How do I install the Hisat2 Simulate Reads Py skill?

Run npx skillmds add vimalinx/hisat2-simulate-reads-py in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Hisat2 Simulate Reads Py safe to use?

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Which AI agents work with Hisat2 Simulate Reads Py?

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Is Hisat2 Simulate Reads Py free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Hisat2 Simulate Reads Py?

vimalinx (@vimalinx) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Hisat2 Simulate Reads Py by vimalinx

Name: Hisat2 Simulate Reads Py
Rating: 4.2 (5 reviews)
Author: vimalinx

File contents

hisat2-simulate-reads-py

Quick Start

Command: hisat2_simulate_reads.py [genome_file] [gtf_file] [snp_file] [base_fname]
Local executable: /home/vimalinx/miniforge3/envs/bio/bin/hisat2_simulate_reads.py
Full reference: See references/help.md for complete options and usage details

When To Use This Tool

Use hisat2_simulate_reads.py when you need synthetic HISAT2-style benchmark reads from a genome, annotation, and SNP set.
It is appropriate for RNA-seq by default, but can also simulate DNA-seq with -d.
Use it when benchmarking alignment settings, validating graph-aware variant handling, or generating controlled test data with fixed read and fragment lengths.
Reach for it when you need reproducible simulations with explicit random seeds and optional sanity checks.

Common Patterns

# Default paired-end RNA-seq simulation
hisat2_simulate_reads.py genome.fa annotation.gtf variants.snp sim

# Single-end RNA-seq with shorter reads
hisat2_simulate_reads.py genome.fa annotation.gtf variants.snp sim --single-end -r 75 -n 100000

# DNA-seq simulation with explicit random seed
hisat2_simulate_reads.py genome.fa annotation.gtf variants.snp sim -d --random-seed 42

# Run internal sanity checks and print extra statistics
hisat2_simulate_reads.py genome.fa annotation.gtf variants.snp sim --sanity-check -v

Recommended Workflow

Prepare a reference genome FASTA file and corresponding GTF annotation file
Optionally prepare a SNP file if variant incorporation is needed
Run hisat2_simulate_reads.py with required positional arguments and desired options (e.g., -n for fragment count, -e for expression profile)
Validate output using --sanity-check and review statistics with -v if needed

Guardrails

Requires both genome FASTA and GTF files as positional inputs
Defaults to paired-end RNA-seq reads; use --single-end and/or -d for alternative modes
Set --random-seed for reproducible simulations
The script writes output files based on base_fname, including base_fname.sam and at least base_fname_1.fa (plus base_fname_2.fa for paired-end mode)
In the current environment, -h prints a non-fatal Python SyntaxWarning before the usage text; treat that as a script warning, not a failed invocation

---name: hisat2-simulate-reads-pydescription: Use when simulating RNA-seq or DNA-seq reads from a reference genome and GTF annotation file, optionally incorporating SNP variants and controlling expression profiles.--- # hisat2-simulate-reads-py ## Quick Start - **Command:** `hisat2_simulate_reads.py [genome_file] [gtf_file] [snp_file] [base_fname]` - **Local executable:** `/home/vimalinx/miniforge3/envs/bio/bin/hisat2_simulate_reads.py` - **Full reference:** See `references/help.md` for complete options and usage details ## When To Use This Tool - Use `hisat2_simulate_reads.py` when you need synthetic HISAT2-style benchmark reads from a genome, annotation, and SNP set. - It is appropriate for RNA-seq by default, but can also simulate DNA-seq with `-d`. - Use it when benchmarking alignment settings, validating graph-aware variant handling, or generating controlled test data with fixed read and fragment lengths. - Reach for it when you need reproducible simulations with explicit random seeds and optional sanity checks. ## Common Patterns ```bash # Default paired-end RNA-seq simulation hisat2_simulate_reads.py genome.fa annotation.gtf variants.snp sim # Single-end RNA-seq with shorter reads hisat2_simulate_reads.py genome.fa annotation.gtf variants.snp sim --single-end -r 75 -n 100000 # DNA-seq simulation with explicit random seed hisat2_simulate_reads.py genome.fa annotation.gtf variants.snp sim -d --random-seed 42 # Run internal sanity checks and print extra statistics hisat2_simulate_reads.py genome.fa annotation.gtf variants.snp sim --sanity-check -v ``` ## Recommended Workflow 1. Prepare a reference genome FASTA file and corresponding GTF annotation file 2. Optionally prepare a SNP file if variant incorporation is needed 3. Run `hisat2_simulate_reads.py` with required positional arguments and desired options (e.g., `-n` for fragment count, `-e` for expression profile) 4. Validate output using `--sanity-check` and review statistics with `-v` if needed ## Guardrails - Requires both genome FASTA and GTF files as positional inputs - Defaults to paired-end RNA-seq reads; use `--single-end` and/or `-d` for alternative modes - Set `--random-seed` for reproducible simulations - The script writes output files based on `base_fname`, including `base_fname.sam` and at least `base_fname_1.fa` (plus `base_fname_2.fa` for paired-end mode) - In the current environment, `-h` prints a non-fatal Python `SyntaxWarning` before the usage text; treat that as a script warning, not a failed invocation

Frequently asked questions