Quick Start Guide

This guide will help you get started with SATAY Tools for analyzing transposon insertion data.

  1. Prepare your data: Ensure you have quality-controlled FASTQ files from your SATAY experiment

  2. Align reads: Map FASTQ files to reference genome

# Align FASTQ files to genome and generate BAM files
satay align -f /path/to/fastq_dir -o /path/to/output_dir -g genome.fasta

  1. Map insertions: Identify genomic location of transposon insertions and count reads supporting each insertion. Generates a file with transposon insertions and read counts per genome interval (i.e. CDS).

# Call transposon insertions from BAM files
satay map -b /path/to/bam_dir -o /path/to/output_dir -s sample_name -a annotations.gff

  1. Merge counts: Combine transposon/read counts data from multiple samples. This writes {date}_{experiment_name}_transposon_counts.csv and {date}_{experiment_name}_read_counts.csv.

# Merge count files from multiple samples
satay merge -d /path/to/counts_dir -a annotations.gff -n experiment_name

  1. Analyze: Perform differential abundance analysis to identify significant changes in insertion frequency/ abundance between treatments. --counts-file is one of the count matrices from the merge step, and --sample_data is a CSV with a sample-ID column matching the matrix columns plus a condition column (see the Tutorial for the format).

# Perform differential analysis
satay analyze -f {date}_experiment_name_transposon_counts.csv -s sample_data.csv -o /path/to/output_dir -c condition_column -b baseline_condition