Crossmapper

Crossmapper evaluates simulated sequencing reads to quantify cross-mapping between reference genomes and to guide experimental design for multi-species, host–pathogen, hybrid, xenograft, and metagenomic sequencing studies.

Key Features:

• Read Cross-Mapping Assessment: It evaluates the likelihood that sequencing reads originate from unintended genomes in multi-species contexts such as host–pathogen interactions, hybrid genomes, xenografts, and metagenomics.
• Experimental Design Optimization: By simulating reads and back-mapping them to reference genomes, it quantifies cross-mapping rates and enables comparison of parameters such as read length, layout, coverage, and mapping settings.
• Comparative Reporting: It generates reports summarizing cross-mapping rates across multiple comparisons to support selection of experimental parameters.
• Resource Optimization: It assesses the impact of pooling diverse genetic materials into single libraries by quantifying potential cross-mapping biases to inform sequencing strategies.

Scientific Applications:

• Transcriptomics and Metagenomics Studies: It aids in distinguishing reads from different organisms within complex samples.
• Hybrid Species Analysis: It predicts cross-mapping issues in sequencing studies involving hybrid genomes.
• Allele-Specific Expression Studies: It helps optimize design parameters to minimize cross-mapping artifacts in allele-specific expression analyses.

Methodology:

Simulate reads from user-provided genomic or transcriptomic data, back-map simulated reads to reference genomes, and quantify cross-mapping rates across specified parameters including read length, layout, coverage, and mapping settings.