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immunomind/immunarch: 0.6.5: Basic single-cell support

Authors: Vadim Nazarov; immunarch.bot; Eugene Rumynskiy;

immunomind/immunarch: 0.6.5: Basic single-cell support

Abstract

fix(vignette): fix incorrect CRAN links in the Introduction vignette refactor(data): make the data smaller in order to follow the CRAN guidelines refactor(web): fix paths to the moved Basic Analysis vignette refactor(vignette): remove the Basic Analysis vignette from the CRAN pacakge refactor(vignette): add the tracking visualisation to the single-cell vignette fix(vignette): remove https because it fails on CRAN checks feat(upkeep): update README & NAMESPACE to reflect the single-cell support and also shorten the documentation for readability fix(io): fix imports fix(single-cell): fix the missing barcode column feat(data): add the "scdata" dataset with paired chain data and barcodes docs(io): update docs for repLoad / repSave to reflect single-cell support docs(single-cell): add docs for select_barcodes feat(vignette): finish the single-cell vignette feat(vignette): add a draft for the single-cell vignette refactor(upkeep): add "single-cell" and "data" commit scopes feat(io): add a paired chain parsing support for 10X feat(data): add new test files for single-cell docs(single-cell): add docs for single-cell functions docs(upkeep): update the docs for bulk data feat(upkeep): add the single-cell example data feat(web): add the single-cell vignette feat(single-cell): add a support for filtering and selecting clonotypes by barcodes and the Seurat::Idents() output refactor(io): remove raw_contig and raw_clonotype columns from 10X data to reduce the memory print feat(upkeep): add a new environment for additional immunarch columns fix(io): update the repLoad docs feat(io): add the ".coding" argument to filter out non-coding sequences (ON by default) chore(vignette): add badges for the optimisation of looking for downloads statistics chore(tools): move filter_barcodes() to singlecell.R and rename it to select_barcodes() chore(db): rename search.R with annotation.R chore(pub-rep): rename shared.R to public.R chore(tools): rename processing.R to sampling.R chore(data): move the description of "immdata" to data_docs.R chore(tools): move data filtering & manipulation functions to the preprocessing.R file refactor(io) / refactor(vignette): focus on the automatic detection of file formats refactor(upkeep): change authors to contributors feat(io): add "report" and "vdjca" files to the ignore list refactor(io): put a warning when .format is provided, and update repLoad documentation skip this comment in NEWS: add IO_REFACTOR label to where I experimented with data.table-based input reading. Initial benchmarks shows x2 acceleration in data loading speed fix(vis): fix a bug #65 in plotting repClonality with .col="nt" (PR #66 from Rushil) refactor(upkeep): add pull requests names to the contribution guide fix(vis): fix a bug in clonality visualisations #65 (PR #66) refactor(upkeep): update the contribution guide refactor(vignette): remove treemap and replace gridExtra with patchwork refactor(vis): remove treemap and replace gridExtra with patchwork fix(vignette): replace "develop" with "dev" refactor(tools): add_class() now adds the class to the beginning of the class attributes in order to comply with the R class system feat(vignette): cosmetic changes to the README feat(upkeep): add the pkgdown folder to the ignore feat(upkeep): remove "Home" and "News", add a link to the covid-19 repo feat(vignette): make the README more succinct, add a quick start section and the visitors badge refactor(upkeep): minor changes in text feat(upkeep): add the tag for the website refactor(io): refactor warning messages to make them more correct & add "na.rm = TRUE" to eliminates NAs when computing new Proportion columns

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visibility
download
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
15
Top 10%
Average
Top 10%
159
3
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