repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
scientific-agent-skills | skills/pkpd-modeling/scripts/ddi_static.py | .py | #!/usr/bin/env python3
"""Drug-drug interaction prediction: ICH M12 basic models and the mechanistic static model.
ICH M12 (Step 4, 2024) sets out a stepwise risk assessment: in vitro data feed
basic models whose cut-offs decide whether a clinical study is needed, and a
mechanistic static or PBPK model can be used to ... | 347 | 15,708 |
scientific-agent-skills | skills/pkpd-modeling/scripts/nca.py | .py | #!/usr/bin/env python3
"""Non-compartmental analysis of concentration-time data.
NCA looks arithmetically trivial and is not. Essentially every disagreement
between two NCA results traces to one of four choices that are rarely written
down: how lambda_z was selected, which trapezoidal rule was used, what happened
to B... | 588 | 23,289 |
scientific-agent-skills | skills/scanpy/scripts/score_genes.py | .py | #!/usr/bin/env python3
"""
Score cells for one or more gene signatures.
Computes ``sc.tl.score_genes`` for each named gene set in a JSON file and adds
one obs column per signature (``<name>_score``). Also supports the built-in
cell-cycle scoring with ``--cell-cycle``. Writes UMAPs colored by each score.
Gene-set JSON... | 83 | 3,743 |
scientific-agent-skills | skills/scanpy/scripts/pseudobulk.py | .py | #!/usr/bin/env python3
"""
Aggregate single cells into pseudobulk profiles for rigorous DE.
Sums raw counts within each combination of grouping columns (e.g. sample x
cell_type) using ``sc.get.aggregate`` and exports a genes x pseudobulk-sample
count matrix plus a sample-metadata table. Feed these into pydeseq2 / edge... | 75 | 2,972 |
scientific-agent-skills | skills/scanpy/scripts/preprocess.py | .py | #!/usr/bin/env python3
"""
Normalize, log-transform, select highly variable genes, and optionally scale.
Takes QC-filtered raw counts and produces a normalized, log1p-transformed
object ready for dimensionality reduction. A copy of the raw counts is kept in
``adata.layers['counts']`` and the normalized log values in `... | 89 | 3,801 |
scientific-agent-skills | skills/scanpy/scripts/reduce_dimensions.py | .py | #!/usr/bin/env python3
"""
PCA, neighborhood graph, and UMAP / t-SNE embeddings.
Takes a normalized object (optionally HVG-subset / scaled) and computes PCA,
the kNN graph, and a UMAP (and optionally t-SNE) embedding. Writes a PCA
variance-ratio elbow plot to help choose ``--n-pcs``.
Examples:
python reduce_dimen... | 65 | 2,684 |
scientific-agent-skills | skills/scanpy/scripts/plot.py | .py | #!/usr/bin/env python3
"""
Generate common single-cell plots from a processed AnnData object.
A flexible plotting front-end so the agent doesn't hand-write matplotlib /
scanpy plotting calls. Pick a plot type and the keys/genes to show.
Plot types:
umap / tsne / pca : embedding colored by --color obs columns and/... | 79 | 3,595 |
scientific-agent-skills | skills/scanpy/scripts/cluster.py | .py | #!/usr/bin/env python3
"""
Leiden clustering on a precomputed neighborhood graph.
Runs Leiden at one or more resolutions and writes a UMAP colored by each
clustering. Requires that ``sc.pp.neighbors`` has already been run
(use reduce_dimensions.py first).
Examples:
python cluster.py reduced.h5ad -o clustered.h5ad... | 64 | 2,523 |
scientific-agent-skills | skills/scanpy/scripts/convert.py | .py | #!/usr/bin/env python3
"""
Load any supported single-cell format and write it as .h5ad.
Convenience wrapper to get 10x mtx folders, 10x .h5, CSV/TSV, loom, or mtx
files into AnnData .h5ad once, so later steps all read a single fast format.
For R-native files (.rds / Seurat / SingleCellExperiment), see
references/r_int... | 44 | 1,514 |
scientific-agent-skills | skills/scanpy/scripts/batch_correct.py | .py | #!/usr/bin/env python3
"""
Batch correction / integration across samples.
Supports three methods:
* harmony : corrects the PCA embedding -> writes obsm['X_pca_harmony'].
Fast, recommended default. Needs harmonypy (uv pip install harmonypy).
Follow with: reduce_dimensions.py --use-rep X... | 66 | 2,745 |
scientific-agent-skills | skills/scanpy/scripts/_common.py | .py | #!/usr/bin/env python3
"""
Shared helpers for the scanpy script toolkit.
Every CLI script in this directory imports from this module so that data
loading, saving, figure configuration, and logging behave consistently.
This file is NOT a CLI itself; import it:
from _common import load_anndata, save_anndata, config... | 128 | 4,459 |
scientific-agent-skills | skills/scanpy/scripts/qc_analysis.py | .py | #!/usr/bin/env python3
"""
Quality control and filtering for single-cell RNA-seq data.
Calculates QC metrics (genes/counts per cell, mitochondrial / ribosomal /
hemoglobin fractions), writes before/after QC plots, optionally runs Scrublet
doublet detection, and filters cells and genes by the given thresholds.
Run thi... | 105 | 4,645 |
scientific-agent-skills | skills/scanpy/scripts/subset.py | .py | #!/usr/bin/env python3
"""
Subset an AnnData object by cell metadata or genes.
Filter cells by obs-column values (keep or drop), or restrict to a gene list.
Useful for isolating a cell type / condition for focused re-analysis.
Examples:
python subset.py annotated.h5ad -o tcells.h5ad --obs cell_type --keep "CD4 T ... | 65 | 2,533 |
scientific-agent-skills | skills/scanpy/scripts/find_markers.py | .py | #!/usr/bin/env python3
"""
Rank marker genes per group and export tables + plots.
Runs ``sc.tl.rank_genes_groups`` for a grouping (e.g. leiden clusters), writes
a combined CSV of the top markers per group, per-group CSVs, and the standard
marker plots (rank panel, heatmap, dotplot).
NOTE: per-cell tests inflate signi... | 76 | 3,445 |
scientific-agent-skills | skills/scanpy/scripts/inspect_data.py | .py | #!/usr/bin/env python3
"""
Inspect an AnnData / single-cell file and print a structured summary.
Reports shape, obs/var columns (with dtypes and category counts), layers,
obsm/varm/uns keys, X dtype and value range, and whether the data looks like
raw counts or normalized values. Use this before analysis to understand... | 82 | 2,886 |
scientific-agent-skills | skills/scanpy/scripts/run_pipeline.py | .py | #!/usr/bin/env python3
"""
End-to-end standard scRNA-seq pipeline in one command.
Runs the full exploratory workflow on raw counts:
load -> QC + filter -> (optional doublets) -> normalize + log1p -> HVG
-> (optional scale/regress) -> PCA -> (optional batch correction)
-> neighbors -> UMAP -> Leiden -> mark... | 183 | 8,112 |
scientific-agent-skills | skills/scanpy/scripts/annotate.py | .py | #!/usr/bin/env python3
"""
Annotate clusters with cell-type labels from a mapping file.
Maps a cluster column (e.g. leiden) to cell-type names using a JSON or CSV
mapping, writes the labels into a new obs column, and saves a UMAP and dotplot.
The mapping file is one of:
* JSON : {"0": "CD4 T cells", "1": "B cells"... | 85 | 3,604 |
scientific-agent-skills | skills/scanpy/assets/analysis_template.py | .py | #!/usr/bin/env python3
"""
Complete Single-Cell Analysis Template
This template provides a complete workflow for single-cell RNA-seq analysis
using scanpy, from data loading through clustering and cell type annotation.
Customize the parameters and sections as needed for your specific dataset.
"""
import scanpy as sc... | 302 | 9,806 |
scientific-agent-skills | skills/deeptools/scripts/validate_files.py | .py | #!/usr/bin/env python3
"""
deepTools File Validation Script
Validates BAM, bigWig, and BED files for deepTools analysis.
Checks for file existence, proper indexing, and basic format requirements.
"""
import os
import sys
import argparse
from pathlib import Path
def check_file_exists(filepath):
"""Check if file ... | 196 | 6,039 |
scientific-agent-skills | skills/deeptools/scripts/workflow_generator.py | .py | #!/usr/bin/env python3
"""
deepTools Workflow Generator
Generates bash script templates for common deepTools workflows.
"""
import argparse
import re
import shlex
import sys
SAFE_PATH_PATTERN = re.compile(r"^[A-Za-z0-9._/-]+$")
WORKFLOWS = {
'chipseq_qc': {
'name': 'ChIP-seq Quality Control',
... | 521 | 16,868 |
scientific-agent-skills | skills/matplotlib/scripts/plot_template.py | .py | #!/usr/bin/env python3
"""
Matplotlib Plot Template
Comprehensive template demonstrating various plot types and best practices.
Use this as a starting point for creating publication-quality visualizations.
Usage:
python plot_template.py [--plot-type TYPE] [--style STYLE] [--output FILE]
Plot types:
line, sca... | 407 | 12,257 |
scientific-agent-skills | skills/matplotlib/scripts/style_configurator.py | .py | #!/usr/bin/env python3
"""
Matplotlib Style Configurator
Interactive utility to configure matplotlib style preferences and generate
custom style sheets. Creates a preview of the style and optionally saves
it as a .mplstyle file.
Usage:
python style_configurator.py [--preset PRESET] [--output FILE] [--preview]
Pr... | 413 | 13,368 |
scientific-agent-skills | skills/experimental-design/scripts/randomization.py | .py | """Reproducible randomization / allocation schedules for experiments and trials.
Randomization is what licenses causal inference: it breaks the link between
treatment assignment and any confounder, measured or not. But "I shuffled it"
is not enough — the *method* matters (simple vs. blocked vs. stratified) and the
sch... | 172 | 7,046 |
scientific-agent-skills | skills/experimental-design/scripts/doe_designs.py | .py | """Design-of-experiments (DOE) matrices as labeled, decoded pandas DataFrames.
pyDOE3 returns designs in *coded* units (-1/+1, or 0..k-1). Researchers want the
design in *real* factor units (temperature in C, concentration in mM) with named
columns, randomized run order, and a clear sense of what each design is for. T... | 184 | 7,812 |
scientific-agent-skills | skills/hypothesis-generation/scripts/lint_causal_claims.py | .py | #!/usr/bin/env python3
"""Lexically lint causal versus associational claims in bounded Markdown."""
from __future__ import annotations
import argparse
import re
from collections import Counter
from typing import Any
from _common import (
ValidationError,
error_exit,
issue,
read_markdown,
write_js... | 190 | 6,809 |
scientific-agent-skills | skills/hypothesis-generation/scripts/_common.py | .py | #!/usr/bin/env python3
"""Shared, dependency-free safety helpers for local hypothesis CLIs."""
from __future__ import annotations
import csv
import json
import os
import re
import sys
import tempfile
from datetime import date
from pathlib import Path
from typing import Any, Iterable
MAX_INPUT_BYTES = 2 * 1024 * 1024... | 413 | 14,234 |
scientific-agent-skills | skills/hypothesis-generation/scripts/check_falsification_controls.py | .py | #!/usr/bin/env python3
"""Audit falsifiers, discriminating tests, nulls, and controls without scoring."""
from __future__ import annotations
import argparse
import re
from collections import Counter
from typing import Any
from _common import (
ValidationError,
error_exit,
issue,
read_json,
requir... | 456 | 16,477 |
scientific-agent-skills | skills/hypothesis-generation/scripts/generate_preregistration_scaffold.py | .py | #!/usr/bin/env python3
"""Generate a deterministic local Markdown preregistration scaffold."""
from __future__ import annotations
import argparse
import html
import re
from pathlib import Path
from typing import Any
from _common import (
ValidationError,
error_exit,
read_json,
read_markdown,
writ... | 385 | 14,349 |
scientific-agent-skills | skills/hypothesis-generation/scripts/validate_hypothesis_schema.py | .py | #!/usr/bin/env python3
"""Validate a structured hypothesis record without judging scientific merit."""
from __future__ import annotations
import argparse
from collections import Counter
from pathlib import PurePosixPath
from typing import Any
from _common import (
ValidationError,
error_exit,
issue,
... | 1,079 | 38,955 |
scientific-agent-skills | skills/hypothesis-generation/scripts/audit_evidence_ledger.py | .py | #!/usr/bin/env python3
"""Audit a local evidence ledger and dated search boundary without networking."""
from __future__ import annotations
import argparse
from collections import Counter
from datetime import date
from typing import Any
from _common import (
ValidationError,
error_exit,
issue,
read_c... | 338 | 12,069 |
scientific-agent-skills | skills/hypothesis-generation/scripts/check_operationalization.py | .py | #!/usr/bin/env python3
"""Audit a local operationalization and measurement checklist without scoring."""
from __future__ import annotations
import argparse
from collections import Counter
from typing import Any
from _common import (
ValidationError,
error_exit,
issue,
read_json,
require_bool,
... | 238 | 8,086 |
scientific-agent-skills | skills/hypothesis-generation/scripts/validate_prediction_matrix.py | .py | #!/usr/bin/env python3
"""Validate a prediction/rival-hypothesis CSV without ranking candidates."""
from __future__ import annotations
import argparse
import re
from collections import Counter
from typing import Any
from _common import (
ValidationError,
error_exit,
issue,
read_csv_records,
read_... | 287 | 9,815 |
scientific-agent-skills | skills/pylabrobot/scripts/inspect_backends.py | .py | #!/usr/bin/env python3
"""Inspect a pinned PyLabRobot API surface without constructing a backend."""
from __future__ import annotations
import argparse
import inspect
import re
from importlib.metadata import PackageNotFoundError, metadata, version
from typing import Any, Sequence
if __package__:
from ._common impo... | 217 | 7,041 |
scientific-agent-skills | skills/pylabrobot/scripts/validate_manifest.py | .py | #!/usr/bin/env python3
"""Validate a strict offline PyLabRobot protocol manifest."""
from __future__ import annotations
import argparse
from typing import Sequence
if __package__:
from ._common import ValidationError, emit_error, emit_json, load_json, validate_manifest
else:
from _common import ValidationError, ... | 48 | 1,391 |
scientific-agent-skills | skills/pylabrobot/scripts/check_deck_geometry.py | .py | #!/usr/bin/env python3
"""Check bounded static deck geometry without importing PyLabRobot."""
from __future__ import annotations
import argparse
from typing import Sequence
if __package__:
from ._common import (
ValidationError,
emit_error,
emit_json,
geometry_report,
load_json,
... | 53 | 1,301 |
scientific-agent-skills | skills/pylabrobot/scripts/plan_transfers.py | .py | #!/usr/bin/env python3
"""Plan a deterministic volume ledger and one-use tip allocation."""
from __future__ import annotations
import argparse
from typing import Sequence
if __package__:
from ._common import (
ValidationError,
emit_error,
emit_json,
load_csv,
load_json,
plan_tra... | 60 | 1,556 |
scientific-agent-skills | skills/pylabrobot/scripts/generate_simulation_plan.py | .py | #!/usr/bin/env python3
"""Generate a non-executable, hardware-blocked simulation plan as JSON."""
from __future__ import annotations
import argparse
from typing import Any, Sequence
if __package__:
from ._common import (
PYLABROBOT_VERSION,
ValidationError,
emit_error,
emit_json,
geom... | 141 | 4,793 |
scientific-agent-skills | skills/pylabrobot/scripts/_common.py | .py | """Dependency-free validation and planning helpers for the PyLabRobot skill.
These helpers never import PyLabRobot, open sockets, enumerate hardware, or access
serial/USB devices. All file inputs are bounded, local to the current working
directory, regular files, and non-symlinks.
"""
from __future__ import annotatio... | 719 | 26,669 |
scientific-agent-skills | skills/bioservices/scripts/compound_cross_reference.py | .py | #!/usr/bin/env python3
"""
Compound Cross-Database Search
This script searches for a compound by name and retrieves identifiers
from multiple databases:
- KEGG Compound
- ChEBI
- ChEMBL (via UniChem)
- Basic compound properties
Usage:
python compound_cross_reference.py COMPOUND_NAME [--output FILE]
Examples:
... | 388 | 11,779 |
scientific-agent-skills | skills/bioservices/scripts/protein_analysis_workflow.py | .py | #!/usr/bin/env python3
"""
Complete Protein Analysis Workflow
This script performs a comprehensive protein analysis pipeline:
1. UniProt search and identifier retrieval
2. FASTA sequence retrieval
3. BLAST similarity search
4. KEGG pathway discovery
5. PSICQUIC interaction mapping
6. GO annotation retrieval
Usage:
... | 442 | 13,467 |
scientific-agent-skills | skills/bioservices/scripts/batch_id_converter.py | .py | #!/usr/bin/env python3
"""
Batch Identifier Converter
This script converts multiple identifiers between biological databases
using UniProt's mapping service. Supports batch processing with
automatic chunking and error handling.
Usage:
python batch_id_converter.py INPUT_FILE --from DB1 --to DB2 [options]
Examples... | 348 | 10,892 |
scientific-agent-skills | skills/bioservices/scripts/pathway_analysis.py | .py | #!/usr/bin/env python3
"""
KEGG Pathway Network Analysis
This script analyzes all pathways for an organism and extracts:
- Pathway sizes (number of genes)
- Protein-protein interactions
- Interaction type distributions
- Network data in various formats (CSV, SIF)
Usage:
python pathway_analysis.py ORGANISM OUTPUT_... | 310 | 9,547 |
scientific-agent-skills | skills/protocolsio-integration/scripts/protocols_read.py | .py | #!/usr/bin/env python3
"""Bounded, read-only protocols.io REST client with an explicit execute gate."""
from __future__ import annotations
import argparse
import os
import re
from typing import Any, Mapping, Sequence
try:
from ._common import (
ACCESS_TOKEN_ENV,
DEFAULT_ORIGIN,
MAX_JSON_R... | 494 | 15,573 |
scientific-agent-skills | skills/protocolsio-integration/scripts/_common.py | .py | """Shared safety primitives for the protocols.io helper scripts.
The helpers use only the Python standard library. They never load ``.env``
files, never accept credentials as command-line arguments, and never follow
HTTP redirects.
"""
from __future__ import annotations
import json
import math
import os
import re
im... | 614 | 20,219 |
scientific-agent-skills | skills/protocolsio-integration/scripts/pagination_helper.py | .py | #!/usr/bin/env python3
"""Validate protocols.io pagination pointers without making requests."""
from __future__ import annotations
import argparse
import re
import urllib.parse
from typing import Any, Mapping, Sequence
try:
from ._common import (
SafetyError,
emit_error,
emit_json,
... | 249 | 7,665 |
scientific-agent-skills | skills/protocolsio-integration/scripts/validate_protocol_json.py | .py | #!/usr/bin/env python3
"""Validate and summarize a saved protocols.io protocol response offline."""
from __future__ import annotations
import argparse
import re
from typing import Any, Mapping, Sequence
try:
from ._common import (
SafetyError,
clean_text,
emit_error,
emit_json,
... | 359 | 12,311 |
scientific-agent-skills | skills/protocolsio-integration/scripts/validate_auth_config.py | .py | #!/usr/bin/env python3
"""Validate named protocols.io credential/configuration variables locally."""
from __future__ import annotations
import argparse
import os
from typing import Mapping, Sequence
try:
from ._common import (
ACCESS_TOKEN_ENV,
DEFAULT_ORIGIN,
SafetyError,
credent... | 129 | 3,529 |
scientific-agent-skills | skills/protocolsio-integration/scripts/plan_write_request.py | .py | #!/usr/bin/env python3
"""Create redacted protocols.io mutation plans; never execute them."""
from __future__ import annotations
import argparse
import hashlib
import hmac
import re
from pathlib import Path
from typing import Any, Mapping, Sequence
try:
from ._common import (
DEFAULT_ORIGIN,
Safe... | 658 | 21,735 |
scientific-agent-skills | skills/scikit-survival/scripts/model_report.py | .py | #!/usr/bin/env python3
"""Render a bounded Markdown model card from local aggregate JSON summaries."""
from __future__ import annotations
import argparse
import math
from typing import Any
from _common import CliError, emit_text, load_json
COMPETING_RISK_CHOICES = ("not-assessed", "absent", "present")
def _mappi... | 298 | 11,156 |
scientific-agent-skills | skills/scikit-survival/scripts/train_survival_model.py | .py | #!/usr/bin/env python3
"""Train a leakage-safe Cox or ensemble example on explicit local schema."""
from __future__ import annotations
import argparse
from importlib.metadata import version
from typing import Any
from _common import (
DEFAULT_SEED,
MAX_FEATURES,
CliError,
atomic_save_npz,
bounded... | 584 | 19,335 |
scientific-agent-skills | skills/scikit-survival/scripts/_common.py | .py | #!/usr/bin/env python3
"""Shared, standard-library-first helpers for the bundled survival CLIs."""
from __future__ import annotations
import io
import json
import math
import os
import stat
import tempfile
from pathlib import Path
from typing import Any, Iterable
MAX_INPUT_BYTES = 32 * 1024 * 1024
MAX_REPORT_BYTES ... | 457 | 15,360 |
scientific-agent-skills | skills/scikit-survival/scripts/competing_risk_cif.py | .py | #!/usr/bin/env python3
"""Estimate nonparametric competing-risk cumulative incidence from local data."""
from __future__ import annotations
import argparse
from typing import Any
from _common import (
DEFAULT_SEED,
CliError,
atomic_save_npz,
bounded_int,
emit_json,
parse_floats,
probabili... | 287 | 10,334 |
scientific-agent-skills | skills/scikit-survival/scripts/validate_survival_csv.py | .py | #!/usr/bin/env python3
"""Validate a local survival CSV and optionally write a structured NumPy array."""
from __future__ import annotations
import argparse
from typing import Any
from _common import (
DEFAULT_SEED,
MAX_FEATURES,
CliError,
atomic_save_npy,
bounded_int,
emit_json,
parse_na... | 173 | 5,721 |
scientific-agent-skills | skills/scikit-survival/scripts/evaluate_survival_metrics.py | .py | #!/usr/bin/env python3
"""Evaluate censoring-aware survival metrics with strict input contracts."""
from __future__ import annotations
import argparse
from typing import Any
from _common import (
DEFAULT_SEED,
MAX_TIME_POINTS,
CliError,
bounded_int,
checked_input_file,
emit_json,
structur... | 297 | 10,672 |
scientific-agent-skills | skills/openpiv/scripts/run_example.py | .py | """End-to-end smoke test of the OpenPIV pipeline on OpenPIV's own bundled data.
Runs the full runner.py pipeline against the exp1_001 image pair that ships inside the
openpiv package, so it needs no external files. Use it to confirm an install works
before pointing the CLI at real experiment data.
python skills/o... | 79 | 2,875 |
scientific-agent-skills | skills/openpiv/scripts/analyze.py | .py | """Post-processing helpers for a params.npz written by runner.py.
Verified against openpiv 0.25.4. Pure numpy -- no OpenPIV import needed here.
"""
from pathlib import Path
from typing import Dict, Optional, Tuple
import numpy as np
class PIVAnalyzer:
"""Derived quantities from a saved PIV velocity field.
... | 144 | 5,628 |
scientific-agent-skills | skills/openpiv/scripts/runner.py | .py | """CLI for OpenPIV processing of a single image pair.
Verified against openpiv 0.25.4. Writes vectors.txt, params.npz, and vector_field.png
into the output directory.
"""
import argparse
import warnings
from pathlib import Path
import matplotlib
# openpiv.tools.display_vector_field() calls plt.show() internally, so... | 215 | 6,848 |
scientific-agent-skills | skills/flowio/scripts/inspect_fcs.py | .py | #!/usr/bin/env python3
"""Inspect local FCS files with FlowIO without network or environment access.
Metadata-only parsing is the default. Event statistics are opt-in because
FlowIO loads each dataset into memory and ``as_array`` allocates another array.
Statistics first perform a metadata-only pass so an estimated ar... | 440 | 13,735 |
scientific-agent-skills | skills/clinical-decision-support/scripts/cohort_table_generator.py | .py | #!/usr/bin/env python3
"""Generate disclosure-controlled tables from bounded aggregate cohort summaries."""
from __future__ import annotations
import argparse
import csv
import io
import sys
from typing import Any
from _common import (
InputError,
IssueLog,
load_json_object,
nonnegative_int,
requ... | 289 | 11,390 |
scientific-agent-skills | skills/clinical-decision-support/scripts/decision_logic_traceability.py | .py | #!/usr/bin/env python3
"""Validate and export research/governance decision-logic traceability."""
from __future__ import annotations
import argparse
import csv
import io
import re
import sys
from typing import Any
from _common import (
InputError,
IssueLog,
load_json_object,
require_list,
require... | 314 | 10,929 |
scientific-agent-skills | skills/clinical-decision-support/scripts/survival_plan_validator.py | .py | #!/usr/bin/env python3
"""Validate an estimand-led survival-analysis plan without reading subject rows."""
from __future__ import annotations
import argparse
import sys
from typing import Any
from _common import (
InputError,
IssueLog,
load_json_object,
print_report,
require_list,
require_non... | 295 | 11,149 |
scientific-agent-skills | skills/clinical-decision-support/scripts/evidence_profile_check.py | .py | #!/usr/bin/env python3
"""Check a human-authored GRADE evidence profile without assigning grades."""
from __future__ import annotations
import argparse
import sys
from typing import Any
from _common import (
InputError,
IssueLog,
load_json_object,
print_report,
require_list,
require_nonempty_... | 260 | 10,534 |
scientific-agent-skills | skills/clinical-decision-support/scripts/validate_cds_artifact.py | .py | #!/usr/bin/env python3
"""Validate intended use and governance fields for research-only CDS artifacts."""
from __future__ import annotations
import argparse
import sys
from typing import Any
from _common import (
InputError,
IssueLog,
load_json_object,
print_report,
require_list,
require_none... | 270 | 10,029 |
scientific-agent-skills | skills/clinical-decision-support/scripts/_common.py | .py | #!/usr/bin/env python3
"""Shared bounded local-file utilities for research-only CDS helpers."""
from __future__ import annotations
import json
import math
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Iterable
MAX_INPUT_BYTES = 1_000_000
MAX_TEXT_LENGTH = 4_000
MAX_SOURCES... | 224 | 7,537 |
scientific-agent-skills | skills/clinical-decision-support/scripts/deidentification_checklist.py | .py | #!/usr/bin/env python3
"""Check documentation of a de-identification process without reading health data."""
from __future__ import annotations
import argparse
import sys
from typing import Any
from _common import (
InputError,
IssueLog,
load_json_object,
print_report,
require_list,
require_n... | 261 | 10,034 |
scientific-agent-skills | skills/clinical-decision-support/scripts/model_biomarker_evaluation.py | .py | #!/usr/bin/env python3
"""Create a bounded report from aggregate model/biomarker validation counts."""
from __future__ import annotations
import argparse
import math
import sys
from typing import Any
from _common import (
InputError,
IssueLog,
finite_number,
load_json_object,
nonnegative_int,
... | 346 | 13,691 |
scientific-agent-skills | skills/statistical-analysis/scripts/assumption_checks.py | .py | """
Comprehensive statistical assumption checking utilities.
This module provides functions to check common statistical assumptions:
- Normality
- Homogeneity of variance
- Independence
- Linearity
- Outliers
"""
import numpy as np
import pandas as pd
from scipy import stats
import matplotlib.pyplot as plt
import sea... | 653 | 20,282 |
scientific-agent-skills | skills/gtars/scripts/coverage_preflight.py | .py | #!/usr/bin/env python3
"""Preflight local Gtars uniwig coverage and bigWig generation."""
from __future__ import annotations
import argparse
import math
import sys
from _common import (
HARD_MAX_BYTES,
HARD_MAX_RECORDS,
HARD_MAX_WORKERS,
SafetyError,
add_path_mode_argument,
display_path,
... | 257 | 8,273 |
scientific-agent-skills | skills/gtars/scripts/bed_validator.py | .py | #!/usr/bin/env python3
"""Validate a local BED file without rewriting or uploading it."""
from __future__ import annotations
import argparse
import sys
from _common import (
HARD_MAX_BYTES,
HARD_MAX_RECORDS,
SafetyError,
add_path_mode_argument,
display_path,
fail_json,
inspect_bed,
in... | 184 | 5,432 |
scientific-agent-skills | skills/gtars/scripts/tokenizer_manifest.py | .py | #!/usr/bin/env python3
"""Check a local Gtars tokenizer manifest against its exact universe."""
from __future__ import annotations
import argparse
import re
import sys
from _common import (
HARD_MAX_BYTES,
HARD_MAX_RECORDS,
SafetyError,
add_path_mode_argument,
display_path,
fail_json,
ins... | 239 | 8,558 |
scientific-agent-skills | skills/gtars/scripts/_common.py | .py | #!/usr/bin/env python3
"""Shared dependency-free safety helpers for local Gtars skill CLIs."""
from __future__ import annotations
import argparse
import gzip
import hashlib
import json
import os
import re
import stat
import sys
from collections import Counter
from pathlib import Path
from typing import Any, Iterator
... | 462 | 14,970 |
scientific-agent-skills | skills/gtars/scripts/artifact_inspector.py | .py | #!/usr/bin/env python3
"""Hash and classify local Gtars artifacts without loading or executing them."""
from __future__ import annotations
import argparse
import os
import re
import stat
import sys
from email.parser import Parser
from pathlib import Path
from _common import (
HARD_MAX_BYTES,
HARD_MAX_FILES,
... | 329 | 10,846 |
scientific-agent-skills | skills/gtars/scripts/execution_plan.py | .py | #!/usr/bin/env python3
"""Build a bounded local Gtars overlap/coverage execution plan."""
from __future__ import annotations
import argparse
import sys
from pathlib import Path
from _common import (
HARD_MAX_BYTES,
HARD_MAX_RECORDS,
HARD_MAX_WORKERS,
SafetyError,
add_path_mode_argument,
displ... | 366 | 11,927 |
scientific-agent-skills | skills/gtars/scripts/refget_digest_plan.py | .py | #!/usr/bin/env python3
"""Validate local refget metadata and FASTA sequence digests without networking."""
from __future__ import annotations
import argparse
import base64
import hashlib
import re
import sys
from pathlib import Path
from _common import (
HARD_MAX_BYTES,
HARD_MAX_RECORDS,
SafetyError,
... | 312 | 10,925 |
scientific-agent-skills | skills/pydeseq2/scripts/run_deseq2_analysis.py | .py | #!/usr/bin/env python3
"""
PyDESeq2 Analysis Script
This script performs a complete differential expression analysis using PyDESeq2.
It can be used as a template for standard RNA-seq DEA workflows.
Usage:
python run_deseq2_analysis.py --counts counts.csv --metadata metadata.csv \
--design "~condition" ... | 389 | 13,074 |
scientific-agent-skills | skills/geopandas/scripts/crs_reprojection_plan.py | .py | #!/usr/bin/env python3
"""Plan CRS and datum transformation semantics without transforming coordinates."""
from __future__ import annotations
import argparse
import sys
from typing import Any
from _common import (
CliError,
crs_summary,
disable_proj_network,
emit_json,
fail_json,
finite_numbe... | 211 | 7,420 |
scientific-agent-skills | skills/geopandas/scripts/_common.py | .py | """Shared local-only safety and reporting helpers for GeoPandas CLIs."""
from __future__ import annotations
import hashlib
import json
import math
import os
import re
import tempfile
from importlib.metadata import PackageNotFoundError, version
from pathlib import Path
from typing import Any
PINNED_STACK = {
"geo... | 606 | 21,323 |
scientific-agent-skills | skills/geopandas/scripts/geometry_validity_report.py | .py | #!/usr/bin/env python3
"""Audit and simulate repair of bounded local geometries with optional new output."""
from __future__ import annotations
import argparse
import hashlib
import sys
from typing import Any
from _common import (
DEFAULT_MAX_FEATURES,
DEFAULT_MAX_INPUT_BYTES,
DEFAULT_MAX_OUTPUT_BYTES,
... | 228 | 7,436 |
scientific-agent-skills | skills/geopandas/scripts/sensitive_coordinates_checklist.py | .py | #!/usr/bin/env python3
"""Produce a deterministic privacy/generalization checklist without reading data."""
from __future__ import annotations
import argparse
import sys
from _common import CliError, emit_json, fail_json, finite_number, positive_int
TOOL = "sensitive_coordinates_checklist"
SENSITIVE_FLAGS = (
"... | 231 | 8,980 |
scientific-agent-skills | skills/geopandas/scripts/export_plan.py | .py | #!/usr/bin/env python3
"""Create a non-executing, redacted vector export and GeoParquet plan."""
from __future__ import annotations
import argparse
import sys
from typing import Any
from _common import (
ABSOLUTE_MAX_FEATURES,
DEFAULT_MAX_FEATURES,
DEFAULT_MAX_INPUT_BYTES,
CliError,
bounded_limit... | 306 | 11,098 |
scientific-agent-skills | skills/geopandas/scripts/vector_inventory.py | .py | #!/usr/bin/env python3
"""Create a redacted, metadata-only inventory of one local vector dataset."""
from __future__ import annotations
import argparse
import hashlib
import sys
from _common import (
ABSOLUTE_MAX_FEATURES,
DEFAULT_MAX_FEATURES,
DEFAULT_MAX_INPUT_BYTES,
PINNED_STACK,
bounded_limit... | 141 | 4,488 |
scientific-agent-skills | skills/geopandas/scripts/spatial_join_audit.py | .py | #!/usr/bin/env python3
"""Run a bounded local spatial join and emit only aggregate cardinality."""
from __future__ import annotations
import argparse
import sys
from collections import Counter
from typing import Any
from _common import (
ABSOLUTE_MAX_FEATURES,
DEFAULT_MAX_FEATURES,
DEFAULT_MAX_INPUT_BYTE... | 369 | 12,848 |
scientific-agent-skills | skills/phylogenetics/scripts/phylogenetic_analysis.py | .py | """
Phylogenetic Analysis Pipeline
===============================
Complete workflow: MAFFT alignment → IQ-TREE tree → ETE3 visualization.
Requirements:
conda install -c bioconda mafft iqtree
uv pip install ete3
Usage:
python phylogenetic_analysis.py sequences.fasta --type nt --threads 4
python phylog... | 273 | 9,148 |
scientific-agent-skills | skills/pyopenms/scripts/process_identifications.py | .py | #!/usr/bin/env python3
"""
Process Peptide/Protein Identifications
Post-process search-engine results (idXML): optionally re-index peptides against
a protein FASTA (assigns target/decoy + protein accessions), estimate FDR/q-values,
filter by FDR threshold, peptide length, and best-hit-per-spectrum, then export a
filte... | 112 | 4,464 |
scientific-agent-skills | skills/pyopenms/scripts/theoretical_spectrum.py | .py | #!/usr/bin/env python3
"""
Theoretical Fragment Spectrum Generator
Generate a theoretical fragment-ion spectrum (b/y, optionally a/c/x/z and
losses) for a peptide using TheoreticalSpectrumGenerator. Prints annotated
fragment ions and optionally writes the spectrum to mzML and/or a CSV peak list.
Usage:
python the... | 76 | 2,935 |
scientific-agent-skills | skills/pyopenms/scripts/detect_adducts.py | .py | #!/usr/bin/env python3
"""
Adduct Detection / Feature Decharging
Group features that are different ionization forms (adducts/charge variants) of
the same neutral compound using MetaboliteFeatureDeconvolution. Annotates each
feature with its inferred adduct and neutral mass, and writes the decharged
feature map plus a ... | 91 | 3,683 |
scientific-agent-skills | skills/pyopenms/scripts/export_gnps_sirius.py | .py | #!/usr/bin/env python3
"""
Export for GNPS (FBMN) and SIRIUS
Generate the input files required by downstream annotation tools:
gnps Feature-Based Molecular Networking: writes an MGF of MS2 spectra
(from a consensusXML linked across samples) plus the GNPS
quantification table.
sirius... | 91 | 3,359 |
scientific-agent-skills | skills/pyopenms/scripts/accurate_mass_search.py | .py | #!/usr/bin/env python3
"""
Accurate Mass Search (Metabolite Annotation)
Annotate detected features with putative metabolite identities by matching
accurate masses against the bundled HMDB databases using AccurateMassSearchEngine.
Outputs an annotated mzTab and a flat CSV of hits. By default uses the HMDB
mapping/struc... | 112 | 4,518 |
scientific-agent-skills | skills/pyopenms/scripts/convert_format.py | .py | #!/usr/bin/env python3
"""
Convert Between MS File Formats
Convert spectral data between mzML, mzXML, and MGF, with optional MS-level and
RT/intensity filtering. Uses FileHandler for transparent format detection on load.
Supported conversions (by output extension): .mzML, .mzXML, .mgf
Usage:
python convert_forma... | 96 | 3,293 |
scientific-agent-skills | skills/pyopenms/scripts/align_link_quantify.py | .py | #!/usr/bin/env python3
"""
Multi-Sample Align, Link, and Quantify
End-to-end untargeted quantification across multiple LC-MS samples:
1. Detect features in each mzML (FeatureFindingMetabo) [or load .featureXML]
2. Align retention times (MapAlignmentAlgorithmPoseClustering)
3. Link features into a consen... | 141 | 5,352 |
scientific-agent-skills | skills/pyopenms/scripts/plot_ms_data.py | .py | #!/usr/bin/env python3
"""
Visualize MS Data
Quick plots for inspecting MS data and results:
spectrum single MS spectrum (peak/stick plot) by index or RT
tic total ion chromatogram
featuremap 2D feature map (RT vs m/z, sized/colored by intensity)
map2d 2D heatmap of MS1 signal (RT... | 130 | 4,026 |
scientific-agent-skills | skills/pyopenms/scripts/detect_features_metabo.py | .py | #!/usr/bin/env python3
"""
Untargeted Metabolomics Feature Detection
Run the standard OpenMS small-molecule feature-finding pipeline on centroided
LC-MS data:
MassTraceDetection -> ElutionPeakDetection -> FeatureFindingMetabo
Outputs a featureXML and (optionally) a CSV table of detected features.
This is the rec... | 111 | 4,169 |
scientific-agent-skills | skills/pyopenms/scripts/inspect_ms_data.py | .py | #!/usr/bin/env python3
"""
Inspect Mass Spectrometry Data
Load any supported MS file (mzML, mzXML, featureXML, consensusXML, idXML) and
print a structured summary: spectrum counts by MS level, RT/m/z ranges, TIC,
chromatograms, precursor info, and instrument metadata. Optionally dump a
per-spectrum table to CSV.
Usag... | 168 | 5,980 |
scientific-agent-skills | skills/pyopenms/scripts/consensus_to_matrix.py | .py | #!/usr/bin/env python3
"""
Consensus Map to Quantification Matrix
Convert a consensusXML into analysis-ready tables: a wide intensity matrix
(consensus features x samples) joined with feature metadata (RT, m/z, charge,
quality), plus an optional long/tidy format. Optionally normalize intensities
across samples (median... | 71 | 2,775 |
scientific-agent-skills | skills/pyopenms/scripts/digest_protein.py | .py | #!/usr/bin/env python3
"""
In-Silico Protein Digestion
Digest protein sequences (FASTA or a single sequence) with a configurable
protease, producing theoretical peptides with masses and m/z. Useful for
targeted method design and search-space estimation.
Usage:
python digest_protein.py proteins.fasta --out peptide... | 103 | 3,535 |
scientific-agent-skills | skills/pyopenms/scripts/detect_features_centroided.py | .py | #!/usr/bin/env python3
"""
Peptide/Centroided Feature Detection
Detect features in centroided (peak-picked) LC-MS data using
FeatureFinderAlgorithmPicked -- the modern replacement for the removed
FeatureFinderCentroided. Suited to peptide/proteomics data with defined
isotope patterns and charge states.
Outputs a feat... | 81 | 3,027 |
scientific-agent-skills | skills/pyopenms/scripts/extract_chromatograms.py | .py | #!/usr/bin/env python3
"""
Extract Ion Chromatograms (XIC/EIC) and TIC/BPC
Build chromatograms from MS1 data: total ion chromatogram (TIC), base peak
chromatogram (BPC), and extracted ion chromatograms (XIC) for target m/z values
within a ppm tolerance. Writes a tidy CSV (rt, trace, intensity) and optionally
a PNG plo... | 106 | 3,810 |
scientific-agent-skills | skills/pyopenms/scripts/process_spectra.py | .py | #!/usr/bin/env python3
"""
Signal Processing for Spectra
Apply a configurable chain of signal-processing steps to all (or selected MS-level)
spectra in an MS file: smoothing, centroiding (peak picking), normalization, and
intensity/S-N thresholding. Steps run in the order listed below.
Steps (enable with flags):
... | 125 | 4,793 |
scientific-agent-skills | skills/pyopenms/scripts/mass_calculator.py | .py | #!/usr/bin/env python3
"""
Mass & Chemistry Calculator
Compute masses and isotope distributions for peptides (amino-acid sequences),
empirical formulas, or both. Reports monoisotopic and average mass, m/z for a
range of charge states, the molecular formula, and the theoretical isotope
pattern.
Usage:
python mass_... | 93 | 3,481 |
scientific-agent-skills | skills/relsa-severity-assessment/scripts/forecast_relsa.py | .py | #!/usr/bin/env python3
"""foRcast — ARIMA forecasting of RELSA severity trajectories.
Port of the foRcast tool of Lutscher et al. (2026), Front. Physiol. 17:1869563:
an ARIMA model fitted per animal to its RELSA trajectory, forecasting the score
at the next (or the humane-endpoint) time point with a 95% prediction int... | 758 | 29,431 |
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