SeqShop: Estimates of Genetic Ancestry Practical, May 2015

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Main Workshop wiki page: SeqShop: May 2015

See the tutorial slides for an introduction of the LASER analysis workflow, input/output file formats, and usage of the LASER software.

The main purpose of this page is to provide step-by-step command lines for using LASER to estimate ancestry of 6 targeted sequenced samples (2 HapMap trios) in a principal component space generated using genome-wide SNP data from the Human Genome Diversity Project (HGDP). The HGDP reference panel contains genotype data across 632,958 autosomal loci for 938 individuals from 53 populations worldwide.

For more details about the options and usage of LASER, please read the manual.

LASER workflow

LASER workflow
LASER workflow

HGDP reference panel

HGDP populations
HGDP populations


This section is specifically for the SeqShop Workshop computers.

If you are not running during the SeqShop Workshop, please skip this section.

Login to the seqshop-server Linux Machine

This section will appear redundantly in each session. If you are already logged in or know how to log in to the server, please skip this section

  1. Login to the windows machine
    • The username/password for the Windows machine should be written on the right-hand monitor
  2. Start xming so you can open external windows on our Linux machine
    • Start->Enter "Xming" in the search and select "Xming" from the program list
    • Nothing will happen, but Xming was started.
    • View Screenshot
    • Xming.png

  3. Open putty
    • Start->Enter "putty" in the search and select "PuTTY" from the program list
    • View Screenshot
    • PuttyS.png

  4. Configure PuTTY in the PuTTY Configuration window
    • Host Name:
    • View Screenshot
    • Seqshop.png

    • Setup to allow you to open external windows:
      • In the left pannel: Connection->SSH->X11
        • Add a check mark in the box next to Enable X11 forwarding
        • View Screenshot
        • SeqshopX11.png

    • Click Open
    • If it prompts about a key, click OK
  5. Enter your provided username & password as provided

You should now be logged into a terminal on the seqshop-server and be able to access the test files.

  • If you need another terminal, repeat from step 3.

Login to the seqshop Machine

So you can each run multiple jobs at once, we will have you run on 4 different machines within our seqshop setup.

  • You can only access these machines after logging onto seqshop-server

3 users logon to:

ssh -X seqshop1

3 users logon to:

ssh -X seqshop2

2 users logon to:

ssh -X seqshop3

2 users logon to:

ssh -X seqshop4

Prerequisite Tutorials

This tutorial uses samtools from GotCloud, as well as example data downloaded in the Sequence Mapping & Assembly tutorial, so if you have not already installed GotCloud and the tutorial data in a previous tutorial, please do so now: Tutorial Setup

Setup your run environment

Environment variables will be used throughout the tutorial.

We recommend that you setup these variables so you won't have to modify every command in the tutorial.

  1. Point to where you installed GotCloud
  2. Point to where you installed the seqshop files
  3. Point to where you want the output to go
Using bash (replace the paths below with the appropriate paths):
export GC=~/seqshop/gotcloud
export SS=~/seqshop/example
export OUT=~/seqshop/output
Using tcsh (replace the paths below with the appropriate paths):
setenv GC ~/seqshop/gotcloud
setenv SS ~/seqshop/example
setenv OUT ~/seqshop/output
  • Additional variables for Ancestry:
    • Using bash (replace the paths below with the appropriate paths):
    • export LASER=$OUT/ancestry/LASER-2.01
      export REF=$SS/ancestry/ref
      export HGDP=$SS/ancestry/HGDP
      export BAM=$SS/ancestry/BAM
    • Using tcsh (replace the paths below with the appropriate paths):
    • setenv LASER $OUT/ancestry/LASER-2.01
      setenv REF $SS/ancestry/ref
      setenv HGDP $SS/ancestry/HGDP
      setenv BAM $SS/ancestry/BAM

Getting started

Create a working directory:

mkdir -p $OUT/ancestry
cd $OUT/ancestry

Download and decompress software package:

tar xzvf LASER-2.01.tar.gz

Preparing input files for LASER

Step 0: vcf --> geno

This step prepares the reference panel by converting a VCF genotype file to a GENO file. We will skip this step and use a ready-to-use HGDP reference panel. A typical command to run the vcf2geno tool is given in the file "./LASER-2.01/vcf2geno/":

# cd ./LASER-2.01/vcf2geno/
# ./vcf2geno --inVcf exampleVCF/example.vcf.gz --updateID test.updateId --out test

Step 1: bam --> pileup

This step uses samtools to generate pileup files from bam files.

  • The BAMs provided as part of the download are chr22 only BAMs. They are used to demonstrate how to run this step.
  • Pileup files for the whole genome BAMs are provided with the download and will be used in the next step.
  • You only need to try one of these.
  $GC/bin/samtools mpileup -q 30 -Q 20 -f $REF/human.g1k.v37.fa -l $HGDP/HGDP_938.bed $BAM/121101035.recal.bam > 121101035.recal.pileup
# $GC/bin/samtools mpileup -q 30 -Q 20 -f $REF/human.g1k.v37.fa -l $HGDP/HGDP_938.bed $BAM/121101043.recal.bam > 121101043.recal.pileup 
# $GC/bin/samtools mpileup -q 30 -Q 20 -f $REF/human.g1k.v37.fa -l $HGDP/HGDP_938.bed $BAM/121101050.recal.bam > 121101050.recal.pileup
# $GC/bin/samtools mpileup -q 30 -Q 20 -f $REF/human.g1k.v37.fa -l $HGDP/HGDP_938.bed $BAM/121101052.recal.bam > 121101052.recal.pileup
# $GC/bin/samtools mpileup -q 30 -Q 20 -f $REF/human.g1k.v37.fa -l $HGDP/HGDP_938.bed $BAM/121101415.recal.bam > 121101415.recal.pileup
# $GC/bin/samtools mpileup -q 30 -Q 20 -f $REF/human.g1k.v37.fa -l $HGDP/HGDP_938.bed $BAM/121101861.recal.bam > 121101861.recal.pileup

We use -q 30 and -Q 20 to exclude reads that have mapping quality score lower than 30 or base quality score lower than 20.

Step 2: pileup --> seq

In this step, we will generate a file called "hapmap_trios.seq", containing the information of 6 samples. It takes about 30 seconds to run. We will use the pre-generated pileup files in the $BAM folder.

  • These pre-generated pileup files are for the whole genome of all 6 samples
python $LASER/pileup2seq/ \
-m $HGDP/ \
-b $BAM/AMD_roi_1-based.bed \
-i $BAM/AMD_hapmap_trios_id.txt \
-o hapmap_trios \
$BAM/121101035.recal.pileup \
$BAM/121101043.recal.pileup \
$BAM/121101050.recal.pileup \
$BAM/121101052.recal.pileup \
$BAM/121101415.recal.pileup \

In the above command, -b provides the targeted regions to exclude and -i specifies alternative IDs for the BAM files to be used in the .seq file (including popID and indivID). -b and -i are optional.

Estimating ancestry coordinates

Step 0: Generate the reference ancestry space

LASER can perform principal components analysis (PCA) on genotype data of the reference panel to generate a reference ancestry space.

# $LASER/laser -g $HGDP/HGDP_938.geno -pca 1 -k 30 -o HGDP_938

The above command takes ~20 minutes to finish. We will skip this step, and use a set of reference ancestry coordinates that have been generated in the file $HGDP/HGDP_938.RefPC.coord. View the reference coordinates:

less -S $HGDP/HGDP_938.RefPC.coord

Step 1: Estimate ancestry for sequenced samples

Submit two jobs to place sequenced samples into the reference ancestry space:

$LASER/laser -g $HGDP/HGDP_938.geno -c $HGDP/HGDP_938.RefPC.coord -s hapmap_trios.seq -K 20 -k 4 -x 1 -y 3 -o hapmap_trios.1-3 &
$LASER/laser -g $HGDP/HGDP_938.geno -c $HGDP/HGDP_938.RefPC.coord -s hapmap_trios.seq -K 20 -k 4 -x 4 -y 6 -o hapmap_trios.4-6 &

The first job will process samples 1 to 3 and the second job will processed samples 4 to 6. Each sequenced sample will be projected from a 20-dimensional PCA space onto a 4-dimensional reference ancestry space. The running time is ~10 minutes for processing 3 samples in each job.

Step 2: Combine results

Results from previous step will be output to two files "hapmap_trios.1-3.SeqPC.coord" and "hapmap_trios.4-6.SeqPC.coord". Here we simply concatenate the two files while skipping the header line of the second file.

cp hapmap_trios.1-3.SeqPC.coord hapmap_trios.SeqPC.coord
more +2 hapmap_trios.4-6.SeqPC.coord >> hapmap_trios.SeqPC.coord

View the results:

less -S hapmap_trios.SeqPC.coord

The results should look like below (results will vary slightly):

popID  indivID  L1      Ci         K     t          PC1        PC2         PC3         PC4
YRI    NA19238  78386   0.170864   20    0.999688   467.989    -210.294    -14.1729    -14.4204
CEU    NA12892  85486   0.185973   20    0.999723   10.796     199.095     -9.90387    -21.4534
CEU    NA12891  87588   0.190442   20    0.99973    2.04224    196.07      -19.5705    -12.8022
CEU    NA12878  83213   0.181748   20    0.999711   4.34591    199.861     -12.4825    -22.6281
YRI    NA19239  87564   0.193424   20    0.999734   474.464    -215.96     -9.02921    -19.7372
YRI    NA19240  95866   0.213874   20    0.999748   469.914    -214.94     -14.9923    -13.6559

Visualizing results

Example R codes are available in ./LASER-2.01/plot/. Let's copy the folder to current working directory:

cp -r $LASER/plot/ ./

Go to the plot folder and run the script to plot results:

cd plot
Rscript plotHGDP.r $HGDP/HGDP_938.RefPC.coord ../hapmap_trios.SeqPC.coord

A figure named "Results_on_HGDP.pdf" will be generated. Visualize the figure:

evince Results_on_HGDP.pdf &

We expect to see the following figure, in which 3 CEU samples cluster with HGDP Europeans and 3 YRI samples cluster with HGDP Africans:

LASER results
LASER results


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