Introduction | Dataset example and description | Folder organization | Extra information | Installation instructions | Load required packages | Checking flow cytometry data | Example 1 | Example 2 | Example 3 | Example 4 | Sanger sequence dataset | Processing a single B cell receptor sanger sequence | Processing a group of B cell receptors sanger sequences | Joining flow cytometry and sanger sequencing datasets | IgBlast analysis for sequencing results
Package: scifer 1.15.1
Rodrigo Arcoverde Cerveira
scifer: Scifer: Single-Cell Immunoglobulin Filtering of Sanger Sequences
Have you ever index sorted cells in a 96 or 384-well plate and then sequenced using Sanger sequencing? If so, you probably had some struggles to either check the electropherogram of each cell sequenced manually, or when you tried to identify which cell was sorted where after sequencing the plate. Scifer was developed to solve this issue by performing basic quality control of Sanger sequences and merging flow cytometry data from probed single-cell sorted B cells with sequencing data. scifer can export summary tables, 'fasta' files, electropherograms for visual inspection, and generate reports.
Authors:
scifer_1.15.1.tar.gz
scifer_1.15.1.zip(r-4.7)scifer_1.15.1.zip(r-4.6)scifer_1.15.1.zip(r-4.5)
scifer_1.15.1.tgz(r-4.6-any)scifer_1.15.1.tgz(r-4.5-any)
scifer_1.15.1.tar.gz(r-4.7-any)scifer_1.15.1.tar.gz(r-4.6-any)
scifer_1.15.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
scifer/json (API)
| # Install 'scifer' in R: |
| install.packages('scifer', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rodrigarc/scifer/issues
On BioConductor:scifer-1.15.1(bioc 3.24)scifer-1.14.0(bioc 3.23)
preprocessingqualitycontrolsangerseqsequencingsoftwareflowcytometrysinglecell
Last updated from:0f46ed0586. Checks:1 WARNING, 7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 215 | ||
| linux-devel-x86_64 | NOTE | 592 | ||
| source / vignettes | OK | 371 | ||
| linux-release-x86_64 | NOTE | 524 | ||
| macos-release-arm64 | NOTE | 294 | ||
| macos-oldrel-arm64 | NOTE | 220 | ||
| windows-devel | NOTE | 449 | ||
| windows-release | NOTE | 445 | ||
| windows-oldrel | NOTE | 415 | ||
| wasm-release | OK | 187 |
Exports:df_to_fastafcs_plotfcs_processingigblastquality_reportsummarise_abi_filesummarise_quality
Dependencies:base64encbasiliskbasilisk.utilsBHBiobaseBiocGenericsbiocmakeBiostringsbslibcachemclicommonmarkcpp11crayoncytolibdata.tableDBIDECIPHERdigestdir.expirydplyrevaluatefarverfastmapfilelockflowCorefontawesomefsgenericsggplot2gluegridExtragtableherehighrhtmltoolshttpuvIRangesisobandjquerylibjsonlitekableExtraknitrlabelinglaterlatticelifecyclemagrittrMatrixmatrixStatsmemoisemimeotelpillarpkgconfigplyrpngpromisespwalignR6rappdirsRColorBrewerRcppRcppTOMLreticulateRhdf5librlangrmarkdownrprojrootRProtoBufLibrstudioapiS4VectorsS7sangerseqRsassscalesSeqinfoshinysourcetoolsstringistringrsvglitesystemfontstextshapingtibbletidyselecttinytexutf8vctrsviridisLitewithrxfunxml2xtableXVectoryaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Fasta file creation from dataframe columns and/or vectors. | df_to_fasta |
| Plot flow data from index sorted cells | fcs_plot |
| Extract index sorting from flow cytometry data | fcs_processing |
| Run IgBLAST python wrapper | igblast |
| Generate general and individualized reports | quality_report |
| Scifer: Single-Cell Immunoglobulin Filtering of Sanger Sequences | scifer-package scifer |
| Check for secondary peaks in a sangerseq object | secondary_peaks |
| Create a summary of a single ABI sequencing file | summarise_abi_file |
| Summary table of quality measurements from Sanger sequencing | summarise_quality |
