Stampy - Mapping multiple individuals to genome
Hi everybody,
I am very very new to this world, so apologize if the following questions are too basic...
I am trying to use Stampy to map my RAD-seq reads to a reference genome.
I have double digested, paired end data from multiple individuals of 6 species and the genome of one of those species.
I created the genome file and the hash table. According to the manual when mapping paired end data to a genome the script should look something like that:
./stampy.py -g hg18 -h hg18 -M solexareads_1.fastq solexareads_2.fastq
My questions are:
1) is it possible to map multiple individuals to the genome in one go or should I map each individual singularly to it? Could I use for example something like:
./stampy.py -g hg18 -h hg18 -M ind1_1.fastq ind1_2.fastq ind2_1.fastq ind2_2.fastq ind3_1.fastq ind3_2.fastq ?
2) which option can be added to specify the number of mismatches allowed between reads and genome? I didn't understand it from the help...
Any help would be greatly appreciated
Many many thanks
Vivi
Hi everybody,
I am very very new to this world, so apologize if the following questions are too basic...
I am trying to use Stampy to map my RAD-seq reads to a reference genome.
I have double digested, paired end data from multiple individuals of 6 species and the genome of one of those species.
I created the genome file and the hash table. According to the manual when mapping paired end data to a genome the script should look something like that:
./stampy.py -g hg18 -h hg18 -M solexareads_1.fastq solexareads_2.fastq
My questions are:
1) is it possible to map multiple individuals to the genome in one go or should I map each individual singularly to it? Could I use for example something like:
./stampy.py -g hg18 -h hg18 -M ind1_1.fastq ind1_2.fastq ind2_1.fastq ind2_2.fastq ind3_1.fastq ind3_2.fastq ?
2) which option can be added to specify the number of mismatches allowed between reads and genome? I didn't understand it from the help...
Any help would be greatly appreciated
Many many thanks
Vivi
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