Agent skill

bio-sequence-properties

View SKILL.md on GitHub Repository
Stars 2,009
Forks 275

Install this agent skill to your Project

npx add-skill https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-sequence-properties

SKILL.md

name: bio-sequence-properties description: Calculate sequence properties like GC content, molecular weight, isoelectric point, and GC skew using Biopython. Use when analyzing sequence composition, computing physical properties, or comparing sequences. tool_type: python primary_tool: Bio.SeqUtils measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

  • read_file
  • run_shell_command

Sequence Properties

Calculate physical and chemical properties of biological sequences using Biopython.

Required Imports

python
from Bio.Seq import Seq
from Bio.SeqUtils import gc_fraction, molecular_weight, GC123, GC_skew, nt_search, seq1, seq3
from Bio.SeqUtils.ProtParam import ProteinAnalysis

DNA/RNA Properties

GC Content

python
from Bio.SeqUtils import gc_fraction

seq = Seq('ATGCGATCGATCGATCGATCG')
gc = gc_fraction(seq)  # Returns 0.476... (fraction)
gc_percent = gc * 100  # Convert to percentage

Handle ambiguous bases:

python
gc = gc_fraction(seq, ambiguous='ignore')  # Ignore N bases in calculation
gc = gc_fraction(seq, ambiguous='weighted')  # Weight by probability

GC at Codon Positions (GC123)

Analyze GC content at each codon position (useful for codon bias analysis):

python
from Bio.SeqUtils import GC123

seq = Seq('ATGCGATCGATCGATCGATCG')
gc_total, gc_pos1, gc_pos2, gc_pos3 = GC123(seq)
# gc_total: overall GC%
# gc_pos1: GC% at 1st codon position
# gc_pos2: GC% at 2nd codon position
# gc_pos3: GC% at 3rd codon position (wobble)

GC Skew

Calculate (G-C)/(G+C) in sliding windows to identify replication origins:

python
from Bio.SeqUtils import GC_skew

seq = Seq('ATGCGATCGATCGATCGATCG' * 10)
skew_values = GC_skew(seq, window=100)  # Returns list of skew values

Molecular Weight

python
from Bio.SeqUtils import molecular_weight

dna = Seq('ATGCGATCG')
mw = molecular_weight(dna)  # Single-stranded DNA weight

# Double-stranded DNA
mw_ds = molecular_weight(dna, double_stranded=True)

# Circular DNA
mw_circ = molecular_weight(dna, circular=True)

# RNA
rna = Seq('AUGCGAUCG')
mw_rna = molecular_weight(rna, seq_type='RNA')

# Protein
protein = Seq('MRCRS')
mw_prot = molecular_weight(protein, seq_type='protein')

Melting Temperature

python
from Bio.SeqUtils import MeltingTemp

seq = Seq('ATGCGATCGATCG')

# Basic Tm (Wallace rule - short oligos)
tm_wallace = MeltingTemp.Tm_Wallace(seq)

# GC method (more accurate for longer sequences)
tm_gc = MeltingTemp.Tm_GC(seq)

# Nearest neighbor (most accurate)
tm_nn = MeltingTemp.Tm_NN(seq)

# With salt correction
tm_corrected = MeltingTemp.Tm_NN(seq, Na=50, Mg=1.5)

Sequence Search with IUPAC Codes (nt_search)

Built-in search that handles IUPAC ambiguity codes:

python
from Bio.SeqUtils import nt_search

seq = 'ATGCGATCGATCGATNGATC'
# Search for pattern with ambiguous bases
result = nt_search(seq, 'GATNGATC')  # N matches any base
# Returns: ['GATNGATC', 8] - pattern and position(s)

Base Composition

python
def base_composition(seq):
    seq_str = str(seq).upper()
    total = len(seq_str)
    return {base: seq_str.count(base) / total * 100 for base in 'ATGC'}

Amino Acid Code Conversion

Convert between 1-letter and 3-letter amino acid codes:

python
from Bio.SeqUtils import seq1, seq3

# 3-letter to 1-letter
one_letter = seq1('MetAlaGlyTrp')  # Returns 'MAGW'

# 1-letter to 3-letter
three_letter = seq3('MAGW')  # Returns 'MetAlaGlyTrp'

# With custom separator
three_letter = seq3('MAGW', join='-')  # Returns 'Met-Ala-Gly-Trp'

Protein Properties

Using ProteinAnalysis

python
from Bio.SeqUtils.ProtParam import ProteinAnalysis

protein = ProteinAnalysis('MAEGEITTFTALTEKFNLPPGNYKKPKLLYCSNG')

Basic Properties

python
mw = protein.molecular_weight()           # Molecular weight in Daltons
pi = protein.isoelectric_point()          # Isoelectric point
aa_comp = protein.amino_acids_percent     # Amino acid composition (property)
aa_count = protein.count_amino_acids()    # Raw amino acid counts

Stability and Hydropathy

python
instability = protein.instability_index()  # < 40 = stable, > 40 = unstable
gravy = protein.gravy()                    # Negative = hydrophilic, Positive = hydrophobic
arom = protein.aromaticity()               # Fraction of Phe+Trp+Tyr

Charge at Specific pH

python
charge = protein.charge_at_pH(7.0)  # Net charge at pH 7.0
charge_acidic = protein.charge_at_pH(4.0)
charge_basic = protein.charge_at_pH(10.0)

Flexibility Profile

python
flexibility = protein.flexibility()  # List of flexibility values per residue
# Based on Vihinen, 1994 scale

Secondary Structure

python
helix, turn, sheet = protein.secondary_structure_fraction()

Extinction Coefficient

python
eps_reduced, eps_cystine = protein.molar_extinction_coefficient()
# eps_reduced: all Cys are reduced
# eps_cystine: all Cys form disulfide bonds

Protein Scale Profiles

Calculate profiles using any amino acid scale:

python
# Kyte-Doolittle hydropathy profile
kd_scale = {'A': 1.8, 'R': -4.5, 'N': -3.5, ...}
profile = protein.protein_scale(kd_scale, window=7)

Code Patterns

Analyze Multiple Sequences

python
from Bio import SeqIO
from Bio.SeqUtils import gc_fraction

def analyze_fasta(filename):
    results = []
    for record in SeqIO.parse(filename, 'fasta'):
        results.append({
            'id': record.id,
            'length': len(record.seq),
            'gc': gc_fraction(record.seq) * 100
        })
    return results

GC Content Distribution (Sliding Windows)

python
from Bio.SeqUtils import gc_fraction

def gc_distribution(seq, window_size=100, step=50):
    gc_values = []
    for i in range(0, len(seq) - window_size + 1, step):
        window = seq[i:i + window_size]
        gc_values.append((i, gc_fraction(window) * 100))
    return gc_values

GC Skew Plot Data

python
from Bio.SeqUtils import GC_skew

def gc_skew_analysis(seq, window=1000):
    skew = GC_skew(seq, window=window)
    positions = list(range(0, len(seq) - window + 1, window))
    cumulative = []
    total = 0
    for s in skew:
        total += s
        cumulative.append(total)
    return positions, skew, cumulative

Full Protein Analysis Report

python
from Bio.SeqUtils.ProtParam import ProteinAnalysis

def protein_report(sequence):
    protein = ProteinAnalysis(str(sequence).replace('*', ''))
    helix, turn, sheet = protein.secondary_structure_fraction()
    return {
        'length': len(sequence),
        'molecular_weight': protein.molecular_weight(),
        'isoelectric_point': protein.isoelectric_point(),
        'charge_at_pH7': protein.charge_at_pH(7.0),
        'instability_index': protein.instability_index(),
        'gravy': protein.gravy(),
        'aromaticity': protein.aromaticity(),
        'helix_fraction': helix,
        'turn_fraction': turn,
        'sheet_fraction': sheet,
    }

Dinucleotide Frequencies

python
from collections import Counter

def dinucleotide_freq(seq):
    seq_str = str(seq)
    dinucs = [seq_str[i:i+2] for i in range(len(seq_str) - 1)]
    counts = Counter(dinucs)
    total = sum(counts.values())
    return {di: count / total for di, count in counts.items()}

CpG Observed/Expected Ratio

python
def cpg_ratio(seq):
    seq_str = str(seq).upper()
    cpg = seq_str.count('CG')
    c = seq_str.count('C')
    g = seq_str.count('G')
    expected = (c * g) / len(seq_str) if len(seq_str) > 0 else 0
    return cpg / expected if expected > 0 else 0

Property Reference

DNA/RNA Properties

Property Function Notes
GC content gc_fraction() Returns fraction (0-1)
GC by position GC123() Total, pos1, pos2, pos3
GC skew GC_skew() (G-C)/(G+C) in windows
Molecular weight molecular_weight() In Daltons
Melting temp MeltingTemp.Tm_*() Multiple methods
IUPAC search nt_search() Handles ambiguity codes

Protein Properties

Property Method Typical Range
MW molecular_weight() Daltons
pI isoelectric_point() 0-14
Charge charge_at_pH(pH) Varies
Instability instability_index() <40 stable
GRAVY gravy() -2 to +2
Aromaticity aromaticity() 0-0.15
Flexibility flexibility() Per-residue list

Amino Acid Codes

Function Input Output
seq1() 'MetAlaGly' 'MAG'
seq3() 'MAG' 'MetAlaGly'

Common Errors

Error Cause Solution
KeyError in ProteinAnalysis Non-standard amino acid Remove X, *, etc.
Wrong MW Wrong seq_type Specify 'RNA' or 'protein'
Invalid Tm Sequence too short Use >10 bp for accurate Tm
Empty GC_skew Sequence shorter than window Reduce window size

Decision Tree

Need sequence properties?
├── DNA/RNA sequence?
│   ├── GC content? → gc_fraction()
│   ├── GC at codon positions? → GC123()
│   ├── GC skew (replication origin)? → GC_skew()
│   ├── Molecular weight? → molecular_weight()
│   ├── Melting temperature? → MeltingTemp.Tm_NN()
│   └── Search with IUPAC codes? → nt_search()
├── Protein sequence?
│   └── Create ProteinAnalysis object
│       ├── Size → molecular_weight()
│       ├── Charge → isoelectric_point(), charge_at_pH()
│       ├── Stability → instability_index()
│       ├── Hydrophobicity → gravy()
│       ├── Flexibility → flexibility()
│       └── Structure → secondary_structure_fraction()
└── Convert amino acid codes?
    └── seq1() / seq3()

Related Skills

  • seq-objects - Create Seq objects for property calculation
  • sequence-io/sequence-statistics - File-level statistics (N50, totals)
  • codon-usage - GC123 for codon position analysis
  • transcription-translation - Translate before protein analysis
  • alignment-files/bam-statistics - samtools stats for alignment-level GC and quality stats

Recommended Agent Skills

Expand your agent's capabilities with these related and highly-rated skills.

FreedomIntelligence/OpenClaw-Medical-Skills

vcf-annotator

Annotate VCF variants with VEP, ClinVar, gnomAD frequencies, and ancestry-aware context. Generates prioritised variant reports.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

chemist-analyst

Analyzes events through chemistry lens using molecular structure, reaction mechanisms, thermodynamics, kinetics, and analytical techniques (spectroscopy, chromatography, mass spectrometry). Provides insights on chemical processes, material properties, reaction pathways, synthesis, and analytical methods. Use when: Chemical reactions, material analysis, synthesis planning, process optimization, environmental chemistry. Evaluates: Molecular structure, reaction mechanisms, yield, selectivity, safety, environmental impact.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

bio-alignment-io

Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and other alignment formats for phylogenetics and conservation analysis. Use when reading, writing, or converting alignment file formats.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

sleep-analyzer

分析睡眠数据、识别睡眠模式、评估睡眠质量，并提供个性化睡眠改善建议。支持与其他健康数据的关联分析。

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

metabolomics-workbench-database

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.

2,009 275
Explore
FreedomIntelligence/OpenClaw-Medical-Skills

bio-hi-c-analysis-matrix-operations

Balance, normalize, and transform Hi-C contact matrices using cooler and cooltools. Apply iterative correction (ICE), compute expected values, and generate observed/expected matrices. Use when normalizing or transforming Hi-C matrices.

2,009 275
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results