A web UI for optimised versions of the models published in Wang et al. 2023.
ChlamyAtlas expects input in either the FASTA format or as pure amino acid sequence. The FASTA format consists of two building blocks. The first is a description which explains the following sequence. This description starts with ">" and is written in a single line. The amino acid sequence follows in the next line and can span multiple lines. An example for this format is:
>sp|A0A178WF56|CSTM3_ARATH Protein CYSTEINE-RICH TRANSMEMBRANE MODULE 3 OS=Arabidopsis thaliana OX=3702 GN=CYSTM3 PE=1 SV=1
MAQYHQQHEMKQTMAETQYVTAPPPMGYPVMMKDSPQTVQPPHEGQSKGSGGFLRGCLAA
MCCCCVLDCVF
>sp|A1YKT1|TCP18_ARATH Transcription factor TCP18 OS=Arabidopsis thaliana OX=3702 GN=TCP18 PE=1 SV=1
MNNNIFSTTTTINDDYMLFPYNDHYSSQPLLPFSPSSSINDILIHSTSNTSNNHLDHHHQ
FQQPSPFSHFEFAPDCALLTSFHPENNGHDDNQTIPNDNHHPSLHFPLNNTIVEQPTEPS
ETINLIEDSQRISTSQDPKMKKAKKPSRTDRHSKIKTAKGTRDRRMRLSLDVAKELFGLQ
DMLGFDKASKTVEWLLTQAKPEIIKIATTLSHHGCFSSGDESHIRPVLGSMDTSSDLCEL
ASMWTVDDRGSNTNTTETRGNKVDGRSMRGKRKRPEPRTPILKKLSKEERAKARERAKGR
TMEKMMMKMKGRSQLVKVVEEDAHDHGEIIKNNNRSQVNRSSFEMTHCEDKIEELCKNDR
FAVCNEFIMNKKDHISNESYDLVNYKPNSSFPVINHHRSQGAANSIEQHQFTDLHYSFGA
KPRDLMHNYQNMY
ChlamyAtlas was developed with the assumption that the description follows the standard used by the Universal Protein Resource (Uniprot) and only returns the Uniprot ID as description in the output table. This can be circumvented by removing the "|" in the description. In this case the complete description gets returned.
The only other supported format are pure amino acid sequences. An example for this format is:
MAQYHQQHEMKQTMAETQYVTAPPPMGYPVMMKDSPQTVQPPHEGQSKGSGGFLRGCLAA
MCCCCVLDCVF
This format can only be used for a single amino acid sequence. Multiple amino acid sequences must be in the following format:
>!MAQYHQQHEMKQTMAETQYVTAPPPMGYPVMMKDSPQTVQPPHEGQSKGSGGFLRGCLAA
MCCCCVLDCVF
>!MNNNIFSTTTTINDDYMLFPYNDHYSSQPLLPFSPSSSINDILIHSTSNTSNNHLDHHHQ
FQQPSPFSHFEFAPDCALLTSFHPENNGHDDNQTIPNDNHHPSLHFPLNNTIVEQPTEPS
ETINLIEDSQRISTSQDPKMKKAKKPSRTDRHSKIKTAKGTRDRRMRLSLDVAKELFGLQ
DMLGFDKASKTVEWLLTQAKPEIIKIATTLSHHGCFSSGDESHIRPVLGSMDTSSDLCEL
ASMWTVDDRGSNTNTTETRGNKVDGRSMRGKRKRPEPRTPILKKLSKEERAKARERAKGR
TMEKMMMKMKGRSQLVKVVEEDAHDHGEIIKNNNRSQVNRSSFEMTHCEDKIEELCKNDR
FAVCNEFIMNKKDHISNESYDLVNYKPNSSFPVINHHRSQGAANSIEQHQFTDLHYSFGA
KPRDLMHNYQNMY
Explanations of Chloropred ,Qchloro, Mitopred,Qmito,Secrpred,Qsecr, and FinalPred.
Prediction score indicating the likelihood of the protein being localized to the Chloroplast. A higher scores suggest a stronger prediction that the protein is localized in the Chloroplast.
q-value associated with the Chloroplast prediction score. Provides a measure of statistical significance for the Chloroplast prediction. Lower q-values indicate higher statistical significance.
Prediction score for the localization of the protein to the Mitochondria. A higher scores suggest a stronger prediction of Mitochondrial localization.
q-value associated with the Mitochondria prediction score. Indicates the statistical significance of the Mitochondria localization prediction. Lower q-values suggest a more reliable prediction.
Prediction score for identifying the protein as a Secretory Protein.A higher scores indicate a stronger likelihood that the protein functions as a Secretory Protein.
q-value for the Secretory Protein prediction. Provides a measure of the statistical significance of the Secretory Protein prediction. Lower q-values are indicative of more statistically significant predictions.
Represents the model's final prediction of the protein's localization based on the highest score and its corresponding q-value. The final localization is determined by comparing the q-values and prediction scores against preset cutoffs. If all q-values exceed the cutoff, the protein is classified as "Cytoplasmic."
The threshold q-value below which a prediction is considered statistically significant. Set to 0.05 by default, meaning that predictions with q-values below this threshold are classified as significant. This parameter helps in distinguishing between statistically significant and non-significant predictions, reducing the chance of false-positive localizations.
-
NET_EMAIL_EMAIL: Email address to send emails from
Default: Set via user secrets
-
NET_EMAIL_ACCOUNTNAME: Email account name to send emails from
Default: Set via user secrets
-
NET_EMAIL_PASSWORD: Email account password to send emails from
Default: Set via user secrets
-
NET_EMAIL_SERVER: Email server to send emails from
Default: Set via user secrets
-
NET_EMAIL_PORT: Email server port to send emails from
Default: Set via user secrets
-
PYTHON_SERVICE_TIMEOUT: Time in minutes before conenction timeout between ui and api service
Default: 30 minutes
-
PYTHON_SERVICE_URL: Sets the url for the api predictor backend.
Default:
http://localhost:8000
Remarks: In docker compose this could be
http://host.docker.internal:8000
Remarks: On Linux might require:
extra_hosts: - "host.docker.internal:host-gateway"
-
PYTHON_SERVICE_STORAGE_TIMESPAN: How long the user data should be stored
Default: 1 Hour
version: '3.7'
name: chlamyatlas
services:
api:
image: csbdocker/chlamyatlas-api:latest
ports:
- 8000:80
environment:
GUNICORN_CMD_ARGS: "-k uvicorn.workers.UvicornWorker --preload"
MAX_WORKERS: "4"
TIMEOUT: "0"
ui:
image: csbdocker/chlamyatlas-ui:latest
environment:
PYTHON_SERVICE_URL: "http://host.docker.internal:8000"
PYTHON_SERVICE_STORAGE_TIMESPAN: "7"
ports:
- 5000:5000
# Use this to make host.docker.internal accessible on linux docker
extra_hosts:
- "host.docker.internal:host-gateway"
You'll need to install the following pre-requisites in order to build SAFE applications
- .NET SDK 8.0 or higher
- Node 18 or higher
- NPM 9 or higher
- Python 3.11 or higher
- run
setup.cmd
.. or ..
dotnet tool restore
py -m venv .venv
.\.venv\Scripts\python.exe -m pip install -r .\src\FastAPI\requirements.txt
.\build.cmd run
starts SAFE stack
plus in another terminal run:
- activate local python environment:
.\.venv\Scripts\Activate.ps1
- navigate to fastapi folder:
cd .\src\FastAPI\
- start fastapi backend:
./run.cmd
Set user-secrets in the following schema:
{
"email": {
"NET_EMAIL_EMAIL": "[email protected]",
"NET_EMAIL_ACCOUNTNAME": "PlaceholderAccountName",
"NET_EMAIL_PASSWORD": "HelloWorld1234",
"NET_EMAIL_SERVER": "smtp.placeholdermail.de",
"NET_EMAIL_PORT": 587
}
}
.\build.cmd dockerbundle [--uionly]
, creates:new
docker image(s). Skip fastapi image with--uionly
.\build.cmd dockertest
, uses local docker-compose file to start:new
images.
- Login to CSB-Docker
- Ensure correct Versions, both for python and dotnet service.
.\build.cmd versions
- Remarks: Versions are defined in project files. Paths can be found in build project
ProjectInfo.fs
. Accessed via regex parsing.
- Run
Test Publish
steps. The following step requires built:new
images. .\build.cmd dockerpublish
sequenceDiagram
participant py as Python ML
participant net as F#35; Server
participant c as Client
actor u as User
u -->> c: Gives data
c -->>+net: sends user data
par start analysis
loop
net-)+py: send sequence
py->py: predict target
py-)net: return predicted target
end
and return request information
net -) c: returns `request-ID`
end
critical ⚠️
u -->> c: copies and stores `request-ID`
end
opt email
u -->> c: give email address
c -->> net: give id + email to store
end
opt check status
u -->> c: use `request-ID` to check status
end
py-)net: send last package
deactivate py
net-->>net: run q-value calculation
net-->>net: store results
deactivate net
opt gave email
net-)u: send email
end
u -->> c: request data
c-->>net: get data
net-->>c: return data
c-->>u: download data