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## `cogent3`
`cogent3` is a mature python library for analysis of genomic sequence data. We endeavour to provide a first-class experience within Jupyter notebooks, but the algorithms also support parallel execution on compute systems with 1000's of processors.
## Who is it for?
### Anyone who wants to analyse sequence divergence using robust statistical models
`cogent3` is unique in providing numerous [non-stationary Markov models](http://www.ncbi.nlm.nih.gov/pubmed/25503772) for modelling sequence evolution, [including codon models](https://www.ncbi.nlm.nih.gov/pubmed/28175284). `cogent3` also includes an extensive collection of time-reversible models (again including [novel codon models](https://www.ncbi.nlm.nih.gov/pubmed/19815689)). We have done more than just invent these new methods, we have [established the most robust algorithms](https://www.ncbi.nlm.nih.gov/pubmed/19099591) for their implementation and their [suitability for real data](https://www.ncbi.nlm.nih.gov/pubmed/23935949). Additionally, there are novel signal processing methods focussed on statistical estimation of [integer period signals](https://www.ncbi.nlm.nih.gov/pubmed/21527008).
![nstat](https://cogent3.org/_static/gif/demo-fit-ns.gif)
### Anyone who wants to undertake exploratory genomic data analysis
Beyond our novel methods, `cogent3` provides an extensive suite of capabilities for manipulating and analysing sequence data. You can manipulate sequences by their annotations, e.g.
![annot](https://cogent3.org/_static/gif/demo-annotate.gif)
Plus, you can read standard tabular and biological data formats, perform multiple sequence alignment using any `cogent3` substitution models, phylogenetic reconstruction and tree manipulation, manipulation of tabular data, visualisation of phylogenies and much more.
### Anyone looking for a functional programming style approach to genomic data analysis
Our `cogent3.app` module provides a very different approach to using the library capabilities. Notably, a functional programming style interface lowers the barrier to entry for using `cogent3`'s advanced capabilities. It also supports building pipelines suitable for large-scale analysis. Individuals comfortable with R should find this interface pretty easy to use.
## Installation?
```bash
$ pip install cogent3
```
### Install `extra` -- adds visualisation support
The `extra` group includes python libraries required for visualisation, i.e. [plotly](https://pypi.org/project/plotly/), [kaleido](https://pypi.org/project/kaleido/), [psutil](https://pypi.org/project/psutil/) and [pandas](https://pypi.org/project/pandas/).
```bash
$ pip install "cogent3[extra]"
```
### Install `dev` -- adds `cogent3` development related libraries
The `dev` group includes python libraries required for development of `cogent3`.
```bash
$ pip install "cogent3[dev]"
```
### Install the development version
```bash
$ pip install git+https://github.com/cogent3/cogent3.git@develop#egg=cogent3
```
## Project Information
`cogent3` is released under the BSD-3 license, documentation is at [cogent3.org](https://cogent3.org), while [`cogent3` code is on GitHub](https://github.com/cogent3/cogent3). If you would like to contribute (and we hope you do!), we have created a companion [`c3dev` GitHub](https://github.com/cogent3/c3dev) repo which provides details on how to contribute and some useful tools for doing so.
## Project History
`cogent3` is a descendant of [PyCogent](https://github.com/pycogent/pycogent.github.com). While there is much in common with PyCogent, the amount of change has been substantial, motivating the name change to `cogent3`. This name has been chosen because `cogent` was always the import name (dating back to [PyEvolve in 2004](https://www.ncbi.nlm.nih.gov/pubmed/14706121)) and it's Python 3 only.
Given this history, we are grateful to the multitude of individuals who have made contributions over the years. These individuals are explicitly acknowledged in all the files they contributed to and were co-authors on the original [PyEvolve](https://www.ncbi.nlm.nih.gov/pubmed/14706121) and [PyCogent](https://www.ncbi.nlm.nih.gov/pubmed/17708774) publications.
Compared to PyCogent version 1.9, there has been a massive amount of changes. These include integration of many of the new developments on algorithms and modelling published by the [Huttley lab](https://biology.anu.edu.au/research/groups/huttley-group-bioinformatics-molecular-evolution-genomes) over the last decade. We have also modernised our dependencies. For example, we now use `plotly` for visualisation, `tqdm` for progress bar display, `concurrent.futures` and `mpi4py.futures` for parallel process execution, `tox` and `pytest` for unit testing.
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cogent3:比较基因组学工具包3
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cogent3 cogent3是用于分析基因组序列数据的成熟python库。 我们努力在Jupyter笔记本电脑中提供一流的体验,但是这些算法还支持在具有1000个处理器的计算系统上并行执行。 是给谁用的? 任何想要使用健壮的统计模型分析序列差异的人 cogent3的独特之处在于,它提供了许多用于建模序列进化的,。 cogent3还包括大量时间可逆模型(再次包括)。 我们不仅发明了这些新方法,还为它们的实现及其的。 另外,存在着重于统计估计的新颖的信号处理方法。 任何想要进行探索性基因组数据分析的人 除了我们新颖的方法外, cogent3还提供了一套广泛的功能来处理和分析序列数据。 您可以通过它们的注释来操纵序列,例如 此外,您可以阅读标准的表格和生物学数据格式,使用任何cogent3替换模型执行多序列比对,系统发育重建和树操作,表格数据操作,系统发育可视化等等。 任何寻求功能编程风
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cogent3:比较基因组学工具包3 (501个子文件)
formattest.aln 5KB
formattest.fasta.bz2 790B
ChangeLog 262B
dayhoff.dat 2KB
ENSG00000198712.fa 2KB
F9-demo.fa 966B
brca1.fasta 164KB
brca1.fasta 164KB
primates_brca1.fasta 29KB
primate_brca1.fasta 20KB
primate_brca1.fasta 20KB
refseqs_protein.fasta 17KB
brca1-bats.fasta 15KB
SCA1-cds.fasta 14KB
long_testseqs.fasta 13KB
long_testseqs.fasta 13KB
primate_cdx2_promoter.fasta 5KB
formattest.fasta 3KB
trna_profile.fasta 2KB
BRCA1-demo.fasta 2KB
test2.fasta 345B
refseqs.fasta 319B
inseqs_protein.fasta 130B
c_elegans_WS199_dna_shortened.fasta 104B
inseqs.fasta 42B
ST_genome_part.gb 32KB
annotated_seq.gb 15KB
formattest.gde 3KB
gff2_test.gff 514B
c_elegans_WS199_shortened_gff.gff3 1KB
.gitignore 414B
formattest.fasta.gz 736B
.hgignore 299B
.hgtags 1002B
MANIFEST.in 77B
tox.ini 2KB
tbp.jaspar 277B
sample.jaspar 244B
plotly-latest.min.js 2.94MB
require.min.js 17KB
GN-tree.json 59KB
tp53.json 59KB
dists_for_phylo.json 12KB
site-het-param-rules.json 10KB
tree-with-support.json 3KB
LICENSE 1KB
scitrack.log 5KB
Makefile 3KB
bowtie_output.map 854B
README.md 5KB
formattest.msf 3KB
nexus_dna.nex 8KB
nexus_comments.nex 478B
nexus_mixed.nex 401B
nexus_aa.nxs 3KB
formattest.paml 3KB
brca1_5.250.paml 1KB
brca1_5.paml 352B
test.paml 352B
2E12.pdb 159KB
1A1X.pdb 97KB
1LJO.pdb 82KB
interleaved.phylip 7KB
formattest.phylip 3KB
abglobin_aa.phylip 2KB
CerebellumDukeDNaseSeq.pk 1KB
Homo_sapiens_codon_usage.pri 451KB
test.psl 767B
test_coevolution.py 465KB
alignment.py 166KB
test_alignment.py 137KB
coevolution.py 94KB
tree.py 88KB
test_tree.py 86KB
test_likelihood_function.py 80KB
test_test.py 77KB
test_table.py 73KB
table.py 71KB
sequence.py 69KB
test.py 63KB
models.py 62KB
ebi.py 57KB
test_distribution.py 54KB
test_misc.py 53KB
distance_transform.py 52KB
test_ns_substitution_model.py 51KB
letter.py 48KB
test_sequence.py 48KB
moltype.py 47KB
likelihood_function.py 40KB
test_moltype.py 39KB
pairwise.py 38KB
misc.py 38KB
test_core_standalone.py 37KB
substitution_model.py 36KB
test_ebi.py 36KB
evo.py 36KB
test_distance.py 35KB
data_store.py 35KB
location.py 33KB
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