Value
if consistent, returns 0. If not consistent, returns a
vector with a number of tests, where TRUE
indicates
a failed test.
Author(s)
Cristiane Taniguti, chtaniguti@tamu.edu
viewqtl object sanity check
Description
viewqtl object sanity check
Usage
check_viewqtl(viewqtl_obj)
Arguments
viewqtl_obj |
an object of class |
Value
if consistent, returns 0. If not consistent, returns a
vector with a number of tests, where TRUE
indicates
a failed test.
Author(s)
Cristiane Taniguti, chtaniguti@tamu.edu
Change ggplot coordinates to plot radar - From package see
Description
Change ggplot coordinates to plot radar - From package see
Usage
coord_radar(theta = "x", start = 0, direction = 1)
Arguments
theta |
ariable to map angle to (x or y) |
start |
offset of starting point from 12 o'clock in radians. Offset is applied clockwise or anticlockwise depending on value of direction. |
direction |
1, clockwise; -1, anticlockwise |
Get effects information
Description
Get effects information
Usage
data_effects(
qtl_info,
effects,
pheno.col = NULL,
parents = NULL,
lgs = NULL,
groups = NULL,
position = NULL,
software,
design = c("bar", "circle", "digenic")
)
Arguments
qtl_info |
data.frame with: LG - linkage group ID; Pos - position in linkage map (cM); Pheno - phenotype ID; Pos_lower - lower position of confidence interval; Pos_upper - upper position of the confidence interval; Pval - QTL p-value; h2 - herdability |
effects |
data.frame with: pheno - phenotype ID; qtl.id - QTL ID; haplo - haplotype ID; effect - haplotype effect value |
pheno.col |
integer identifying phenotype |
parents |
vector with parents ID |
lgs |
vector of integers with linkage group ID of selected QTL/s |
groups |
vector of integers with selected linkage group ID |
position |
vector of centimorgan positions of selected QTL/s |
software |
character defining which software was used for QTL analysis. Currently support for: QTLpoly, diaQTL and polyqtlR. |
design |
character defining the graphic design. Options: 'bar' - barplot of the effects; 'circle' - circular plot of the effects (useful to compare effects of different traits); 'digenic' - heatmap plotting sum of additive effects (bottom diagonal) and digenic effects (top diagonal) when present |
Value
ggplot graphic
Returns the class with the highest probability in a genotype probability distribution. Function from MAPpoly.
Description
Returns the class with the highest probability in a genotype probability distribution. Function from MAPpoly.
Usage
dist_prob_to_class(geno, prob.thres = 0.9)
Arguments
geno |
the probabilistic genotypes contained in the object
|
prob.thres |
probability threshold to select the genotype. Values below this genotype are assumed as missing data |
Value
a matrix containing the doses of each genotype and marker. Markers are disposed in rows and individuals are disposed in columns. Missing data are represented by NAs
Draws linkage map, parents haplotypes and marker doses Adapted from MAPpoly
Description
Draws linkage map, parents haplotypes and marker doses Adapted from MAPpoly
Usage
draw_map_shiny(
left.lim = 0,
right.lim = 5,
ch = 1,
maps.dist,
ph.p1,
ph.p2,
d.p1,
d.p2,
snp.names = TRUE,
software = NULL
)
Arguments
left.lim |
covered window in the linkage map start position |
right.lim |
covered window in the linkage map end position |
ch |
linkage group ID |
ph.p1 |
list containing a data.frame for each group with parent 1 estimated phases. The data.frame contain the columns: 1) Character vector with chromosome ID; 2) Character vector with marker ID; 3 to (ploidy number)*2 columns with each parents haplotypes |
ph.p2 |
list containing a data.frame for each group with parent 2 estimated phases. See ph.p1 parameter description. |
d.p1 |
list containing a data.frame for each group with parent 1 dosages. The data.frame contain the columns: 1) character vector with chromosomes ID; 2) Character vector with markers ID; 3) Character vector with parent ID; 4) numerical vector with dosage |
d.p2 |
list containing a data.frame for each group with parent 2 dosages. See d.p1 parameter description |
snp.names |
logical TRUE/FALSE. If TRUE it includes the marker names in the plot |
software |
character defined from each software it comes from |
maps |
list containing a vector for each linkage group markers with marker positions (named with marker names) |
Value
graphic representing selected section of a linkage group
Filter non-conforming classes in F1, non double reduced population. Function from MAPpoly.
Description
Filter non-conforming classes in F1, non double reduced population. Function from MAPpoly.
Usage
filter_non_conforming_classes(input.data, prob.thres = NULL)
Arguments
input.data |
object of class mappoly |
prob.thres |
threshold for filtering genotypes by genotype probability values. If NULL, the filter is not applied. |
Value
filtered mappoly.data
object
Extract the LOD Scores in a 'mappoly.map'
object
Function from MAPpoly.
Description
Extract the LOD Scores in a 'mappoly.map'
object
Function from MAPpoly.
Usage
get_LOD(x, sorted = TRUE)
Arguments
x |
an object of class |
sorted |
logical. if |
Value
a numeric vector containing the LOD Scores
Color pallet ggplot-like - Adapted from MAPpoly
Description
Color pallet ggplot-like - Adapted from MAPpoly
Usage
gg_color_hue(n)
Arguments
n |
number of colors |
Map functions - from MAPpoly
Description
Map functions - from MAPpoly
Usage
imf_h(r)
Arguments
r |
vector with recombination fraction values |
Value
vector with genetic distances
Import data from polymapR
Description
Function to import datasets from polymapR. Function from MAPpoly.
Usage
import_data_from_polymapR(
input.data,
ploidy,
parent1 = "P1",
parent2 = "P2",
input.type = c("discrete", "probabilistic"),
prob.thres = 0.95,
pardose = NULL,
offspring = NULL,
filter.non.conforming = TRUE,
verbose = TRUE
)
Arguments
input.data |
a |
ploidy |
the ploidy level |
parent1 |
a character string containing the name (or pattern of genotype IDs) of parent 1 |
parent2 |
a character string containing the name (or pattern of genotype IDs) of parent 2 |
input.type |
Indicates whether the input is discrete ("disc") or probabilistic ("prob") |
prob.thres |
threshold probability to assign a dosage to offspring. If the probability
is smaller than |
pardose |
matrix of dimensions (n.mrk x 3) containing the name of the markers in the first column, and the dosage of parents 1 and 2 in columns 2 and 3. (see polymapR vignette) |
offspring |
a character string containing the name (or pattern of genotype IDs) of the offspring
individuals. If |
filter.non.conforming |
if |
verbose |
if |
Details
See examples at https://rpubs.com/mmollin/tetra_mappoly_vignette.
Value
object of class mappoly.data
Author(s)
Marcelo Mollinari mmollin@ncsu.edu
References
Bourke PM et al: (2019) PolymapR — linkage analysis and genetic map construction from F1 populations of outcrossing polyploids. _Bioinformatics_ 34:3496–3502. doi: 10.1093/bioinformatics/bty1002
Mollinari, M., and Garcia, A. A. F. (2019) Linkage analysis and haplotype phasing in experimental autopolyploid populations with high ploidy level using hidden Markov models, _G3: Genes, Genomes, Genetics_. doi: 10.1534/g3.119.400378
Import phased map list from polymapR
Description
Function to import phased map lists from polymapR. Function from MAPpoly.
Usage
import_phased_maplist_from_polymapR(maplist, mappoly.data, ploidy = NULL)
Arguments
maplist |
a list of phased maps obtained using function
|
mappoly.data |
a dataset used to obtain |
ploidy |
the ploidy level |
Details
See examples at https://rpubs.com/mmollin/tetra_mappoly_vignette.
Value
object of class mappoly.map
Author(s)
Marcelo Mollinari mmollin@ncsu.edu
References
Bourke PM et al: (2019) PolymapR — linkage analysis and genetic map construction from F1 populations of outcrossing polyploids. _Bioinformatics_ 34:3496–3502. doi: 10.1093/bioinformatics/bty1002
Mollinari, M., and Garcia, A. A. F. (2019) Linkage analysis and haplotype phasing in experimental autopolyploid populations with high ploidy level using hidden Markov models, _G3: Genes, Genomes, Genetics_. doi: 10.1534/g3.119.400378
Is it a probability dataset? Function from MAPpoly.
Description
Is it a probability dataset? Function from MAPpoly.
Usage
is.prob.data(x)
Arguments
x |
object of class |
Value
TRUE/FALSE indicating if genotype probability information is present
Gets summary information from map. Adapted from MAPpoly
Description
Gets summary information from map. Adapted from MAPpoly
Usage
map_summary(left.lim = 0, right.lim = 5, ch = 1, maps, d.p1, d.p2)
Arguments
left.lim |
covered window in the linkage map start position |
right.lim |
covered window in the linkage map end position |
ch |
linkage group ID |
maps |
list containing a vector for each linkage group markers with marker positions (named with marker names) |
d.p1 |
list containing a data.frame for each group with parent 1 dosages. The data.frame contain the columns: 1) character vector with chromosomes ID; 2) Character vector with markers ID; 3) Character vector with parent ID; 4) numerical vector with dosage |
d.p2 |
list containing a data.frame for each group with parent 2 dosages. See d.p1 parameter description |
Value
list with linkage map information: doses; number snps by group; cM per snp; map size; number of linkage groups
Haldane map function. From MAPpoly
Description
Haldane map function. From MAPpoly
Usage
mf_h(d)
Arguments
d |
vector containing recombination fraction values |
Value
vector with genetic distances estimated with Haldane function
Chi-square test. Function from MAPpoly.
Description
Chi-square test. Function from MAPpoly.
Usage
mrk_chisq_test(x, ploidy)
Arguments
x |
data.frame containing dosage information |
ploidy |
integer defining the specie ploidy |
Value
vector with p-values for each marker
Only the plot part of plot_profile function
Description
Only the plot part of plot_profile function
Usage
only_plot_profile(pl.in)
Arguments
pl.in |
output object from |
Value
ggplot graphic with QTL significance profile
Linkage phase format conversion: list to matrix. Function from MAPpoly.
Description
This function converts linkage phase configurations from list to matrix form
Usage
ph_list_to_matrix(L, ploidy)
Arguments
L |
a list of configuration phases |
ploidy |
ploidy level |
Value
a matrix whose columns represent homologous chromosomes and the rows represent markers
Linkage phase format conversion: matrix to list. Function from MAPpoly.
Description
This function converts linkage phase configurations from matrix form to list
Usage
ph_matrix_to_list(M)
Arguments
M |
matrix whose columns represent homologous chromosomes and the rows represent markers |
Value
a list of linkage phase configurations
Plots mappoly.homoprob from MAPpoly
Description
Plots mappoly.homoprob from MAPpoly
Usage
## S3 method for class 'mappoly.homoprob'
plot(x, stack = FALSE, lg = NULL, ind = NULL, verbose = TRUE, ...)
Arguments
x |
an object of class |
stack |
logical. If |
lg |
indicates which linkage group should be plotted. If |
ind |
indicates which individuals should be plotted. It can be the
position of the individuals in the dataset or it's name.
If |
verbose |
if |
... |
unused arguments |
Scatter plot relating linkage map and genomic positions
Description
Scatter plot relating linkage map and genomic positions
Usage
plot_cm_mb(viewmap, group, range.min, range.max)
Arguments
viewmap |
object of class |
group |
selected group ID |
range.min |
minimum value of the selected position range |
range.max |
maximum value of the selected position range |
Plot effects data
Description
Plot effects data
Usage
plot_effects(
data_effects.obj,
software,
design = c("bar", "circle", "digenic")
)
Arguments
data_effects.obj |
output of function |
software |
character defining which software was used for QTL analysis. Currently support for: QTLpoly, diaQTL and polyqtlR. |
design |
character defining the graphic design. Options: 'bar' - barplot of the effects; 'circle' - circular plot of the effects (useful to compare effects of different traits); 'digenic' - heatmap plotting sum of additive effects (bottom diagonal) and digenic effects (top diagonal) when present |
Plot a genetic map - Adapted from MAPpoly
Description
This function plots a genetic linkage map(s)
Usage
plot_map_list(viewmap, horiz = TRUE, col = "ggstyle", title = "Linkage group")
Arguments
viewmap |
object of class |
horiz |
logical. If FALSE, the maps are plotted vertically with the first map to the left. If TRUE (default), the maps are plotted horizontally with the first at the bottom |
col |
a vector of colors for the bars or bar components (default = 'lightgrey')
|
title |
a title (string) for the maps (default = 'Linkage group') |
Value
A data.frame
object containing the name of the markers and their genetic position
Author(s)
Marcelo Mollinari, mmollin@ncsu.edu
Cristiane Taniguti, chtaniguti@tamu.edu
References
Mollinari, M., and Garcia, A. A. F. (2019) Linkage analysis and haplotype phasing in experimental autopolyploid populations with high ploidy level using hidden Markov models, _G3: Genes, Genomes, Genetics_. doi: 10.1534/g3.119.400378
Plot a single linkage group with no phase - from MAPpoly
Description
Plot a single linkage group with no phase - from MAPpoly
Usage
plot_one_map(x, i = 0, horiz = FALSE, col = "lightgray")
Arguments
x |
vector of genetic distances |
i |
margins size |
horiz |
logical TRUE/FALSE. If TRUE the map is plotted horizontally. |
col |
color pallete to be used |
Logarithm of P-value (LOP) profile plots. Modified version of QTLpoly function.
Description
Plots profiled logarithm of score-based P-values (LOP) from individual or combined traits.
Usage
plot_profile(
profile,
qtl_info,
selected_mks,
pheno.col = NULL,
lgs.id = NULL,
by_range = TRUE,
range.min = NULL,
range.max = NULL,
plot = TRUE,
software = NULL
)
Arguments
profile |
data.frame with: pheno - phenotype ID; LOP - significance value for the QTL. It can be LOP, LOD or DIC depending of the software used |
qtl_info |
data.frame with: LG - linkage group ID; Pos - position in linkage map (cM); Pheno - phenotype ID; Pos_lower - lower position of confidence interval; Pos_upper - upper position of the confidence interval; Pval - QTL p-value; h2 - herdability |
selected_mks |
data.frame with: LG - linkage group ID; mk - marker ID; pos - position in linkage map (cM) |
pheno.col |
integer identifying phenotype |
lgs.id |
integer identifying linkage group |
by_range |
logical TRUE/FALSE. If TRUE range.min and range.max will set a colored window in the plot and the other positions will be gray. If FALSE, range.min and range.max is ignored |
range.min |
position in centimorgan defining the start of the colored window |
range.max |
position in centimorgan defining the end of the colored window |
plot |
logical TRUE/FALSE. If FALSE the function return a data.frame with information for |
software |
character defining which software was used for QTL analysis. Currently support for: QTLpoly, diaQTL and polyqtlR. |
Value
ggplot graphic (if plot == TRUE) or data.frame (if plot == FALSE) with information from QTL significance profile
Converts list of mappoly.map object into viewmap object
Description
Converts list of mappoly.map object into viewmap object
Usage
prepare_MAPpoly(mappoly_list)
Arguments
mappoly_list |
list with objects of class |
Value
object of class viewmap
Converts QTLpoly outputs to viewqtl object
Description
Converts QTLpoly outputs to viewqtl object
Usage
prepare_QTLpoly(data, remim.mod, est.effects, fitted.mod)
Arguments
data |
object of class "qtlpoly.data" |
remim.mod |
object of class "qtlpoly.model" "qtlpoly.remim". |
est.effects |
object of class "qtlpoly.effects" |
fitted.mod |
object of class "qtlpoly.fitted" |
Value
object of class viewqtl
Author(s)
Cristiane Taniguti, chtaniguti@tamu.edu
Converts diaQTL output to viewqtl object
Description
Converts diaQTL output to viewqtl object
Usage
prepare_diaQTL(scan1_list, scan1_summaries_list, fitQTL_list, BayesCI_list)
Arguments
scan1_list |
list with results from diaQTL |
scan1_summaries_list |
list with results from diaQTL |
fitQTL_list |
list with results from diaQTL |
BayesCI_list |
list with results from diaQTL |
Value
object of class viewqtl
Upload example files
Description
Upload example files
Usage
prepare_examples(example)
Arguments
example |
character indicating the example dataset selected |
Value
object of class viewpoly
Upload hidecan example files
Description
Upload hidecan example files
Usage
prepare_hidecan_examples(example)
Arguments
example |
character indicating the example dataset selected |
Value
object of class viewpoly
prepare maps for plot - from MAPpoly
Description
prepare maps for plot - from MAPpoly
Usage
prepare_map(input.map, config = "best")
Arguments
input.map |
object of class |
config |
choose between 'best', 'all' or provide vector with defined configuration. 'best' provide just the best estimated configuration. 'all' provides all possibles. |
Value
list containing phase and dosage information
Converts map information in custom format files to viewmap object
Description
Converts map information in custom format files to viewmap object
Usage
prepare_map_custom_files(dosages, phases, genetic_map, mks_pos = NULL)
Arguments
dosages |
TSV or TSV.GZ file with both parents dosage information. It should contain four columns: 1) character vector with chromosomes ID; 2) Character vector with markers ID; 3) Character vector with parent ID; 4) numerical vector with dosage. |
phases |
TSV or TSV.GZ file with phases information. It should contain: 1) Character vector with chromosome ID; 2) Character vector with marker ID; 3 to (ploidy number)*2 columns with each parents haplotypes. |
genetic_map |
TSV or TSV.GZ file with the genetic map information |
mks_pos |
TSV or TSV.GZ file with table with three columns: 1) marker ID; 2) genome position; 3) chromosome |
Value
object of class viewmap
Converts polymapR ouputs to viewmap object
Description
Converts polymapR ouputs to viewmap object
Usage
prepare_polymapR(polymapR.dataset, polymapR.map, input.type, ploidy)
Arguments
polymapR.dataset |
a |
polymapR.map |
output map sequence from polymapR |
input.type |
indicates whether the input is discrete ("disc") or probabilistic ("prob") |
ploidy |
ploidy level |
Value
object of class viewmap
Converts polyqtlR outputs to viewqtl object
Description
Converts polyqtlR outputs to viewqtl object
Usage
prepare_polyqtlR(polyqtlR_QTLscan_list, polyqtlR_qtl_info, polyqtlR_effects)
Arguments
polyqtlR_QTLscan_list |
list containing results from polyqtlR |
polyqtlR_qtl_info |
data.frame containing the QTL information:LG - group ID; Pos - QTL position (cM); pheno - phenotype ID; Pos_lower - lower position of confidence interval; Pos_upper - upper position of the confidence interval; thresh - LOD threshold applied |
polyqtlR_effects |
data.frame with results from |
Value
object of class viewqtl
Converts QTL information in custom files to viewqtl object
Description
Converts QTL information in custom files to viewqtl object
Usage
prepare_qtl_custom_files(
selected_mks,
qtl_info,
blups,
beta.hat,
profile,
effects,
probs
)
Arguments
selected_mks |
data.frame with: LG - linkage group ID; mk - marker ID; pos - position in linkage map (cM) |
qtl_info |
data.frame with: LG - linkage group ID; Pos - position in linkage map (cM); Pheno - phenotype ID; Pos_lower - lower position of confidence interval; Pos_upper - upper position of the confidence interval; Pval - QTL p-value; h2 - herdability |
blups |
data.frame with: haplo - haplotype ID; pheno - phenotype ID; qtl - QTL ID; u.hat - QTL estimated BLUPs |
beta.hat |
data.frame with: pheno - phenotype ID; beta.hat - estimated beta |
profile |
data.frame with: pheno - phenotype ID; LOP - significance value for the QTL, in this case LOP (can be LOD or DIC depending of the software used) |
effects |
data.frame with: pheno - phenotype ID; qtl.id - QTL ID; haplo - haplotype ID; effect - haplotype effect value |
probs |
data.frame with first column (named 'ind') as individuals ID and next columns named with markers ID and containing the genotype probability at each marker |
Value
object of class viewqtl
Check hidecan inputs
Description
Check hidecan inputs
Usage
read_input_hidecan(input_list, func)
Arguments
input_list |
shiny input result containing file path |
func |
hidecan read input function |
Run the Shiny Application
Description
Run the Shiny Application
Usage
run_app(
onStart = NULL,
options = list(),
enableBookmarking = NULL,
uiPattern = "/",
...
)
Arguments
onStart |
A function that will be called before the app is actually run.
This is only needed for |
options |
Named options that should be passed to the |
enableBookmarking |
Can be one of |
uiPattern |
A regular expression that will be applied to each |
... |
arguments to pass to golem_opts. See '?golem::get_golem_options' for more details. |
Polysomic segregation frequency - Function from MAPpoly
Description
Computes the polysomic segregation frequency given a ploidy level and the dosage of the locus in both parents. It does not consider double reduction.
Usage
segreg_poly(ploidy, d.p1, d.p2)
Arguments
ploidy |
the ploidy level |
d.p1 |
the dosage in parent P |
d.p2 |
the dosage in parent Q |
Value
a vector containing the expected segregation frequency for all possible genotypic classes.
Author(s)
Marcelo Mollinari, mmollin@ncsu.edu
References
Mollinari, M., and Garcia, A. A. F. (2019) Linkage analysis and haplotype phasing in experimental autopolyploid populations with high ploidy level using hidden Markov models, _G3: Genes, Genomes, Genetics_. doi: 10.1534/g3.119.400378
Serang O, Mollinari M, Garcia AAF (2012) Efficient Exact Maximum a Posteriori Computation for Bayesian SNP Genotyping in Polyploids. _PLoS ONE_ 7(2): e30906.
Plot selected haplotypes
Description
Plot selected haplotypes
Usage
select_haplo(
input.haplo,
probs,
selected_mks,
effects.data,
exclude.haplo = NULL
)
Arguments
input.haplo |
character vector with selected haplotypes. It contains the information: "Trait:<trait ID>_LG:<linkage group ID_Pos:<QTL position>" |
probs |
data.frame with first column (named 'ind') as individuals ID and next columns named with markers ID and containing the genotype probability at each marker |
selected_mks |
data.frame with: LG - linkage group ID; mk - marker ID; pos - position in linkage map (cM) |
effects.data |
output object from |
exclude.haplo |
character vector with haplotypes to be excluded. It contains the information: "Trait:<trait ID>_LG:<linkage group ID_Pos:<QTL position>" |
Value
ggplot graphic
Summary maps - adapted from MAPpoly
Description
This function generates a brief summary table
Usage
summary_maps(viewmap, software = NULL)
Arguments
viewmap |
a list of objects of class |
software |
character defined from each software it comes from |
Value
a data frame containing a brief summary of all maps
Author(s)
Gabriel Gesteira, gabrielgesteira@usp.br
Cristiane Taniguti, chtaniguti@tamu.edu