Package: amplican 1.29.0

Eivind Valen

amplican: Automated analysis of CRISPR experiments

`amplican` performs alignment of the amplicon reads, normalizes gathered data, calculates multiple statistics (e.g. cut rates, frameshifts) and presents results in form of aggregated reports. Data and statistics can be broken down by experiments, barcodes, user defined groups, guides and amplicons allowing for quick identification of potential problems.

Authors:Kornel Labun [aut], Eivind Valen [cph, cre]

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amplican.pdf |amplican.html
amplican/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/valenlab/amplican/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On BioConductor:amplican-1.29.0(bioc 3.21)amplican-1.28.0(bioc 3.20)

immunooncologytechnologyalignmentqpcrcrispr

7.66 score 10 stars 41 scripts 334 downloads 51 exports 118 dependencies

Last updated 20 days agofrom:555fe1ea6b. Checks:OK: 1 WARNING: 6 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-win-x86_64WARNINGNov 02 2024
R-4.5-linux-x86_64WARNINGNov 02 2024
R-4.4-win-x86_64WARNINGNov 02 2024
R-4.4-mac-x86_64WARNINGNov 02 2024
R-4.4-mac-aarch64NOTENov 02 2024
R-4.3-win-x86_64WARNINGNov 02 2024
R-4.3-mac-x86_64WARNINGNov 02 2024
R-4.3-mac-aarch64NOTENov 02 2024

Exports:AlignmentsExperimentSetamplican_print_readsamplicanAlignamplicanConsensusamplicanFilteramplicanMapamplicanNormalizeamplicanOverlapamplicanPipelineamplicanPipelineConservativeamplicanReportamplicanSummarizeassignedCountbarcodeDatabarcodeData<-cigarsToEventscomb_alongexperimentDataexperimentData<-extractEventsfindEOPfindLQRfindPDfwdReadsfwdReads<-fwdReadsTypefwdReadsType<-getEventsis_hdr_strictlookupAlignmentmetaplot_deletionsmetaplot_insertionsmetaplot_mismatchespairToEventsplot_cutsplot_deletionsplot_heightplot_heterogeneityplot_insertionsplot_mismatchesplot_variantsreadCountsreadCounts<-rveReadsrveReads<-rveReadsTyperveReadsType<-unassignedCountunassignedDataunassignedData<-writeAlignments

Dependencies:abindaskpassbase64encBHBiobaseBiocGenericsBiocParallelBiostringsbitopsbslibcachemcliclustercodetoolscolorspacecpp11crayoncrosstalkcurldata.tableDelayedArraydeldirdigestdplyrDTevaluateextrafontextrafontdbfansifarverfastmapfontawesomeformatRfsfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicRangesggplot2ggthemesgluegridExtragtablehighrhtmltoolshtmlwidgetshttpuvhttrhwriterinterpIRangesisobandjpegjquerylibjsonliteknitrlabelinglambda.rlaterlatticelatticeExtralazyevallifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplyrpngpromisespurrrpwalignR6rappdirsRColorBrewerRcppRcppEigenRhtslibrlangrmarkdownRsamtoolsRttf2pt1S4ArraysS4VectorssassscalesShortReadsnowSparseArraystringistringrSummarizedExperimentsystibbletidyselecttinytexUCSC.utilsutf8vctrsviridisLitewafflewithrxfunXVectoryamlzlibbioc

ampliCan FAQ

Rendered fromamplicanFAQ.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2023-05-02
Started: 2018-09-14

ampliCan Overview

Rendered fromamplicanOverview.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2024-04-24
Started: 2016-08-23

Report breakdown by amplicon sequence

Rendered fromexample_amplicon_report.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2023-05-02
Started: 2017-06-02

Report breakdown by barcode

Rendered fromexample_barcode_report.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2023-05-02
Started: 2017-06-02

Report breakdown by group

Rendered fromexample_group_report.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2023-07-30
Started: 2017-06-02

Report breakdown by guideRNA

Rendered fromexample_guide_report.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2023-07-30
Started: 2017-06-02

Report breakdown by ID

Rendered fromexample_id_report.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2023-05-02
Started: 2017-06-02

Summary Read Report

Rendered fromexample_index.Rmdusingknitr::rmarkdownon Nov 02 2024.

Last update: 2023-05-02
Started: 2017-04-20

Readme and manuals

Help Manual

Help pageTopics
Automated analysis of CRISPR experiments.amplican-package amplican
Pretty print forward and reverse reads aligned to each other.amplican_print_reads
Align reads to amplicons.amplicanAlign
Extract consensus out of forward and reverse events.amplicanConsensus
Filter Events Overlapping Primers, PRIMER DIMERS and Low Alignment Score Events.amplicanFilter
Map events to their respective relative coordinates specified with UPPER case.amplicanMap
Remove events that can be found in Controls.amplicanNormalize
Check which events overlap expected cut sites.amplicanOverlap
Wraps main package functionality into one function.amplicanPipeline
Wraps main package functionality into one function.amplicanPipelineConservative
Prepare reports as .Rmd files.amplicanReport
Summarize how many reads have frameshift and how many reads have deletions.amplicanSummarize
Transform extended CIGAR strings into GRanges.cigarsToEvents
Generate all combinations along string exchanging m characters at a time with dictionary letters.comb_along
Find Events Overlapping Primers.findEOP
Find Off-targets and Fragmented alignments from reads.findLQR
Find PRIMER DIMER reads.findPD
Create quadratic or cubic bezier curves [copied from ggforce]geom_bezier stat_bezier
Transform aligned strings into GRanges representation of events.getEvents
Figure out which reads conform to the HDR using the donor.is_hdr_strict
MetaPlots deletions using ggplot2.metaplot_deletions
MetaPlots insertions using ggplot2.metaplot_insertions
MetaPlots mismatches using ggplot2.metaplot_mismatches
Read "pair" format of EMBOSS needle into GRanges as events.pairToEvents
Plots cuts using ggplot2.plot_cuts
Plots deletions using ggplot2.plot_deletions
Get figure height in inches for number of elements on y axis.plot_height
Plots heterogeneity of the reads using ggplot2.plot_heterogeneity
Plots insertions using ggplot2.plot_insertions
Plots mismatches using ggplot2.plot_mismatches
Plots most frequent variants using ggplot2.plot_variants