Overview | Theory | Example | Cooperative factors example | Competitive factors example | References
Package: target 1.27.0
Mahmoud Ahmed
target: Predict Combined Function of Transcription Factors
Implement the BETA algorithm for infering direct target genes from DNA-binding and perturbation expression data Wang et al. (2013) <doi:10.1038/nprot.2013.150>. Extend the algorithm to predict the combined function of two DNA-binding elements from comprable binding and expression data.
Authors:
target_1.27.0.tar.gz
target_1.27.0.zip(r-4.7)target_1.27.0.zip(r-4.6)target_1.27.0.zip(r-4.5)
target_1.27.0.tgz(r-4.6-any)target_1.27.0.tgz(r-4.5-any)
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target_1.27.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
target/json (API)
| # Install 'target' in R: |
| install.packages('target', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mahshaaban/target/issues
Datasets:
- real_peaks - AR peaks in LNCaP cell line
- real_transcripts - Differential expression of DHT treated LNCaP cell line
- sim_peaks - Simulated peaks
- sim_transcripts - Simulated transcripts The transcripts chromosome 1 of the mm10 mouse genome with randomly singed statistics assigned to each.
On BioConductor:target-1.27.0(bioc 3.24)target-1.26.0(bioc 3.23)
softwarestatisticalmethodtranscriptionalgorithmchip-seqdna-bindinggene-regulationtranscription-factors
Last updated from:c38bdfe0e2. Checks:1 NOTE, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | NOTE | 160 | ||
| linux-devel-x86_64 | OK | 245 | ||
| source / vignettes | OK | 219 | ||
| linux-release-x86_64 | OK | 356 | ||
| macos-release-arm64 | OK | 126 | ||
| macos-oldrel-arm64 | OK | 104 | ||
| windows-devel | OK | 156 | ||
| windows-release | OK | 118 | ||
| windows-oldrel | OK | 117 | ||
| wasm-release | OK | 114 |
Exports:associated_peaksdirect_targetsfind_distancemerge_rangesplot_predictionsrank_productscore_peaksscore_regionstarget_apptest_predictions
Dependencies:base64encBiocGenericsbslibcachemclicommonmarkdigestfastmapfontawesomefsgenericsGenomicRangesgluehtmltoolshttpuvIRangesjquerylibjsonlitelaterlifecyclemagrittrmatrixStatsmemoisemimeotelpromisesR6rappdirsRcpprlangS4VectorssassSeqinfoshinysourcetoolswithrxtable
Using target to predict combined binding
Last update: 2019-09-26
Started: 2019-08-28
Using the target package
Overview | The theory | Python implementation | R implementation | Example | Advantages of the R implementation | References
Last update: 2019-08-28
Started: 2019-08-28
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Predict associated peaks | associated_peaks |
| Predict direct targets | direct_targets |
| Find the distance between peaks and regions | find_distance |
| Merge peaks and regions GRanges | merge_ranges |
| Plot the ECDF of ranks by groups | plot_predictions |
| Calculate the regions rank products | rank_product |
| AR peaks in LNCaP cell line | real_peaks |
| Differential expression of DHT treated LNCaP cell line | real_transcripts |
| Calculate peak scores | score_peaks |
| Calculate region scores | score_regions |
| Simulated peaks | sim_peaks |
| Simulated transcripts The transcripts chromosome 1 of the mm10 mouse genome with randomly singed statistics assigned to each. | sim_transcripts |
| 'target': Predict Combined Function of Transcription Factors. | target-package target |
| Run the shiny App | target_app |
| Test the ECDF ranks of groups are from same distribution | test_predictions |
