Package: preseqR 4.0.0
Chao Deng
preseqR: Predicting Species Accumulation Curves
Originally as an R version of Preseq <doi:10.1038/nmeth.2375>, the package has extended its functionality to predict the r-species accumulation curve (r-SAC), which is the number of species represented at least r times as a function of the sampling effort. When r = 1, the curve is known as the species accumulation curve, or the library complexity curve in high-throughput genomic sequencing. The package includes both parametric and nonparametric methods, as described by Deng C, et al. (2018) <arxiv:1607.02804v3>.
Authors:
preseqR_4.0.0.tar.gz
preseqR_4.0.0.tar.gz(r-4.5-noble)preseqR_4.0.0.tar.gz(r-4.4-noble)
preseqR_4.0.0.tgz(r-4.4-emscripten)preseqR_4.0.0.tgz(r-4.3-emscripten)
preseqR.pdf |preseqR.html✨
preseqR/json (API)
| # Install 'preseqR' in R: |
| install.packages('preseqR', repos = 'https://cloud.r-project.org') |
- Dickens - Dickens' vocabulary
- FisherButterfly - Fisher's butterfly data
- SRR061157_k31 - K-mer counts of a metagenomic data
- SRR1301329_1M_base - Coverage histogram of a WES data
- SRR1301329_1M_read - Read counts of a WES data
- SRR1301329_base - Coverage histogram of a WES data
- SRR1301329_read - Read counts of a WES data
- SRR611492 - Coverage histogram of a scWGS data
- SRR611492_5M - Coverage histogram of a scWGS data
- Shakespeare - Shakespeare's word type frequencies
- Twitter - Social network
- WillButterfly - Fisher's butterfly data
Conda:r-preseqr-4.0.0(2025-03-25)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:311a1e5602. Checks:3 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 23 2025 |
| R-4.5-linux | OK | Mar 23 2025 |
| R-4.4-linux | OK | Mar 23 2025 |
Exports:bbc.rSACcs.rSACds.rSACds.rSAC.bootstrapfisher.alphafisher.rSACkmer.frac.curvekmer.frac.curve.bootstrappreseqR.interpolate.rSACpreseqR.nonreplace.samplingpreseqR.optimal.sequencingpreseqR.rSACpreseqR.rSAC.bootstrappreseqR.rSAC.sequencing.rmduppreseqR.sample.covpreseqR.sample.cov.bootstrappreseqR.simu.histpreseqR.ztnb.emztnb.rSACztp.rSAC
Dependencies:polynom
Citation
To cite preseqR in publications use:
Deng C, Daley T and Smith AD (2015). Applications of species accumulation curves in large-scale biological data analysis. Quantitative Biology, 3(3), 135-144. URL https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4885658.
Deng C, Daley T, Calabrese P, Ren J and Smith AD (2018). Estimating the number of species to attain sufficient representation in a random sample. arXiv preprint. URL https://arxiv.org/abs/1607.02804v3.
Corresponding BibTeX entries:
@Article{,
title = {Applications of species accumulation curves in large-scale
biological data analysis},
author = {Chao Deng and Timothy Daley and Andrew D. Smith},
journal = {Quantitative Biology},
year = {2015},
volume = {3},
number = {3},
pages = {135--144},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4885658},
}
@Article{,
title = {Estimating the number of species to attain sufficient
representation in a random sample},
author = {Chao Deng and Timothy Daley and Peter Calabrese and Jie
Ren and Andrew D. Smith},
journal = {arXiv},
year = {2018},
url = {https://arxiv.org/abs/1607.02804v3},
}
Readme and manuals
UPDATES TO VERSION 4.0.0
- Improve the user interface for core functions
- Add functions to optimize the depth of single-cell whole-genome sequencing experiments and whole-exome sequencing experiments
- Add functions to predict the sample coverage, which is the probability of sampling an observed species from a population
- Add functions to predict the fraction of k-mers represented at least r times in a sequencing experiment
UPDATES TO VERSION 3.1.2
- Fix a bug for removing defects
UPDATES TO VERSION 3.1.1
- Substitute embedded c++ code with R code
- Remove the dependencies on the software preseq
UPDATES TO VERSION 3.0.1
- Fix a bug in Chao's estimator
- Fix issues for a Solaris C++ compiler.
UPDATES TO VERSION 3.0.0
-
We have changed the return types of many functions in the package. These functions no longer generate estimated accumulative curves. Instead, they return function types, which are estimators for the number of species represented by at least r indivdiduals in a random sample.
-
We added several estimators for predicting the number of species represented by at least r individuals in a random sample
UPDATES TO VERSION 2.1.1
We have changed the interfaces for most of our exported functions. We add new estimators for the number of species represented by at least r individuals in a random sample.
preseqR
Code in this repository aims to expand the functionality of Preseq available in the R statistical computing enviroment. There are five ways this is supposed to work:
- The basic functionality of the preseq program, initially focusing only on library complexity, is available. These functions contain the string "rfa" as part of their names.
- The mathematical routines for doing rational function approximation via continued fractions is implemented as a wrapper for our existing functionality in C++.
- Fitting a zero-truncated negative binomial distribution to the sample is available. These functions include the string "ztnb" as part of the names.
- The simulation module is used to generate samples based on mixture of Poisson.
- Extra functions are provided to estimate the number of species represented at least r times in a random sample.
See https://cran.r-project.org/package=preseqR for details.
INSTALLATION
-
We recommand everyone to install the package preseqR from CRAN. It can be easily done by opening an R shell and typing:
>install.packages("preseqR") -
The following instructions are for installing the package from the source. Assume the source code of preseqR has been pulled from the git repo and it is under the current directory. Open an R shell and type:
>install.packages("polynom")>install.packages("preseqR", repos=NULL, type="source")Note that the package polynom is required by preseqR.