Package: hlaR 1.0.0

Joan Zhang

hlaR: Tools for HLA Data

A streamlined tool for eplet analysis of donor and recipient HLA (human leukocyte antigen) mismatch. Messy, low-resolution HLA typing data is cleaned, and imputed to high-resolution using the NMDP (National Marrow Donor Program) haplotype reference database <https://haplostats.org/haplostats>. High resolution data is analyzed for overall or single antigen eplet mismatch using a reference table (currently supporting 'HLAMatchMaker' <http://www.epitopes.net> versions 2 and 3). Data can enter or exit the workflow at different points depending on the user's aims and initial data quality.

Authors:Joan Zhang [aut, cre], Aileen Johnson [aut], Christian P Larsen [cph, aut]

hlaR_1.0.0.tar.gz
hlaR_1.0.0.zip(r-4.7-any)hlaR_1.0.0.zip(r-4.6-any)hlaR_1.0.0.zip(r-4.5-any)
hlaR_1.0.0.tgz(r-4.6-any)hlaR_1.0.0.tgz(r-4.5-any)
hlaR_1.0.0.tar.gz(r-4.7-any)hlaR_1.0.0.tar.gz(r-4.6-any)
hlaR_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
hlaR/json (API)

# Install 'hlaR' in R:
install.packages('hlaR', repos = c('https://larsenlab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/larsenlab/hlar/issues

On CRAN:

Conda:

5.30 score 9 stars 11 scripts 274 downloads 8 exports 147 dependencies

Last updated from:a7fec958e0. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK217
source / vignettesOK289
linux-releaseOK198
macos-releaseOK190
macos-oldrelOK219
windows-develOK96
windows-releaseOK109
windows-oldrelOK106
wasm-releaseOK207

Exports:CalAlleleMismFreqCalAlleleTopNCalEpletMHCICalEpletMHCIICleanAlleleCountAlleleMismEvalAlleleMismImputeHaplo

Dependencies:askpassbackportsbase64encbitbit64blobbrewbriobroombslibcachemcallrcellrangerclicliprcommonmarkconflictedcpp11crayoncredentialscurldata.tableDBIdbplyrdescdevtoolsdiffobjdigestdownlitdplyrdtplyrellipsisevaluatefansifarverfastmapfontawesomeforcatsfsgarglegenericsgertggplot2gitcredsgluegoogledrivegooglesheets4gtablehavenhighrhmshtmltoolshtmlwidgetshttpuvhttrhttr2idsiniisobandjanitorjquerylibjsonliteknitrlabelinglaterlifecyclelubridatemagrittrmemoisemimeminiUImodelropensslotelpakpillarpkgbuildpkgconfigpkgdownpkgloadplyrpraiseprettyunitsprocessxprofvisprogresspromisespspurrrR6raggrappdirsrcmdcheckRColorBrewerRcpprdtoolsreadrreadxlrematchrematch2reprexreshape2rlangrmarkdownroxygen2rprojrootrstudioapirversionsrvestS7sassscalesschoolmathselectrsessioninfoshinysnakecasesourcetoolsstringistringrsyssystemfontstestthattextshapingtibbletidyrtidyselecttidyversetimechangetinytextzdburlcheckerusethisutf8uuidvctrsviridisLitevroomwaldowhiskerwithrxfunxml2xopenxtableyamlzip

Eplet Mismatch
Aims | Overview | Use Cases: | Example: Investigate the Importance of Eplet Mismatch in Retrospective Transplant Cohort | Step 1: Import recipient and donor typing data. We have an example cohort that can be loaded into the environment with the following code. This is A cohort of 14 recipients with donor and recipient high resolution HLA typing data for HLA Class I (A, B, C) and HLA Class II (DRB1, DRB3/4/5, and DQb and DQb). | Step 2: Calculate MHCI mismatch, pull information from result using single and overall outputs. | Example 1 - MHC-I | Step 3: Calculate MHCII mismatch and DRDQ risk score, pull information from result using single and overall outputs. | Step 4: Use visuals to examine the data. | Sources | MatchMaker Logic:
Rendered fromeplet-mm.Rmdusingknitr::rmarkdown

Last update: 2022-10-26
Started: 2020-10-27

Imputation
Vignette Aims | Load Test Data Set | Generate List of Possible Haplotypes and Sort Most likely Pairs | Impute high-resolution data | Notes:
Rendered fromallele-haplotype.Rmdusingknitr::rmarkdown

Last update: 2021-10-14
Started: 2021-01-14