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allcopol-0.1.2
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AllCoPol: Inferring allele co-ancestry in polyploids
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | allcopol-0.1.2 |
| نام | allcopol |
| نسخه کتابخانه | 0.1.2 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Ulrich Lautenschlager |
| ایمیل نویسنده | ulrich.lautenschlager@ur.de |
| آدرس صفحه اصلی | https://github.com/AGOberprieler/allcopol |
| آدرس اینترنتی | https://pypi.org/project/allcopol/ |
| مجوز | MIT |
# AllCoPol
AllCoPol is collection of tools for the analysis of polyploids, that allows
to infer ancestral allele combinations as well as corresponding subgenome phylogenies.
## Installation
AllCoPol is hosted at the Python Package Index (PyPI), so it can be easily
installed via pip:
```bash
python3 -m pip install allcopol
```
To run PhyloNet, Java 1.7 or later has to be installed.
## Contained tools
### allcopol
This is the main tool of the package implementing heuristic optimization of
ancestral allele combinations. It requires at least four arguments,
specifying the input files (`-A`, `-G`), the number of supplied gene trees per marker
(`-S`), and the path to a PhyloNet jar file (`-P`),
which can can be obtained from https://bioinfocs.rice.edu/phylonet (newest tested version: 3.8.0).
Besides, the tabu tenure (`-t`) and the number of iterations (`-i`) are crucial
parameters, which have to be tuned for proper optimization.
The allele mapping file (`-A`) is a tab-delimited text file with one line
per accession and four columns: accession, taxon, allele IDs (comma separated),
and ploidy level.
The gene tree file (`-G`) consists of newick strings supplied as one tree per line.
For the trees, which are assumed to be rooted, topologies are sufficient while
edge lengths, support values, etc. will be ignored. Multiple gene trees per
marker can be supplied as consecutive lines in the tree file, e.g.
```text
<tree1 for marker1>
<tree2 for marker1>
<tree3 for marker1>
<tree1 for marker2>
<tree2 for marker2>
<tree3 for marker2>
...
```
Because the program cannot know from the input file which trees belong to the
same marker, the `-S` option has to be set correctly (for the example above: `-S 3`).
To get a complete list of program options, type
```bash
allcopol --help
```
_Minimal example:_
mapping.nw (input):
```text
acc1 sp1 A_1,A_2 2
acc2 sp1 B_1,B_2 2
acc3 sp2 C_1,C_2 2
acc4 sp2 D_1,D_2 2
acc5 sp3 E_1,E_2 2
acc6 sp4 F_1,F_2 2
acc7 sp5 G_1,G_2,H_1,H_2 4
```
trees.nw (input):
```text
(((E_2,(B_1,C_2)),(G_1,F_2)),((H_1,H_2),((A_2,A_1),((G_2,D_2),(F_1,((C_1,B_2),(D_1,E_1)))))));
((((F_2,(G_2,(G_1,F_1))),(A_1,A_2)),((((C_1,C_2),B_1),B_2),(((D_2,D_1),E_1),E_2))),(H_1,H_2));
((((G_2,((F_1,F_2),G_1)),A_1),((H_2,H_1),(D_1,E_1))),(((D_2,E_2),(C_2,(B_2,(C_1,B_1)))),A_2));
(((B_2,(C_2,B_1)),(H_2,H_1)),((A_2,A_1),(((G_2,G_1),(F_2,F_1)),((E_1,D_1),((D_2,E_2),C_1)))));
(((A_1,A_2),(H_2,H_1)),(((E_1,D_1),((F_1,F_2),(G_2,G_1))),(((E_2,D_2),(B_1,(C_2,B_2))),C_1)));
```
command:
```bash
allcopol -A mapping.txt -G trees.nw -S 1 -P PhyloNet_3.8.0.jar -t 5 -i 20
```
Setting the tabu tenure to zero and using reinitialization (-u), it is also
possible to perform random restart hillclimbing instead of tabu search.
While this avoids extensive parameter tuning, it usually requires a higher
number of iterations to obtain satisfactory solutions:
```bash
allcopol -A mapping.txt -G trees.nw -S 1 -P PhyloNet_3.8.0.jar -t 0 -u 1 -i 100
```
If runtime is limiting, the number of evaluated solutions per iteration can be
limited via the -s option. Note that this may be at the expense of a lower final
solution quality.
### create_indfile
This script takes a number of allele mapping strings (one per line, obtained
by multiple runs of `allcopol` based on the same\* input files) as input and
prints a matrix representation of the inferred allele partitions. The latter can
be used as input for Clumpp or `align_clusters`.
\* The used gene trees may vary, but the underlying markers and their order in
the tree files must be identical.
_Example:_
mappings.txt (input):
```text
sp2:C_1,C_2;sp3:D_1,D_2;sp1___01:B_1_m0,B_2_m0,B_1_m1,B_2_m1;sp1___02:A_1_m0,A_2_m0,A_1_m1,A_2_m1
sp2:C_1,C_2;sp3:D_1,D_2;sp1___01:A_1_m0,B_2_m0,B_1_m1,B_2_m1;sp1___02:A_2_m0,A_1_m1,A_2_m1,B_1_m0
sp2:C_1,C_2;sp3:D_1,D_2;sp1___01:A_1_m0,A_2_m0,A_1_m1,A_2_m1;sp1___02:B_1_m0,B_2_m0,B_1_m1,B_2_m1
sp2:C_1,C_2;sp3:D_1,D_2;sp1___01:A_1_m0,A_2_m0,A_1_m1,B_2_m1;sp1___02:B_1_m0,B_2_m0,B_1_m1,A_2_m1
```
command:
```bash
create_indfile mappings.txt sp1 > example.indfile
```
The second argument `sp1` is the name of the polyploid taxon, whose
pseudo-diploid ancestors have been inferred.
example.indfile (output):
```text
1 1 (x) 1 : 0 1
2 2 (x) 1 : 0 1
3 3 (x) 1 : 0 1
4 4 (x) 1 : 0 1
5 5 (x) 1 : 1 0
6 6 (x) 1 : 1 0
7 7 (x) 1 : 1 0
8 8 (x) 1 : 1 0
1 1 (x) 1 : 1 0
2 2 (x) 1 : 0 1
...
```
### align_clusters
This tool can be used to match clusters (pseudo-diploids) among multiple
reconstructions. To avoid getting stuck in a local optimum, a tabu list is
applied, whose size can be specified via the `-t` option - unlike `allcopol`,
the heuristic used for this step seems to be relatively robust.
`-n` sets the total number of optimization iterations.
Applied to the matrix representation written above, the command
```bash
align_clusters -n 50 -t 2 example.indfile
```
creates the output file example.permutations:
```text
2 1
2 1
1 2
1 2
```
and a second file containing the averaged cluster coefficients
(example.clustering).
### relabel_trees
Using the output of `align_clusters`, the species trees obtained by multiple
runs of `allcopol` can be relabeled to mitigate label switching.
`relabel_trees` expects three arguments, a file containing the inferred species
trees, the name of the analyzed polyploid taxon and a permutation file as
written by `align_clusters`.
_Example:_
sp_trees.nw (input):
```text
(sp3,(sp1___02,(sp1___01,sp2)));
(sp3,(sp1___02,(sp1___01,sp2)));
(sp3,(sp1___01,(sp1___02,sp2)));
(sp3,(sp1___01,(sp1___02,sp2)));
```
The command
```bash
relabel_trees sp_trees.nw sp1 example.permutations
```
yields
```text
(sp3,(sp1_P1,(sp1_P2,sp2)));
(sp3,(sp1_P1,(sp1_P2,sp2)));
(sp3,(sp1_P1,(sp1_P2,sp2)));
(sp3,(sp1_P1,(sp1_P2,sp2)));
```
Now that the pseudo-diploids are labeled according to their homology,
conventional consensus methods can be applied to the trees.
نیازمندی
| مقدار | نام |
|---|---|
| - | argparse |
| - | biopython |
| - | configargparse |
| - | numpy |
| - | scipy |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.5 | Python |
نحوه نصب
نصب پکیج whl allcopol-0.1.2:
pip install allcopol-0.1.2.whl
نصب پکیج tar.gz allcopol-0.1.2:
pip install allcopol-0.1.2.tar.gz