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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.

Code Block

title	Get set up for the exercises

cds
cd my_rnaseq_course
cd day_1_partB2/hisat_exercise
ls

Next, see if HISAT2 is a module that is available on stampede.

Code Block
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.

Code Blockcode

title	Load hisat2 module

#if not loaded already, load biocontainers module 
module spider hisat2
module load hisat2/ctr-2.1.0--py36pl5.22.0_0

Code Block

title	Check is hisat2 is accessible after loading module

hisat2

Part 1. Create a index of your reference

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Warning

title	Submit to the TACC queue or run in an idev shell

Create a commands file and use launcher_creator.py followed by sbatch.

Code Block

title	Put this in your commands file

nano commands.hisat2

hisat2 -x ../reference/genome.fa -1 ../data/GSM794483_C1_R1_1.fq -2 ../data/GSM794483_C1_R1_2.fq -S GSM794483_C1.sam --phred33 --novel-splicesite-outfile GSM794483_C1.junctions --rna-strandness RF --dta -t
hisat2 -x ../reference/genome.fa -1 ../data/GSM794484_C1_R2_1.fq -2 ../data/GSM794484_C1_R2_2.fq -S GSM794484_C1.sam --phred33 --novel-splicesite-outfile GSM794484_C1.junctions --rna-strandness RF --dta -t
hisat2 -x ../reference/genome.fa -1 ../data/GSM794485_C1_R3_1.fq -2 ../data/GSM794485_C1_R3_2.fq -S GSM794485_C1.sam --phred33 --novel-splicesite-outfile GSM794485_C1.junctions --rna-strandness RF --dta -t
hisat2 -x ../reference/genome.fa -1 ../data/GSM794486_C2_R1_1.fq -2 ../data/GSM794486_C2_R1_2.fq -S GSM794486_C1.sam --phred33 --novel-splicesite-outfile GSM794486_C1.junctions --rna-strandness RF --dta -t
hisat2 -x ../reference/genome.fa -1 ../data/GSM794487_C2_R2_1.fq -2 ../data/GSM794487_C2_R2_2.fq -S GSM794487_C1.sam --phred33 --novel-splicesite outfile GSM794487_C1.junctions --rna-strandness RF --dta -t
hisat2 -x ../reference/genome.fa -1 ../data/GSM794488_C2_R3_1.fq -2 ../data/GSM794488_C2_R3_2.fq -S GSM794488_C1.sam --phred33 --novel-splicesite-outfile GSM794488_C1.junctions --rna-strandness RF --dta -t

Expand

title	Use this Launcher_creator command

launcher_creator.py -n hisat2 -t 01:00:00 -j commands.hisat2 -q normal -a UT-2015-05-18 -DNAdenovo -l hisat2_launcher.slurm -m " module load biocontainers; module load hisat2/ctr-2.1.0--py36pl5.22.0_0"

Hisat2 output

1.SAM file : HISAT2 alignment output in standard SAM format.

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Code Block

title	Example alignment summary

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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Run HISAT2