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title | Submit to the TACC queue or run in an idev shell |
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Create a commands file and use launcher_creator.py followed by sbatch. Expand |
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title | I need some help figuring out the options... |
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| Put this in your commands file: Code Block |
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nano commands.mem
bwa mem reference/genome.fa data/GSM794483_C1_R1_1.fq data/GSM794483_C1_R1_2.fq > C1_R1.mem.sam
bwa mem reference/genome.fa data/GSM794484_C1_R2_1.fq data/GSM794484_C1_R2_2.fq > C1_R2.mem.sam
bwa mem reference/genome.fa data/GSM794485_C1_R3_1.fq data/GSM794485_C1_R3_2.fq > C1_R3.mem.sam
bwa mem reference/genome.fa data/GSM794486_C2_R1_1.fq data/GSM794486_C2_R1_2.fq > C2_R1.mem.sam
bwa mem reference/genome.fa data/GSM794487_C2_R2_1.fq data/GSM794487_C2_R2_2.fq > C2_R2.mem.sam
bwa mem reference/genome.fa data/GSM794488_C2_R3_1.fq data/GSM794488_C2_R3_2.fq > C2_R3.mem.sam |
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title | Use this Launcher_creator command |
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| launcher_creator.py -n mem -t 04:00:00 -j commands.mem -q normal -a UT-2015-05-18 -m "module load bwa/0.7.7" -l bwa_mem_launcher.slurm |
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Since these will take a while to run, you can look at already generated results at: /corral-repl/utexas/BioITeam/rnaseq_course_2015/bwa_mem_results
Help! I have a lots of reads and a large number of reads. Make BWA go faster!
Now that we are done mapping, lets look at how to assess mapping results.