Bio Tools

Quality Control

# FastQC report
fastqc reads.fq -o qc_output/

# FASTA/FASTQ stats
seqtk comp reads.fq | head
seqtk size reads.fq

Genome Arithmetic

# Intersect two BED files
bedtools intersect -a regions.bed -b features.bed

# Coverage
bedtools coverage -a regions.bed -b aligned.bam

# Get FASTA from BED regions
bedtools getfasta -fi reference.fa -bed regions.bed

Python Quick Recipes

# Read FASTA/FASTQ
from Bio import SeqIO
for record in SeqIO.parse("input.fa", "fasta"):
    print(record.id, len(record.seq))

# Fetch from NCBI
from Bio import Entrez
Entrez.email = "[email protected]"
handle = Entrez.efetch(db="nucleotide", id="NM_000546", rettype="fasta")
record = SeqIO.read(handle, "fasta")

# Differential expression
from pydeseq2 import DeseqDataSet, DeseqStats
dds = DeseqDataSet(counts=count_matrix, metadata=metadata, design="~condition")
dds.deseq2()
stat_res = DeseqStats(dds, contrast=["condition", "treated", "untreated"])
stat_res.summary()

# Single-cell RNA-seq
import scanpy as sc
adata = sc.read_h5ad("data.h5ad")
sc.pp.normalize_total(adata)
sc.pp.log1p(adata)
sc.tl.pca(adata)
sc.tl.umap(adata)
sc.tl.leiden(adata)

# Molecular structures
from rdkit import Chem
from rdkit.Chem import Descriptors
mol = Chem.MolFromSmiles("CC(=O)OC1=CC=CC=C1C(=O)O")  # Aspirin
print(f"MW: {Descriptors.MolWt(mol):.1f}")
print(f"LogP: {Descriptors.MolLogP(mol):.2f}")

Important Notes

• For remote BLAST against NCBI, use Bio.Blast.NCBIWWW.qblast() — this sends the query over the network
• For large files, prefer streaming with SeqIO.parse() over SeqIO.read()
• Save plots to files (plt.savefig("/workspace/group/plot.png")) since there's no display
• Write output files to /workspace/group/ so the user can access them