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dima-cli-4.1.3
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مشاهده بیشترتوضیحات
A command-line tool that analyses the diversity and motifs of biological sequences
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | dima-cli-4.1.3 |
| نام | dima-cli |
| نسخه کتابخانه | 4.1.3 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Shan Tharanga <stwm2@student.london.ac.uk> |
| ایمیل نویسنده | Shan Tharanga <stwm2@student.london.ac.uk> |
| آدرس صفحه اصلی | - |
| آدرس اینترنتی | https://pypi.org/project/dima-cli/ |
| مجوز | MIT |
# DiMA - Diversity Motif Analyser
## Table of Contents
- [What is DiMA?](#what-is-dima)
- [Publications](#publications)
- [Installation](#installation)
- [Basic Usage](#basic-usage)
- [Shell Command](#shell-command)
- [Python](#python)
- [Results](#results)
- [Advance Usage](#advance-usage)
- [Shell Command](#shell-command)
- [Python](#python)
- [Results](#results)
- [Command-Line Arguments](#command-line-arguments)
- [Module Parameters](#module-parameters)
## What is DiMA?
Protein sequence diversity is one of the major challenges in the design of diagnostic, prophylactic and therapeutic
interventions against viruses. DiMA is a tool designed to facilitate the dissection of protein sequence diversity
dynamics for viruses. DiMA provides a quantitative measure of sequence diversity by use of Shannon’s entropy,
applied via a user-defined k-mer sliding window. Further, the entropy value is corrected for sample size bias by
applying a statistical adjustment.
Additionally, DiMA further interrogates the diversity by dissecting the entropy value at each k-mer position to various
diversity motifs. The distinct k-mer sequences at each position are classified into the following motifs based on
their incidence.
- **Index**: The predominant sequence.
- **Major**: The sequence with the second highest incidence after the Index.
- **Minor**: Kmers with incidence in between major and unique motifs
- **Unique**: Kmers which are only seen once in a particular kmer position.
Moreover, the description line of the sequences in the alignment can be
formatted for inclusion of meta-data that can be tagged to the diversity motifs. DiMA enables comparative diversity
dynamics analysis, within and between proteins of a virus species, and proteomes of different viral species.
## Publications
- https://arxiv.org/abs/2205.13915
## Installation
`pip install dima-cli`
## Basic Usage
### Shell Command
```shell
dima-cli -i aligned_sequences.afa -o results.json
```
### Python
```python
from dima import Dima
results = Dima(sequences="aligned_sequences.afa").run()
```
### Results
<details>
<summary>Click to view basic results</summary>
```
{
"sequence_count": 5,
"support_threshold": 30,
"low_support_count": 20,
"query_name": "Unknown Query",
"kmer_length": 9,
"average_entropy": 0.06854034285524647,
"highest_entropy": {
"position": 186,
"entropy": 1.3921472236645345
},
"results": [
{
"position": 1,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "MSASKEIKS",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "SAGVYMGNL",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 2,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "AGVYMGNLS",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "SASKEIKSF",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
}
]
},
{
"position": 3,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "GVYMGNLSS",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "ASKEIKSFL",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
}
]
},
{
"position": 4,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "VYMGNLSSQ",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "SKEIKSFLW",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
}
]
},
{
"position": 5,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "KEIKSFLWT",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "YMGNLSSQQ",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 6,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "MGNLSSQQL",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "EIKSFLWTQ",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
}
]
},
{
"position": 7,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "IKSFLWTQS",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "GNLSSQQLD",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 8,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "KSFLWTQSL",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "NLSSQQLDQ",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 9,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "SFLWTQSLR",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "LSSQQLDQR",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 10,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "SSQQLDQRR",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "FLWTQSLRR",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
}
]
},
{
"position": 11,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "LWTQSLRRE",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "SQQLDQRRA",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 12,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "QQLDQRRAL",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "WTQSLRREL",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
}
]
},
{
"position": 13,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "TQSLRRELS",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "QLDQRRALL",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 14,
"low_support": "LS",
"entropy": 1.3709505944546687,
"support": 5,
"distinct_variants_count": 2,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 40.0,
"diversity_motifs": [
{
"sequence": "QSLRRELSG",
"count": 3,
"incidence": 60.000004,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "LDQRRALLS",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "QSLRRELSS",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 15,
"low_support": "LS",
"entropy": 1.3709505944546687,
"support": 5,
"distinct_variants_count": 2,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 40.0,
"diversity_motifs": [
{
"sequence": "DQRRALLSM",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "SLRRELSGY",
"count": 3,
"incidence": 60.000004,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "SLRRELSSY",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 16,
"low_support": "LS",
"entropy": 1.3709505944546687,
"support": 5,
"distinct_variants_count": 2,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 40.0,
"diversity_motifs": [
{
"sequence": "QRRALLSMI",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "LRRELSSYC",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "LRRELSGYC",
"count": 3,
"incidence": 60.000004,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
}
]
},
{
"position": 17,
"low_support": "LS",
"entropy": 1.3709505944546687,
"support": 5,
"distinct_variants_count": 2,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 40.0,
"diversity_motifs": [
{
"sequence": "RRELSGYCS",
"count": 3,
"incidence": 60.000004,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "RRALLSMIG",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "RRELSSYCS",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 18,
"low_support": "LS",
"entropy": 1.3709505944546687,
"support": 5,
"distinct_variants_count": 2,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 40.0,
"diversity_motifs": [
{
"sequence": "RELSGYCSN",
"count": 3,
"incidence": 60.000004,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "RALLSMIGM",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "RELSSYCSN",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
},
{
"position": 19,
"low_support": "LS",
"entropy": 1.3709505944546687,
"support": 5,
"distinct_variants_count": 2,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 40.0,
"diversity_motifs": [
{
"sequence": "ALLSMIGMS",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "ELSSYCSNI",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "ELSGYCSNI",
"count": 3,
"incidence": 60.000004,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
}
]
},
{
"position": 20,
"low_support": "LS",
"entropy": 1.3709505944546687,
"support": 5,
"distinct_variants_count": 2,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 40.0,
"diversity_motifs": [
{
"sequence": "LSGYCSNIK",
"count": 3,
"incidence": 60.000004,
"motif_short": "I",
"motif_long": "Index",
"metadata": null
},
{
"sequence": "LLSMIGMSG",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
},
{
"sequence": "LSSYCSNIK",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": null
}
]
}
]
}
```
</details>
## Advance Usage
### Shell Command
```shell
dima-cli -i aligned_sequences.afa -o results.json -f "accession|strain|country|date"
```
### Python
```python
from dima import Dima
results = Dima(sequences="aligned_sequences.afa", header_format="accession|strain|country|date").run()
```
### Results
<details>
<summary>Click to view advanced results</summary>
```
{
"sequence_count": 5,
"support_threshold": 30,
"low_support_count": 20,
"query_name": "Unknown Query",
"kmer_length": 9,
"average_entropy": 0.06854034285524647,
"highest_entropy": {
"position": 186,
"entropy": 1.3921472236645345
},
"results": [
{
"position": 1,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "MSASKEIKS",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": {
"Accession": {
"AYD75365.1": 1,
"QEP52131.1": 1,
"AYD75321.1": 1,
"AYD75325.1": 1
},
"Country": {
"Sierra Leone": 4
},
"Species": {
"Homo sapiens": 3,
"Unknown": 1
},
"Year": {
"1977": 1,
"2012": 1,
"1980": 1,
"1979": 1
}
}
},
{
"sequence": "SAGVYMGNL",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": {
"Accession": {
"AYD75329.1": 1
},
"Country": {
"Sierra Leone": 1
},
"Year": {
"1975": 1
},
"Species": {
"Homo sapiens": 1
}
}
}
]
},
{
"position": 2,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "SASKEIKSF",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": {
"Species": {
"Homo sapiens": 3,
"Unknown": 1
},
"Year": {
"1977": 1,
"1980": 1,
"1979": 1,
"2012": 1
},
"Country": {
"Sierra Leone": 4
},
"Accession": {
"AYD75325.1": 1,
"QEP52131.1": 1,
"AYD75365.1": 1,
"AYD75321.1": 1
}
}
},
{
"sequence": "AGVYMGNLS",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": {
"Species": {
"Homo sapiens": 1
},
"Year": {
"1975": 1
},
"Accession": {
"AYD75329.1": 1
},
"Country": {
"Sierra Leone": 1
}
}
}
]
},
{
"position": 3,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
"sequence": "ASKEIKSFL",
"count": 4,
"incidence": 80.0,
"motif_short": "I",
"motif_long": "Index",
"metadata": {
"Year": {
"1980": 1,
"1977": 1,
"1979": 1,
"2012": 1
},
"Accession": {
"AYD75321.1": 1,
"AYD75365.1": 1,
"QEP52131.1": 1,
"AYD75325.1": 1
},
"Country": {
"Sierra Leone": 4
},
"Species": {
"Unknown": 1,
"Homo sapiens": 3
}
}
},
{
"sequence": "GVYMGNLSS",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": {
"Accession": {
"AYD75329.1": 1
},
"Species": {
"Homo sapiens": 1
},
"Country": {
"Sierra Leone": 1
},
"Year": {
"1975": 1
}
}
}
]
},
{
"position": 4,
"low_support": "LS",
"entropy": 0.7219280948873623,
"support": 5,
"distinct_variants_count": 1,
"distinct_variants_incidence": 100.0,
"total_variants_incidence": 20.0,
"diversity_motifs": [
{
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},
{
"sequence": "LSSYCSNIK",
"count": 1,
"incidence": 20.0,
"motif_short": "U",
"motif_long": "Unique",
"metadata": {
"Year": {
"2012": 1
},
"Species": {
"Homo sapiens": 1
},
"Accession": {
"QEP52131.1": 1
},
"Country": {
"Sierra Leone": 1
}
}
}
]
}
]
}
```
</details>
## Command-Line Arguments
| **Argument** | **Type** | **Required** | **Default** | **Example** | **Description** |
|--------------|--------------------|--------------|---------------|--------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------|
| -h | N/A | False | N/A | `dima-cli -h` | Prints a summary of all available command-line arguments. |
| -n | String | False | Unknown | `dima-cli -i sequences.afa -o results.json -f "accession\|strain\|country" -n "NA"` -n "Unknown" | Silently fix missing values in the FASTA header with given value. |
| -v | N/A | False | N/A | `dima-cli -v` | Prints the version of dima-cli that is currently installed. |
| -q | String | False | Unknown Query | `dima-cli -q "Coronavirus Surface Protein" -i sequences.afa -o results.json` | The name of the sample that will appear on the results. |
| -i | String | True | N/A | `dima-cli -i sequences.afa -o results.json` | The path to the FASTA Multiple Sequence Alignment file. |
| -o | String | True | N/A | `dima-cli -i sequences.afa -o results,json` | The location where the results shall be saved. |
| -l | Integer | False | 9 | `dima-cli -i sequences.afa -l 12 -o results.json` | The length of the kmers generated. |
| -f | String | False | N/A | `dima-cli -i sequences.afa -f "accession\|strain\|country" -o results.json` | The format of the FASTA header. Labels where each variant of a kmer position originated from. |
| -s | Integer | False | 30 | `dima-cli -i sequences.afa -l 12 -s 40 -o results.json` | The minimum required support for each kmer position. |
| -a | nucleotide/protein | False | protein | `dima-cli -i dna_sequences.afa -a nucleotide -o results.json` | The alphabet of the sequences (ie: `protein`/`nucleotide`, default: protein) |
| -t | json/xlsx | False | json | `dima-cli -i dna_sequences.afa -a nucleotide -o results.json -t xlsx` | The output format (ie: `json`/`xlsx`, default: json) |
| -c | String | False | N/A | `dima-cli -i dna_sequences.afa -a nucleotide -o results.json -c hcs.json` | Path to save Highly Conserved Sequences (HCS) in JSON format. |
| -e | Float | False | 100 | `dima-cli -i dna_sequences.afa -a nucleotide -o results.json -c hcs.json -e 90.5` | Minimum incidence (%) threshold for HCS concatenation. |
## Module Parameters
| **Parameter** | **Type** | **Required** | **Default** | **Description** |
|-------------------|-----------------|--------------|-----------------|-----------------------------------------------------------------------------------------------------------------|
| sequences | String/StringIO | True | N/A | The path to a FASTA Multiple Sequence Alignment file (MSA), or a StringIO object containing FASTA MSA. |
| kmer_length | Integer | False | 9 | The length of the kmers generated. |
| header_fillna | String | False | Unknown | Silently fix missing values in the FASTA header with given value (only required when `header_format` is given). |
| header_format | String | False | N/A | The format of the FASTA header. Labels where each variant of a kmer position originated from. |
| support_threshold | Integer | False | 30 | The minimum required support for each kmer position. |
| query_name | String | False | Unknown Query | The name of the sample that will appear on the results. |
| alphabet | String | False | protein | The alphabet of the sequences (ie: protein/nucleotide, default: protein) |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7,<3.11 | Python |
نحوه نصب
نصب پکیج whl dima-cli-4.1.3:
pip install dima-cli-4.1.3.whl
نصب پکیج tar.gz dima-cli-4.1.3:
pip install dima-cli-4.1.3.tar.gz