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Mapping of large DNA insertions of known sequence by capturing reads or read pairs spanning the junction of the insertion and the genome.

Mapping of recessive point mutations in bulked segregant populations via linkage analysis.

Mapping of point mutations in mutants selected after several backrosses by analysis of the variant density across the genome.

Analyses the effect of a set of polymorphisms on coding sequences with no mapping algorithm.

Mapping of natural variants using QTL-seq approaches.

Mutant background: Mapping cross performed: Origin of the control reads:

Use low stringency during SNP analysis? By default, Easymap only considers SNPs that pass high quality thresholds. However, in sub-optimal read datasets, more lenient filtering can help to identify a candidate interval and the causal mutation. If you analyzed your reads in the default mode and obtained very few SNPs or believe that the causal mutation could have been discarded, turn on this option and run the program again.

Perform automated pre-processing of read files? Checking this option will add an optional step to process the input reads to eliminate low-quality data, trim low-quality nucleotides and auto-remove adapters. This step is performed with fastp and will require additional storage space.

Use multiple CPU cores during analysis? Using multiple cores will notably accelerate certain parts of the analysis. If you dont know how many cores your computer can spare, leave this option unchecked, otherwise please indicate how many cores Easymap can use.

Number of cores:
Warning: Overloading the CPU can lead to lagging or system failure.

Reference sequence:
GFF3 file (gene structural annotation):
Gene functional annotation file [OPTIONAL]:

Test sample (if your reads are paired-end, select both files while holding the Ctrl/Cmd key):

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