| Name | crispio JSON |
| Version |
0.0.2.post2
JSON |
| download |
| home_page | None |
| Summary | Designing CRISPR-Cas guide RNAs in bacteria. |
| upload_time | 2024-03-23 16:16:12 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) [year] [fullname] Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
biology
crispr
science
bacteria
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# 🌱 crispio
Command-line utilities and Python API for designing CRISPRi experiments in bacteria.
**crispio** makes it easy to design annotated and systematically named libraries of guide RNAs.
Alternatively, **crispio** can map a FASTA of existing guides to a genome.
**Hint**: If you have a table of guide RNAs from the literature that you want to annotate
with genomic features, **crispio** is your tool. Use [`bioino table2fasta`](https://github.com/scbirlab/bioino#command-line)
to convert the table to a FASTA file, then use [`crispio map`](#mapping-known-guide-rnas-to-a-genome).
- [Installation](#installation)
- [Command-line interface](#command-line-interface)
- [Generating new guide RNAs](#generating-new-guide-rnas)
- [Mapping known guide RNAs to a genome](#mapping-known-guide-rnas-to-a-genome)
- [Annotating with extra features](#annotating-with-extra-features)
- [Checking for off-targets](#checking-for-off-targets)
- [Python API](#python-api)
- [Issues, bugs, suggestions]()
- [Documentation]()
## Installation
### The easy way
Install the pre-compiled version from GitHub:
```bash
$ pip install crispio
```
### From source
Clone the repository, then `cd` into it. Then run:
```bash
$ pip install -e .
```
## Command-line interface
The main way to use **crispio** is with its several subcommands. You can get
help by entering `crispio <subcommand> --help`.
```bash
$ crispio --help
usage: crispio [-h] {generate,map,featurize,offtarget} ...
Design and analysis of bacterial CRISPRi experiments.
optional arguments:
-h, --help show this help message and exit
Sub-commands:
{generate,map,featurize,offtarget}
Use these commands to specify the tool you want to use.
generate Generate and annotate all guide RNAs for a given genome.
map Map and annotate provided guide RNAs to a given genome.
featurize Annotate guide RNAs with additional calculated features.
offtarget Compare two sets of guide RNAs for potential cross-target activity.
```
## Generating new guide RNAs
Given a genome in FASTA format and a matching GFF,
[both available for your favourite bacterium from NCBI](https://www.ncbi.nlm.nih.gov/genbank/ftp/),
along with a PAM sequence or name of a common Cas9 ortholog, you can generate all the possible
guide RNAs and annotate them from the GFF in one go.
The command `crisio generate` finds the position on the genome, annotates
with genomic features, replichore, and sequence context, detects restriction
sites, and gives each guide RNA a unique ID and a human-readable
adjective-noun mnemonic.
```bash
$ crispio generate -l 20 --pam Sth1 -g EcoMG1655-NC_000913.3.fasta -a EcoMG1655-NC_000913.3.gff3 | head
🚀 Generating sgRNAs with the following parameters:
...
##sequence-region NC_000913.3 1 4641652
##species https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145
##genome-sequence NC_000913.3 1 6930
##genome-description Escherichia coli str. K-12 substr. MG1655, complete genome
##genome-filename 63
#sgRNA-map crispio 63 62
NC_000913.3 crispio protospacer 2 21 . + . ID=sgr-e5373243;Name=thrL-21-modest_saddle;ann_Name=thrL;ann_end=255;ann_feature=gene;ann_gene=thrL;ann_gene_biotype=protein_coding;ann_locus_tag=_up-thrL;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=190;ann_strand=+;guide_context_down=TATGTCTCTGTGTGGATTAA;guide_context_up=CAGCACCCCAGGAACCCATA;guide_length=20;guide_re_sites=;guide_sequence=GCTTTTCATTCTGACTGCAA;guide_sequence_hash=19d8fdaa;mnemonic=modest_saddle;pam_end=28;pam_offset=-166;pam_replichore=R;pam_search=NNRGVAN;pam_sequence=CGGGCAA;pam_start=21;source_name=thrL-21-modest_saddle
...
NC_000913.3 crispio protospacer 180 199 . + . ID=sgr-b71e7fa7;Name=thrL-199-bouncy_sabine;ann_Name=thrL;ann_end=255;ann_feature=gene;ann_gene=thrL;ann_gene_biotype=protein_coding;ann_locus_tag=b0001;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=190;ann_strand=+;guide_context_down=CACCATTACCACCACCATCA;guide_context_up=CAGATAAAAATTACAGAGTA;guide_length=20;guide_re_sites=;guide_sequence=CACAACATCCATGAAACGCA;guide_sequence_hash=3e6eb3a0;mnemonic=bouncy_sabine;pam_end=206;pam_offset=65;pam_replichore=R;pam_search=NNRGVAN;pam_sequence=TTAGCAC;pam_start=199;source_name=thrL-199-bouncy_sabine
```
The guides are output in GFF format, so it can be used directly as an annotation
track in your favourite genome browser.
It can be dense for human beings to parse, so you can convert to a TSV using
[`bioino ggf2table`](https://github.com/scbirlab/bioino#command-line):
```bash
$ head guides.gff | bioino gff2table
...
seqid source feature start end score strand phase ID Name ann_Name ann_end ann_feature ann_gene ann_gene_biotype ann_locus_tag ann_phase ann_score ann_seqid ann_source ann_start ann_strand guide_context_down guide_context_up guide_length guide_re_sites guide_sequence guide_sequence_hash mnemonic pam_end pam_offset pam_replichore pam_search pam_sequence pam_start source_name
NC_000913.3 crispio protospacer 2 21 . + . sgr-e5373243 thrL-21-modest_saddle thrL 255 gene thrL protein_coding _up-thrL . . NC_000913.3 RefSeq 190 + TATGTCTCTGTGTGGATTAA CAGCACCCCAGGAACCCATA 20 GCTTTTCATTCTGACTGCAA 19d8fdaa modest_saddle 28 -166 R NNRGVAN CGGGCAA 21 thrL-21-modest_saddle
...
NC_000913.3 crispio protospacer 180 199 . + . sgr-b71e7fa7 thrL-199-bouncy_sabine thrL 255 gene thrL protein_coding b0001 . . NC_000913.3 RefSeq 190 + CACCATTACCACCACCATCA CAGATAAAAATTACAGAGTA 20 CACAACATCCATGAAACGCA 3e6eb3a0 bouncy_sabine 206 65 R NNRGVAN TTAGCAC 199 thrL-199-bouncy_sabine
```
All the commands are pipeable. All the chatter goes to `stderr`, so
you can pipe your actual data through `stdout`.
## Mapping known guide RNAs to a genome
The command `crispio map` is similar, but takes known guides in FASTA format as input.
```bash
$ crispio map cv-nar-2020_TableS1.fasta -g EcoMG1655-NC_000913.3.fasta -a EcoMG1655-NC_000913.3.gff3 --pam Spy
🚀 Mapping sgRNAs with the following parameters:
...
Finding sgRNA sites matching 21417 sequences from cv-nar-2020_TableS1.fasta and matching PAM Spy (NGGN) in EcoMG1655-NC_000913.3.fasta...
##sequence-region NC_000913.3 1 4641652
##species https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145
##genome-sequence NC_000913.3 1 4641652
##genome-description Escherichia coli str. K-12 substr. MG1655, complete genome
##genome-filename EcoMG1655-NC_000913.3.fasta
#sgRNA-map crispio EcoMG1655-NC_000913.3.fasta EcoMG1655-NC_000913.3.gff3
NC_000913.3 crispio 2400946 2400965 . + . ID=sgr-7a0a4f43;Name=nuoF-2400965-level_herman;ann_Name=nuoF;ann_end=2401555;ann_feature=gene;ann_gene=nuoF;ann_gene_biotype=protein_coding;ann_locus_tag=b2284;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=2400218;ann_strand=-;guide_context_down=TAGCACGACGTCCTTCCAGG;guide_context_up=CCATGCGCCGGAGGTTGCCG;guide_length=20;guide_re_sites=;guide_sequence=GGAAGGGTGGCTTCGAGCGT;guide_sequence_hash=6a359e86;mnemonic=level_herman;pam_end=2400969;pam_offset=0;pam_replichore=L;pam_search=NGGN;pam_sequence=GGGT;pam_start=2400965;source_name=GGAAGGGTGGCTTCGAGCGT
...
NC_000913.3 crispio protospacer 2400933 2400952 . + . ID=sgr-32446b00;Name=nuoF-2400952-telling_austria;ann_Name=nuoF;ann_end=2401555;ann_feature=gene;ann_gene=nuoF;ann_gene_biotype=protein_coding;ann_locus_tag=b2284;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=2400218;ann_strand=-;guide_context_down=TTCGAGCGTGGGTTAGCACG;guide_context_up=AGGTCGGTTTACCCCATGCG;guide_length=20;guide_re_sites=;guide_sequence=CCGGAGGTTGCCGGGAAGGG;guide_sequence_hash=1908728f;mnemonic=telling_austria;pam_end=2400956;pam_offset=0;pam_replichore=L;pam_search=NGGN;pam_sequence=TGGC;pam_start=2400952;source_name=CCGGAGGTTGCCGGGAAGGG
```
If you don't have a FASTA to hand, but a table instead, you can pipe it
through [`bioino table2fasta`](https://github.com/scbirlab/bioino#command-line):
```bash
$ cat guide-table.tsv | bioino table2fasta -s sequence -n guide_name | crispio map -g EcoMG1655-NC_000913.3.fasta -a EcoMG1655-NC_000913.3.gff3 --pam Sth1
##sequence-region NC_000913.3 1 4641652
##species https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145
##genome-sequence NC_000913.3 1 4641652
##genome-description Escherichia coli str. K-12 substr. MG1655, complete genome
##genome-filename EcoMG1655-NC_000913.3.fasta
#sgRNA-map crispio EcoMG1655-NC_000913.3.fasta EcoMG1655-NC_000913.3.gff3
NC_000913.3 crispio protospacer 1236 1255 . + . ID=sgr-831073da;Name=thrA-1255-honest_brother;ann_Name=thrA;ann_end=2799;ann_feature=gene;ann_gene=thrA;ann_gene_biotype=protein_coding;ann_locus_tag=b0002;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=337;ann_strand=+;guide_context_down=TTCCAATCTGAATAACATGG;guide_context_up=CTCATTGGTGCCAGCCGTGA;guide_length=20;guide_re_sites=BbsI;guide_sequence=TGAAGACGAATTACCGGTCA;guide_sequence_hash=55934652;mnemonic=honest_brother;pam_end=1262;pam_offset=2462;pam_replichore=R;pam_search=NNRGVAN;pam_sequence=AGGGCAT;pam_start=1255;source_name=thrA-1255-honest_brother
...
NC_000913.3 crispio protospacer 3999 4018 . + . ID=sgr-83d65199;Name=thrC-4018-jolly_lunar;ann_Name=thrC;ann_end=5020;ann_feature=gene;ann_gene=thrC;ann_gene_biotype=protein_coding;ann_locus_tag=b0004;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=3734;ann_strand=+;guide_context_down=TGTTCCACGGGCCAACGCTG;guide_context_up=CCCGGCTCCGGTCGCCAATG;guide_length=20;guide_re_sites=BtgZI;guide_sequence=TTGAAAGCGATGTCGGTTGT;guide_sequence_hash=e539f903;mnemonic=jolly_lunar;pam_end=4025;pam_offset=1286;pam_replichore=R;pam_search=NNRGVAN;pam_sequence=CTGGAAT;pam_start=4018;source_name=thrC-4018-jolly_lunar
```
## Annotating with extra features
It may be useful to calcuate additional guide RNA features for downstream applications like
machine learning. These are the available extra features:
```python
>>> from crispio import *
>>> get_features()
['on_nontemplate_strand', 'context_up2', 'context_down2', 'context_up_autocorr', 'pam_n', 'pam_def', 'pam_gc', 'pam_autocorr', 'pam_scaff_corr', 'guide_purine', 'guide_gc', 'seed_seq', 'guide_start3', 'guide_end3', 'guide_autocorr', 'guide_scaff_corr']
```
Using the command-line these can be easily added to a GFF or piped output
from `crispio map` or `crispio generate`.
```bash
$ cat mapped-guides.gff | head | crispio featurize --scaffold Spy
🚀 Featurizing sgRNAs with the following parameters:
...
> Generating features for guides...
##sequence-region NC_000913.3 1 4641652
##species https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145
##genome-sequence NC_000913.3 1 4641652
##genome-description Escherichia coli str. K-12 substr. MG1655, complete genome
##genome-filename EcoMG1655-NC_000913.3.fasta
#sgRNA-map crispin EcoMG1655-NC_000913.3.fasta EcoMG1655-NC_000913.3.gff3
NC_000913.3 crispin protospacer 2400946 2400965 . + . ID=sgr-7a0a4f43;Name=nuoF-2400965-level_herman;ann_Name=nuoF;ann_end=2401555;ann_feature=gene;ann_gene=nuoF;ann_gene_biotype=protein_coding;ann_locus_tag=b2284;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=2400218;ann_strand=-;guide_context_down=TAGCACGACGTCCTTCCAGG;guide_context_up=CCATGCGCCGGAGGTTGCCG;guide_length=20;guide_re_sites=;guide_sequence=GGAAGGGTGGCTTCGAGCGT;guide_sequence_hash=6a359e86;mnemonic=level_herman;pam_end=2400969;pam_offset=0;pam_replichore=L;pam_search=NGGN;pam_sequence=GGGT;pam_start=2400965;source_name=GGAAGGGTGGCTTCGAGCGT;feat_on_nontemplate_strand=True;feat_context_up2=CG;feat_context_down2=TA;feat_context_up_autocorr=8.928;feat_pam_n=G;feat_pam_def=GGT;feat_pam_gc=0.750;feat_pam_autocorr=2.167;feat_pam_scaff_corr=1.917;feat_guide_purine=0.650;feat_guide_gc=0.650;feat_seed_seq=AGCGT;feat_guide_start3=GGA;feat_guide_end3=CGT;feat_guide_autocorr=8.704;feat_guide_scaff_corr=9.772
...
NC_000913.3 crispin protospacer 1764112 1764131 . + . ID=sgr-f3815635;Name=sufA-1764131-scarce_game;ann_Name=sufA;ann_end=1764386;ann_feature=gene;ann_gene=sufA;ann_gene_biotype=protein_coding;ann_locus_tag=b1684;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=1764018;ann_strand=-;guide_context_down=ATCGCTTGCAGCGGGACAAA;guide_context_up=GTCCTTCACGAACGAAATCG;guide_length=20;guide_re_sites=;guide_sequence=ACTTCCGTGCCATCAATAAA;guide_sequence_hash=dc4688e0;mnemonic=scarce_game;pam_end=1764135;pam_offset=0;pam_replichore=R;pam_search=NGGN;pam_sequence=CGGC;pam_start=1764131;source_name=ACTTCCGTGCCATCAATAAA;feat_on_nontemplate_strand=True;feat_context_up2=CG;feat_context_down2=AT;feat_context_up_autocorr=7.159;feat_pam_n=C;feat_pam_def=GGC;feat_pam_gc=1.000;feat_pam_autocorr=2.333;feat_pam_scaff_corr=1.667;feat_guide_purine=0.450;feat_guide_gc=0.400;feat_seed_seq=ATAAA;feat_guide_start3=ACT;feat_guide_end3=AAA;feat_guide_autocorr=7.767;feat_guide_scaff_corr=10.528
```
The attributes starting with `feat_` have been added.
## Checking for off-targets
One downside of CRISPR-based tools is the possibility of off-target effects.
`crispio offtarget` compares two GFF files, or one GFF file against itself, for
guide RNA sites that share a seed sequence (4 PAM-proximal bases) and have a
Hamming distance of 4 or less.
```bash
$ cat mapped-guides.gff | head | crispio offtarget -2 <(cat mapped-guides.gff)
##sequence-region NC_000913.3 1 4641652
##species https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145
##genome-sequence NC_000913.3 1 4641652
##genome-description Escherichia coli str. K-12 substr. MG1655, complete genome
##genome-filename EcoMG1655-NC_000913.3.fasta
#sgRNA-map crispin EcoMG1655-NC_000913.3.fasta EcoMG1655-NC_000913.3.gff3
#crosstalk-comparator 63
NC_000913.3 crispin protospacer 2400946 2400965 . + . ID=sgr-7a0a4f43;Name=nuoF-2400965-level_herman;ann_Name=nuoF;ann_end=2401555;ann_feature=gene;ann_gene=nuoF;ann_gene_biotype=protein_coding;ann_locus_tag=b2284;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=2400218;ann_strand=-;guide_context_down=TAGCACGACGTCCTTCCAGG;guide_context_up=CCATGCGCCGGAGGTTGCCG;guide_length=20;guide_re_sites=;guide_sequence=GGAAGGGTGGCTTCGAGCGT;guide_sequence_hash=6a359e86;mnemonic=level_herman;pam_end=2400969;pam_offset=0;pam_replichore=L;pam_search=NGGN;pam_sequence=GGGT;pam_start=2400965;source_name=GGAAGGGTGGCTTCGAGCGT
...
NC_000913.3 crispin protospacer 1764112 1764131 . + . ID=sgr-f3815635;Name=sufA-1764131-scarce_game;ann_Name=sufA;ann_end=1764386;ann_feature=gene;ann_gene=sufA;ann_gene_biotype=protein_coding;ann_locus_tag=b1684;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=1764018;ann_strand=-;guide_context_down=ATCGCTTGCAGCGGGACAAA;guide_context_up=GTCCTTCACGAACGAAATCG;guide_length=20;guide_re_sites=;guide_sequence=ACTTCCGTGCCATCAATAAA;guide_sequence_hash=dc4688e0;mnemonic=scarce_game;pam_end=1764135;pam_offset=0;pam_replichore=R;pam_search=NGGN;pam_sequence=CGGC;pam_start=1764131;source_name=ACTTCCGTGCCATCAATAAA
```
## Python API
Some classes and functions are exposed in an API for generating guide RNAs
in Python scripts.
Guides can be generated *de novo*.
```python
from crispio import GuideLibrary
genome = "ATATATATATATATATATATATATACCGTTTTTTTAAAAAAACGGATATATATATATAATATATATATATAATATATATATATA"
gl = GuideLibrary.from_generating(genome=genome)
for match_collection in gl:
for guide in match_collection:
print(guide)
```
The above code would return:
```
ATACCGTTTTTTTAAAAAAA
ATACCGTTTTTTTAAAAAAA
```
Or known guide sequences can be mapped to a genome.
```python
from crispio import GuideLibrary
genome = "CCCCCCCCCCCTTTTTTTTTTAAAAAAAAAATGATCGATCGATCGAGGAAAAAAAAAACCCCCCCCCCC"
guide_seq = "ATGATCGATCGATCG"
gl = GuideLibrary.from_mapping(guide_seq=guide_seq, genome=genome)
for collection in gl:
for match in collection:
print(match.as_dict())
```
This code would return:
```
{'pam_search': 'NGG', 'guide_seq': 'ATGATCGATCGATCG', 'pam_seq': 'AGG', 'pam_start': 45, 'reverse': False, 'guide_context_up': 'CTTTTTTTTTTAAAAAAAAA', 'guide_context_down': 'AAAAAAAAAACCCCCCCCCC', 'pam_end': 48, 'length': 15, 'guide_start': 30, 'guide_end': 45}
```
Check the full API in the [documentation](https://readthedocs.org/crispio).
## Issues, bugs, suggestions
Do not hesitate to add to our [issue tracker](https://github.com/scbirlab/crispio).
## Documentation
Check the documentation and full API [here](https://readthedocs.org/crispio).
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"description": "# \ud83c\udf31 crispio\n\n\n\n\n\nCommand-line utilities and Python API for designing CRISPRi experiments in bacteria.\n\n**crispio** makes it easy to design annotated and systematically named libraries of guide RNAs. \nAlternatively, **crispio** can map a FASTA of existing guides to a genome.\n\n**Hint**: If you have a table of guide RNAs from the literature that you want to annotate\nwith genomic features, **crispio** is your tool. Use [`bioino table2fasta`](https://github.com/scbirlab/bioino#command-line) \nto convert the table to a FASTA file, then use [`crispio map`](#mapping-known-guide-rnas-to-a-genome).\n\n- [Installation](#installation)\n- [Command-line interface](#command-line-interface)\n- [Generating new guide RNAs](#generating-new-guide-rnas)\n- [Mapping known guide RNAs to a genome](#mapping-known-guide-rnas-to-a-genome)\n- [Annotating with extra features](#annotating-with-extra-features)\n- [Checking for off-targets](#checking-for-off-targets)\n- [Python API](#python-api)\n- [Issues, bugs, suggestions]()\n- [Documentation]()\n\n## Installation\n\n### The easy way\n\nInstall the pre-compiled version from GitHub:\n\n```bash\n$ pip install crispio\n```\n\n### From source\n\nClone the repository, then `cd` into it. Then run:\n\n```bash\n$ pip install -e .\n```\n\n## Command-line interface\n\nThe main way to use **crispio** is with its several subcommands. You can get \nhelp by entering `crispio <subcommand> --help`.\n\n```bash\n$ crispio --help\nusage: crispio [-h] {generate,map,featurize,offtarget} ...\n\nDesign and analysis of bacterial CRISPRi experiments.\n\noptional arguments:\n -h, --help show this help message and exit\n\nSub-commands:\n {generate,map,featurize,offtarget}\n Use these commands to specify the tool you want to use.\n generate Generate and annotate all guide RNAs for a given genome.\n map Map and annotate provided guide RNAs to a given genome.\n featurize Annotate guide RNAs with additional calculated features.\n offtarget Compare two sets of guide RNAs for potential cross-target activity.\n```\n\n## Generating new guide RNAs\n\nGiven a genome in FASTA format and a matching GFF, \n[both available for your favourite bacterium from NCBI](https://www.ncbi.nlm.nih.gov/genbank/ftp/),\nalong with a PAM sequence or name of a common Cas9 ortholog, you can generate all the possible \nguide RNAs and annotate them from the GFF in one go.\n\nThe command `crisio generate` finds the position on the genome, annotates\nwith genomic features, replichore, and sequence context, detects restriction \nsites, and gives each guide RNA a unique ID and a human-readable\nadjective-noun mnemonic.\n\n```bash\n$ crispio generate -l 20 --pam Sth1 -g EcoMG1655-NC_000913.3.fasta -a EcoMG1655-NC_000913.3.gff3 | head\n\n\ud83d\ude80 Generating sgRNAs with the following parameters:\n ...\n\n##sequence-region NC_000913.3 1 4641652\n##species https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145\n##genome-sequence NC_000913.3 1 6930\n##genome-description Escherichia coli str. K-12 substr. MG1655, complete genome\n##genome-filename 63\n#sgRNA-map crispio 63 62\nNC_000913.3 crispio protospacer 2 21 . + . ID=sgr-e5373243;Name=thrL-21-modest_saddle;ann_Name=thrL;ann_end=255;ann_feature=gene;ann_gene=thrL;ann_gene_biotype=protein_coding;ann_locus_tag=_up-thrL;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=190;ann_strand=+;guide_context_down=TATGTCTCTGTGTGGATTAA;guide_context_up=CAGCACCCCAGGAACCCATA;guide_length=20;guide_re_sites=;guide_sequence=GCTTTTCATTCTGACTGCAA;guide_sequence_hash=19d8fdaa;mnemonic=modest_saddle;pam_end=28;pam_offset=-166;pam_replichore=R;pam_search=NNRGVAN;pam_sequence=CGGGCAA;pam_start=21;source_name=thrL-21-modest_saddle\n\n...\n\nNC_000913.3 crispio protospacer 180 199 . + . ID=sgr-b71e7fa7;Name=thrL-199-bouncy_sabine;ann_Name=thrL;ann_end=255;ann_feature=gene;ann_gene=thrL;ann_gene_biotype=protein_coding;ann_locus_tag=b0001;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=190;ann_strand=+;guide_context_down=CACCATTACCACCACCATCA;guide_context_up=CAGATAAAAATTACAGAGTA;guide_length=20;guide_re_sites=;guide_sequence=CACAACATCCATGAAACGCA;guide_sequence_hash=3e6eb3a0;mnemonic=bouncy_sabine;pam_end=206;pam_offset=65;pam_replichore=R;pam_search=NNRGVAN;pam_sequence=TTAGCAC;pam_start=199;source_name=thrL-199-bouncy_sabine\n\n```\n\nThe guides are output in GFF format, so it can be used directly as an annotation\ntrack in your favourite genome browser. \n\nIt can be dense for human beings to parse, so you can convert to a TSV using \n[`bioino ggf2table`](https://github.com/scbirlab/bioino#command-line):\n\n```bash\n$ head guides.gff | bioino gff2table\n...\n\nseqid source feature start end score strand phase ID Name ann_Name ann_end ann_feature ann_gene ann_gene_biotype ann_locus_tag ann_phase ann_score ann_seqid ann_source ann_start ann_strand guide_context_down guide_context_up guide_length guide_re_sites guide_sequence guide_sequence_hash mnemonic pam_end pam_offset pam_replichore pam_search pam_sequence pam_start source_name\nNC_000913.3 crispio protospacer 2 21 . + . sgr-e5373243 thrL-21-modest_saddle thrL 255 gene thrL protein_coding _up-thrL . . NC_000913.3 RefSeq 190 + TATGTCTCTGTGTGGATTAA CAGCACCCCAGGAACCCATA 20 GCTTTTCATTCTGACTGCAA 19d8fdaa modest_saddle 28 -166 R NNRGVAN CGGGCAA 21 thrL-21-modest_saddle\n\n...\n\nNC_000913.3 crispio protospacer 180 199 . + . sgr-b71e7fa7 thrL-199-bouncy_sabine thrL 255 gene thrL protein_coding b0001 . . NC_000913.3 RefSeq 190 + CACCATTACCACCACCATCA CAGATAAAAATTACAGAGTA 20 CACAACATCCATGAAACGCA 3e6eb3a0 bouncy_sabine 206 65 R NNRGVAN TTAGCAC 199 thrL-199-bouncy_sabine\n```\n\nAll the commands are pipeable. All the chatter goes to `stderr`, so\nyou can pipe your actual data through `stdout`.\n\n## Mapping known guide RNAs to a genome\n\nThe command `crispio map` is similar, but takes known guides in FASTA format as input. \n\n```bash\n$ crispio map cv-nar-2020_TableS1.fasta -g EcoMG1655-NC_000913.3.fasta -a EcoMG1655-NC_000913.3.gff3 --pam Spy\n\n\ud83d\ude80 Mapping sgRNAs with the following parameters:\n ...\nFinding sgRNA sites matching 21417 sequences from cv-nar-2020_TableS1.fasta and matching PAM Spy (NGGN) in EcoMG1655-NC_000913.3.fasta...\n\n##sequence-region NC_000913.3 1 4641652\n##species https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145\n##genome-sequence NC_000913.3 1 4641652\n##genome-description Escherichia coli str. K-12 substr. MG1655, complete genome\n##genome-filename EcoMG1655-NC_000913.3.fasta\n#sgRNA-map crispio EcoMG1655-NC_000913.3.fasta EcoMG1655-NC_000913.3.gff3\nNC_000913.3 crispio 2400946 2400965 . + . ID=sgr-7a0a4f43;Name=nuoF-2400965-level_herman;ann_Name=nuoF;ann_end=2401555;ann_feature=gene;ann_gene=nuoF;ann_gene_biotype=protein_coding;ann_locus_tag=b2284;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=2400218;ann_strand=-;guide_context_down=TAGCACGACGTCCTTCCAGG;guide_context_up=CCATGCGCCGGAGGTTGCCG;guide_length=20;guide_re_sites=;guide_sequence=GGAAGGGTGGCTTCGAGCGT;guide_sequence_hash=6a359e86;mnemonic=level_herman;pam_end=2400969;pam_offset=0;pam_replichore=L;pam_search=NGGN;pam_sequence=GGGT;pam_start=2400965;source_name=GGAAGGGTGGCTTCGAGCGT\n\n...\n\nNC_000913.3 crispio protospacer 2400933 2400952 . + . ID=sgr-32446b00;Name=nuoF-2400952-telling_austria;ann_Name=nuoF;ann_end=2401555;ann_feature=gene;ann_gene=nuoF;ann_gene_biotype=protein_coding;ann_locus_tag=b2284;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=2400218;ann_strand=-;guide_context_down=TTCGAGCGTGGGTTAGCACG;guide_context_up=AGGTCGGTTTACCCCATGCG;guide_length=20;guide_re_sites=;guide_sequence=CCGGAGGTTGCCGGGAAGGG;guide_sequence_hash=1908728f;mnemonic=telling_austria;pam_end=2400956;pam_offset=0;pam_replichore=L;pam_search=NGGN;pam_sequence=TGGC;pam_start=2400952;source_name=CCGGAGGTTGCCGGGAAGGG\n```\n\nIf you don't have a FASTA to hand, but a table instead, you can pipe it\nthrough [`bioino table2fasta`](https://github.com/scbirlab/bioino#command-line):\n\n```bash\n$ cat guide-table.tsv | bioino table2fasta -s sequence -n guide_name | crispio map -g EcoMG1655-NC_000913.3.fasta -a EcoMG1655-NC_000913.3.gff3 --pam Sth1 \n\n##sequence-region NC_000913.3 1 4641652\n##species https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145\n##genome-sequence NC_000913.3 1 4641652\n##genome-description Escherichia coli str. K-12 substr. MG1655, complete genome\n##genome-filename EcoMG1655-NC_000913.3.fasta\n#sgRNA-map crispio EcoMG1655-NC_000913.3.fasta EcoMG1655-NC_000913.3.gff3\nNC_000913.3 crispio protospacer 1236 1255 . + . ID=sgr-831073da;Name=thrA-1255-honest_brother;ann_Name=thrA;ann_end=2799;ann_feature=gene;ann_gene=thrA;ann_gene_biotype=protein_coding;ann_locus_tag=b0002;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=337;ann_strand=+;guide_context_down=TTCCAATCTGAATAACATGG;guide_context_up=CTCATTGGTGCCAGCCGTGA;guide_length=20;guide_re_sites=BbsI;guide_sequence=TGAAGACGAATTACCGGTCA;guide_sequence_hash=55934652;mnemonic=honest_brother;pam_end=1262;pam_offset=2462;pam_replichore=R;pam_search=NNRGVAN;pam_sequence=AGGGCAT;pam_start=1255;source_name=thrA-1255-honest_brother\n\n...\n\nNC_000913.3 crispio protospacer 3999 4018 . + . ID=sgr-83d65199;Name=thrC-4018-jolly_lunar;ann_Name=thrC;ann_end=5020;ann_feature=gene;ann_gene=thrC;ann_gene_biotype=protein_coding;ann_locus_tag=b0004;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=3734;ann_strand=+;guide_context_down=TGTTCCACGGGCCAACGCTG;guide_context_up=CCCGGCTCCGGTCGCCAATG;guide_length=20;guide_re_sites=BtgZI;guide_sequence=TTGAAAGCGATGTCGGTTGT;guide_sequence_hash=e539f903;mnemonic=jolly_lunar;pam_end=4025;pam_offset=1286;pam_replichore=R;pam_search=NNRGVAN;pam_sequence=CTGGAAT;pam_start=4018;source_name=thrC-4018-jolly_lunar\n```\n\n## Annotating with extra features\n\nIt may be useful to calcuate additional guide RNA features for downstream applications like\nmachine learning. These are the available extra features:\n\n```python\n>>> from crispio import *\n>>> get_features()\n['on_nontemplate_strand', 'context_up2', 'context_down2', 'context_up_autocorr', 'pam_n', 'pam_def', 'pam_gc', 'pam_autocorr', 'pam_scaff_corr', 'guide_purine', 'guide_gc', 'seed_seq', 'guide_start3', 'guide_end3', 'guide_autocorr', 'guide_scaff_corr']\n```\n\nUsing the command-line these can be easily added to a GFF or piped output \nfrom `crispio map` or `crispio generate`.\n\n```bash\n$ cat mapped-guides.gff | head | crispio featurize --scaffold Spy\n\n\ud83d\ude80 Featurizing sgRNAs with the following parameters:\n ...\n> Generating features for guides...\n##sequence-region NC_000913.3 1 4641652\n##species https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145\n##genome-sequence NC_000913.3 1 4641652\n##genome-description Escherichia coli str. K-12 substr. MG1655, complete genome\n##genome-filename EcoMG1655-NC_000913.3.fasta\n#sgRNA-map crispin EcoMG1655-NC_000913.3.fasta EcoMG1655-NC_000913.3.gff3\nNC_000913.3 crispin protospacer 2400946 2400965 . + . ID=sgr-7a0a4f43;Name=nuoF-2400965-level_herman;ann_Name=nuoF;ann_end=2401555;ann_feature=gene;ann_gene=nuoF;ann_gene_biotype=protein_coding;ann_locus_tag=b2284;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=2400218;ann_strand=-;guide_context_down=TAGCACGACGTCCTTCCAGG;guide_context_up=CCATGCGCCGGAGGTTGCCG;guide_length=20;guide_re_sites=;guide_sequence=GGAAGGGTGGCTTCGAGCGT;guide_sequence_hash=6a359e86;mnemonic=level_herman;pam_end=2400969;pam_offset=0;pam_replichore=L;pam_search=NGGN;pam_sequence=GGGT;pam_start=2400965;source_name=GGAAGGGTGGCTTCGAGCGT;feat_on_nontemplate_strand=True;feat_context_up2=CG;feat_context_down2=TA;feat_context_up_autocorr=8.928;feat_pam_n=G;feat_pam_def=GGT;feat_pam_gc=0.750;feat_pam_autocorr=2.167;feat_pam_scaff_corr=1.917;feat_guide_purine=0.650;feat_guide_gc=0.650;feat_seed_seq=AGCGT;feat_guide_start3=GGA;feat_guide_end3=CGT;feat_guide_autocorr=8.704;feat_guide_scaff_corr=9.772\n\n...\n\nNC_000913.3 crispin protospacer 1764112 1764131 . + . ID=sgr-f3815635;Name=sufA-1764131-scarce_game;ann_Name=sufA;ann_end=1764386;ann_feature=gene;ann_gene=sufA;ann_gene_biotype=protein_coding;ann_locus_tag=b1684;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=1764018;ann_strand=-;guide_context_down=ATCGCTTGCAGCGGGACAAA;guide_context_up=GTCCTTCACGAACGAAATCG;guide_length=20;guide_re_sites=;guide_sequence=ACTTCCGTGCCATCAATAAA;guide_sequence_hash=dc4688e0;mnemonic=scarce_game;pam_end=1764135;pam_offset=0;pam_replichore=R;pam_search=NGGN;pam_sequence=CGGC;pam_start=1764131;source_name=ACTTCCGTGCCATCAATAAA;feat_on_nontemplate_strand=True;feat_context_up2=CG;feat_context_down2=AT;feat_context_up_autocorr=7.159;feat_pam_n=C;feat_pam_def=GGC;feat_pam_gc=1.000;feat_pam_autocorr=2.333;feat_pam_scaff_corr=1.667;feat_guide_purine=0.450;feat_guide_gc=0.400;feat_seed_seq=ATAAA;feat_guide_start3=ACT;feat_guide_end3=AAA;feat_guide_autocorr=7.767;feat_guide_scaff_corr=10.528\n```\n\nThe attributes starting with `feat_` have been added.\n\n## Checking for off-targets\n\nOne downside of CRISPR-based tools is the possibility of off-target effects.\n`crispio offtarget` compares two GFF files, or one GFF file against itself, for \nguide RNA sites that share a seed sequence (4 PAM-proximal bases) and have a \nHamming distance of 4 or less.\n\n```bash\n$ cat mapped-guides.gff | head | crispio offtarget -2 <(cat mapped-guides.gff)\n\n##sequence-region NC_000913.3 1 4641652\n##species https://www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi?id=511145\n##genome-sequence NC_000913.3 1 4641652\n##genome-description Escherichia coli str. K-12 substr. MG1655, complete genome\n##genome-filename EcoMG1655-NC_000913.3.fasta\n#sgRNA-map crispin EcoMG1655-NC_000913.3.fasta EcoMG1655-NC_000913.3.gff3\n#crosstalk-comparator 63\nNC_000913.3 crispin protospacer 2400946 2400965 . + . ID=sgr-7a0a4f43;Name=nuoF-2400965-level_herman;ann_Name=nuoF;ann_end=2401555;ann_feature=gene;ann_gene=nuoF;ann_gene_biotype=protein_coding;ann_locus_tag=b2284;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=2400218;ann_strand=-;guide_context_down=TAGCACGACGTCCTTCCAGG;guide_context_up=CCATGCGCCGGAGGTTGCCG;guide_length=20;guide_re_sites=;guide_sequence=GGAAGGGTGGCTTCGAGCGT;guide_sequence_hash=6a359e86;mnemonic=level_herman;pam_end=2400969;pam_offset=0;pam_replichore=L;pam_search=NGGN;pam_sequence=GGGT;pam_start=2400965;source_name=GGAAGGGTGGCTTCGAGCGT\n\n...\n\nNC_000913.3 crispin protospacer 1764112 1764131 . + . ID=sgr-f3815635;Name=sufA-1764131-scarce_game;ann_Name=sufA;ann_end=1764386;ann_feature=gene;ann_gene=sufA;ann_gene_biotype=protein_coding;ann_locus_tag=b1684;ann_phase=.;ann_score=.;ann_seqid=NC_000913.3;ann_source=RefSeq;ann_start=1764018;ann_strand=-;guide_context_down=ATCGCTTGCAGCGGGACAAA;guide_context_up=GTCCTTCACGAACGAAATCG;guide_length=20;guide_re_sites=;guide_sequence=ACTTCCGTGCCATCAATAAA;guide_sequence_hash=dc4688e0;mnemonic=scarce_game;pam_end=1764135;pam_offset=0;pam_replichore=R;pam_search=NGGN;pam_sequence=CGGC;pam_start=1764131;source_name=ACTTCCGTGCCATCAATAAA\n```\n\n## Python API\n\nSome classes and functions are exposed in an API for generating guide RNAs \nin Python scripts.\n\nGuides can be generated *de novo*.\n\n```python \nfrom crispio import GuideLibrary\n\ngenome = \"ATATATATATATATATATATATATACCGTTTTTTTAAAAAAACGGATATATATATATAATATATATATATAATATATATATATA\"\ngl = GuideLibrary.from_generating(genome=genome) \nfor match_collection in gl:\n for guide in match_collection:\n print(guide)\n```\n\nThe above code would return:\n\n```\nATACCGTTTTTTTAAAAAAA\nATACCGTTTTTTTAAAAAAA\n```\n\nOr known guide sequences can be mapped to a genome. \n\n```python\nfrom crispio import GuideLibrary\n\ngenome = \"CCCCCCCCCCCTTTTTTTTTTAAAAAAAAAATGATCGATCGATCGAGGAAAAAAAAAACCCCCCCCCCC\"\nguide_seq = \"ATGATCGATCGATCG\"\ngl = GuideLibrary.from_mapping(guide_seq=guide_seq, genome=genome) \n\nfor collection in gl:\n for match in collection:\n print(match.as_dict())\n```\n\nThis code would return:\n\n```\n{'pam_search': 'NGG', 'guide_seq': 'ATGATCGATCGATCG', 'pam_seq': 'AGG', 'pam_start': 45, 'reverse': False, 'guide_context_up': 'CTTTTTTTTTTAAAAAAAAA', 'guide_context_down': 'AAAAAAAAAACCCCCCCCCC', 'pam_end': 48, 'length': 15, 'guide_start': 30, 'guide_end': 45}\n```\n\nCheck the full API in the [documentation](https://readthedocs.org/crispio).\n\n## Issues, bugs, suggestions\n\nDo not hesitate to add to our [issue tracker](https://github.com/scbirlab/crispio).\n\n## Documentation\n\nCheck the documentation and full API [here](https://readthedocs.org/crispio).\n",
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"license": "MIT License Copyright (c) [year] [fullname] Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.",
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