Biowulf High Performance Computing at the NIH
LASER on Biowulf & Helix


From the LASER home page:

LASER is a program to estimate individual ancestry by directly analyzing shotgun sequence reads without calling genotypes. LASER uses principal components analysis (PCA) and Procrustes analysis to analyze sequence reads of each sample and place the sample into a reference PCA space constructed using genotypes of a set of reference individuals. With an appropriate reference panel, the estimated coordinates of the sequence samples reflect their ancestral background and can be used to correct for population stratification in association studies. LASER can accurately estimate ancestry even with modest amounts of data, such as the off-target sequence data generated by targeted sequencing experiments.

In version 2.0 or later, the software package includes a new program TRACE for tracing an individual's genetic ancestry based on genotype data. TRACE follows the same analysis framework as LASER and can accurately place study samples into a reference ancestry space using a relatively small number of genotypes. When using the same reference panel, LASER and TRACE can place sequenced and genotyped samples into the same ancestry space.

LASER can also perform standard PCA on genotype data to explore population structure and to create the reference ancestry space. Different options to compute PC scores and PC loadings have been implemented in the LASER program (version 2.01 or later).

There may be multiple versions of laser available. An easy way of selecting the version is to use modules. To see the modules available, type

module avail laser 

To select a module use

module load laser/[version]

where [version] is the version of choice.

Environment variables set



Interactive job on Biowulf

Allocate an interactive session with sinteractive and set up your environment

biowulf$ sinteractive --mem=10g
node$ module load laser
[+] Loading laser 2.04
node$ exit

First, we will use ~9k SNP loci on chr22 of 700 individuals from the Human Genome Diversity Panel (HGDP) as a reference set to calculate PCA coordinates. laser uses a combination of a configuration file and command line options:

node$ cp -r $LASER_TEST_DATA/HapMap_6_chr22.* $LASER_TEST_DATA/HGDP_700* .
node$ ls -lh
total 15M
-rw-r--r-- 1 user group 348K Jul 10 16:31 HapMap_6_chr22.seq
-rw-r--r-- 1 user group 243K Jul 10 16:31
-rw-r--r-- 1 user group  13M Jul 10 16:31 HGDP_700_chr22.geno
-rw-r--r-- 1 user group 243K Jul 10 16:31

node$ cat > test.config <<EOF
GENO_FILE      HGDP_700_chr22.geno
SEQ_FILE       HapMap_6_chr22.seq
DIM            8
node$ laser -p ./test.conf -pca 1 -o HGDP_700_chr22
====        LASER: Locating Ancestry from SEquence Reads        ====
====          Version 2.04, Last updated on Jan/11/2017         ====
====          (C) 2013-2017 Chaolong Wang, GNU GPL v3.0         ====
Started at: Mon Jul 10 16:41:20 2017

6 individuals in the SEQ_FILE.
9608 loci in the SEQ_FILE.
700 individuals in the GENO_FILE.
9608 loci in the GENO_FILE.

Parameter values used in execution:
GENO_FILE (-g)  HGDP_700_chr22.geno
DIM (-k)        8
OUT_PREFIX (-o) HGDP_700_chr22
CHECK_FORMAT (-fmt)     10
PCA_MODE (-pca) 1
RANDOM_SEED (-seed)     0
NUM_THREADS (-nt)       8

Mon Jul 10 16:41:20 2017
Checking data format ...
COORD_FILE: not specified.

Mon Jul 10 16:41:20 2017
Identify 9608 loci shared by SEQ_FILE and GENO_FILE.
The analysis will base on the remaining 9608 loci.

Mon Jul 10 16:41:20 2017
Reading reference genotypes ...

Mon Jul 10 16:41:21 2017
Performing PCA on reference genotypes ...
Genetic relationship matrix is output to 'HGDP_700_chr22.RefPC.grm'.
Z scores of reference individuals are output to 'HGDP_700_chr22.RefPC.zscore'.
Reference PCA coordinates are output to 'HGDP_700_chr22.RefPC.coord'.
Variances explained by PCs are output to 'HGDP_700_chr22.RefPC.var'.

Finished at: Mon Jul 10 16:41:23 2017
Total wall clock time: 3.02811 seconds.

node$ head HGDP_700_chr22.RefPC.coord
popID   indivID PC1     PC2     PC3     PC4     PC5     PC6     PC7     PC8
Brahui  HGDP00005       2.81178 14.9014 -1.47298        -3.51307        19.0424 -1.46033        10.8402 0.777612
Brahui  HGDP00007       -0.0477848      16.4082 1.4118  -4.20778        15.3486 -5.65236        7.55021 10.5837
Brahui  HGDP00009       -0.567587       14.5716 2.67543 -4.94805        6.51882 1.95237 2.0824  0.0295942

The reference coordinate file does not have to be calculated separately as we've done here. However, if the analysis of unknown samples is to be done more than once or if samples are to be split, it is computationally more efficient. Next, we can analyze some unknown samples. We add the name of the coord file to the config file and omit the -pca to do so. In addition, since this is a stochastic process we will run it three times and take the averate coordinates (-r 3):

node$ echo "COORD_FILE    HGDP_700_chr22.RefPC.coord >> test.conf
node$ laser -p test.conf -r 3 -o test
====        LASER: Locating Ancestry from SEquence Reads        ====
====          Version 2.04, Last updated on Jan/11/2017         ====
====          (C) 2013-2017 Chaolong Wang, GNU GPL v3.0         ====
Started at: Mon Jul 10 16:55:24 2017

6 individuals in the SEQ_FILE.
9608 loci in the SEQ_FILE.
700 individuals in the GENO_FILE.
9608 loci in the GENO_FILE.
700 individuals in the COORD_FILE.
8 PCs in the COORD_FILE.


Mon Jul 10 16:55:25 2017
Reading reference PCA coordinates ...

Mon Jul 10 16:55:25 2017
Analyzing sequence samples ...
Results for the sequence samples are output to:
'test.SeqPC.coord' (mean across 3 repeated runs)
'' (standard deviation across 3 repeated runs)

Finished at: Mon Jul 10 16:55:37 2017
Total wall clock time: 13.5122 seconds.

The graph below is an illustration of the results (plotting the 6 unknown samples on top of the colored reference data):

laser example

There are two utilities to create the genotype and site files:

Tool Descriptiont
vcf2geno convert a VCF file to a genotype and site file used together with samtools pileup to produce .seq file
Batch job on Biowulf

Create a batch script similar to the following example:

#! /bin/bash
# this file is laser.batch

module load laser/2.04 || exit 1

# create the config file and run the PCA on the reference panel

echo "GENO_FILE      HGDP_700_chr22.geno" >  test.conf
echo "SEQ_FILE       HapMap_6_chr22.seq"  >> test.conf
echo "DIM            8" >> test.conf
laser -p test.conf -pca 1 -o HGDP_700_chr22

# now run the analysis in two parallel chunks (Sequences 1-3 in the first
# chunk; sequences 4-6 in the second chunk)
echo "COORD_FILE     HGDP_700_chr22.RefPC.coord" >> test.conf
laser -p test.conf -r3 -x 1 -y 3 -o out.1-3 &
laser -p test.conf -r3 -x 4 -y 6 -o out.4-6 &

Submit to the queue with sbatch:

biowulf$ sbatch --mem=10g --cpus-per-task=2 laser.batch