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First, the longer part of a read that maps to the genome contiguously (called the anchor) is mapped using the global index. Once this is mapped, this helps to to identify the relevant local index. HISAT can usually align the remaining part of the read (small anchor) within a single local index rather than searching across the whole genome.
Run HISAT2
First, make sure you are in the right directory for this exercise.
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cds cd my_rnaseq_course cd day_1_partB2/hisat_exercise ls |
Next, see if HISAT2 is a module that is available on stampede.
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module spider hisat |
As you can see, HISAT2 is not currently a module on stampede. When a program is not available on stampede, you can install it locally in your home or work directory. I have already installed HISAT in my work directory and since my work directory is in your path, you should be able to run hisat2. Type in hisat2 to see if it is in your path and to get usage information.
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#if not loaded already, load biocontainers module
module spider hisat2
module load hisat2/ctr-2.1.0--py36pl5.22.0_0 |
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hisat2 |
Part 1. Create a index of your reference
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Create a
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Hisat2 output
1.SAM file : HISAT2 alignment output in standard SAM format.
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11607353 reads; of these: 11607353 (100.00%) were paired; of these: 21592 (0.19%) aligned concordantly 0 times 11417720 (98.37%) aligned concordantly exactly 1 time 168041 (1.45%) aligned concordantly >1 times ---- 21592 pairs aligned concordantly 0 times; of these: 82 (0.38%) aligned discordantly 1 time ---- 21510 pairs aligned 0 times concordantly or discordantly; of these: 43020 mates make up the pairs; of these: 25009 (58.13%) aligned 0 times 9694 (22.53%) aligned exactly 1 time 8317 (19.33%) aligned >1 times 99.89% overall alignment rate |
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