Understanding
Human Y Chromosome
Robert Yu
2014
Human Genome
“the complete set of genetic information for humans…as DNA sequences within the 23 chromosome pairs in cell nuclei and in a small DNA molecule found within individual mitochondria.”
– Human Genome, wikipedia [http://en.wikipedia.org/wiki/Human_genome]
Human chromosomes contain DNA being ~3.1 billion bp, 20K‐25K genes. Human mitochondrial DNA: ~16,600 bp, 37 genes
not yet
•
Genome‐wide Association Studies (GWAS)
“…also known as whole genome association study…is an examination of many common genetic variants in different individuals to see if any variant is associated with a trait. ” —Genome‐wide association study, wikipedia, [http://en.wikipedia.org/wiki/Genome‐wide_association_study]
•
A typical report of GWAS contains results only covering autosomal chromosomes: where are X, Y, mt chromosomes?
An illustration of a Manhattan plot depicting several strongly associated risk loci. Each dot represents a SNP, with the X‐axis showing genomic location and Y‐axis showing association level. Ref: http://en.wikipedia.org/wiki/Genome‐wide_association_study
Genetic Studies of Mendelian Trait
•
•
Austrian monk, Gregor Mendel announced his discovery of Mendel’s Principles of Heredity or Mendelian Inheritance on March 8, 1865.
Example:
–
–
–
–
•
•
The pea plant has two alleles, B and b, of a flower color gene. Randomly, the B (or b) was from sperm and b (or B) from egg of grandparents.
The current parent, pollen (father) has Bb and pistil (mother) Bb, too.
Randomly inherited, the 4 offspring (children) have one BB, 2 Bb’s and 1 bb.
The 3rd Mendel’s law says “Some alleles are dominant while others are recessive; an organism with at least one dominant allele will display the effect of the dominant allele”.
This 3rd law laid foundation of genetic models in GWAS: assuming b is associated with a trait (disease)
Additive model: a trait (disease) will be enhanced if an individual has two trait‐associated
alleles, bb, comparing with individuals who have only one copy, Bb.
– Dominant model: a trait (disease) will appear whenever an individual carries one or two copies of a trait‐associated allele, b or bb.
– Recessive model: a trait (disease) will not appear only when an individual carries TWO copies of a trait‐associated allele, only bb.
Note: sometimes this trait‐associated allele could be found an actual causal allele of a disease (trait).
–
Ref: “Mendelian inheritance” at http://en.wikipedia.org/wiki/Mendelian_inheritance
Genetic markers, e.g. SNPs, on chromosomes 1‐22 can fit Mendelian inheritance principles well but not so well or not at all for the ones on chromosomes X, Y and mt.
We discussed the case on chromosome X last year. Now we focus on Chromosome Y.
"We used to think most of the Y chromosome was junk," said Dr. Martin Bialer, a medical geneticist with North Shore‐LIJ Health System in Great Neck, N.Y.
"But … there could be something on the chromosome that's important in cancer prevention," Bialer said. "What that is, is unclear.“
April 28, 2014
First let us look at a few research publications on Y chromosome.
•
•
•
•
SNP from blood
Age: 70.7‐83.6
1153 male samples
Association LOY
Review of some basic biology may help us catch the picture.
A Set of Human Chromosomes
Ref: http://en.wikipedia.org/wiki/Human_genome
Sex Chromosomes
Ref: http://phylogenous.wordpress.com/2010/07/19/y‐chromosome‐ii‐what‐is‐even‐on‐it/
Chromosomes 1 – 22: autosomal chromosomes Chromosomes X and Y: allosomal chromosomes (sex determining chromosomes)
“Putative protein” = predicted proteins from sequencing data or other information. “Confirmed protein” = real protein seen.
“Length” = bp x 0.34 nanometers (distance between base pair) “Variations” = unique DNA seq changes so far identified by Ensembl (Jul 2012); this #’ll be up as more personal genomes are examined. “miRNA” = microRNA, functions as a post‐transcriptional regulator of gene expression. “rRNA” = ribosomal RNA, critical in the synthesis of proteins. “snRNA” = small nuclear RNA, regulating transcription factors. “snoRNA” = small nucleolar RNA, primarily functions in guiding chemical modifications to other RNA molecules. “pseudogenes” = inactive copies of protein coding genes, often generated by gene duplication. Gene duplication is a step of new genetic material being added.
“ncRNA” = noncoding RNA, roles as epigenetic elements in protein synthesis and RNA processing, e.g. tRNA, rRNA, miRNA and others.
Data source: Ensembl genome browser release 68, July 2012
Human Y Chromosome
• ~58 million base pairs, 2% of total DNA
• 200+ genes, at least 72 being protein coding
• 5% of Y chromosome are PAR1 and PAR2, capable of being recombined with X’s homologues
• 95% of Y are NRY, non‐recombining region of Y chromosome. • SNPs from NRY were used to trace direct paternal ancestral lines.
Ref: Ensembl Human MapView release 43". February 2014. Retrieved 2007‐04‐14.
Y chromosome
• The DNA in the human Y chromosome is composed of about 59 million base pairs.
• The Y chromosome is passed only from father to son. Mito DNA: only from mother to daughter.
• With a 30% difference between humans and chimpanzees, the Y chromosome is one of the fastest evolving parts of the human genome.
• To date, over 200 Y‐linked genes have been identified.[3] All Y‐linked genes are expressed and (apart from duplicated genes) hemizygous (present on only one chromosome) except in the cases of aneuploidy such as Klinefelter's Syndrome (47,XXY) or XXYY syndrome. (See Y linkage.)
http://en.wikipedia.org/wiki/Y_chromosome
Evolution of Chromosomes X and Y
XCR/YCR: X or Y conserved region
SRY: sex determining region Y
XAR/YAR: X or Y added region
PAR: pseudoautosomal region
MSY: male specific region
Ref: Linda Hellborg, 2004, “Evolutionary Studies of the Mammalian Y Chromosome”
http://www.diva‐portal.org/smash/get/diva2:164238/FULLTEXT01.pdf&sa=U&ei=0‐ZOU‐HXOcOGtAbntYGgCQ&ved=0CDwQFjAF&usg=AFQjCNFIgeQzfGnYvC9_I0c7eHYJaoHCQA
Million years
Glossary:
Fundamental Tasks of GWAS
association ?
Phenotype
• Diseases
• Traits of interest
• Behavior
Sequencing based
Genomic elements
• DNA
• RNA
• Epigenetic markers
SNP
DNA
de novo mutation
AGA C C T T
A C AG C T T
AGAG C T A
A C AG C T A
SNP1
SNP2
Allele
C ,G
A,G
Genotype CG
AA
TT
Sequence fragment
A mutation is defined as any change in a DNA sequence away from normal. This implies there is a normal allele that is prevalent in the population and that the mutation changes this to a rare and abnormal variant.
genetic models
(minor: C)
1 – additive
1 – dominant
0 – recessive
(minor: T)
0 – additive
0 – dominant
0 – recessive
2 – additive
1 – dominant
2 – recessive
1.
2.
3.
Single allele based
Genotype based
Haplotype based
Haplotype
(SNP1 + SNP2)
GT vs GA (on same strand)
CT vs CA
AGACCTT vs AGAGCTA
HG
a polymorphism is a DNA sequence variation that is common in the population. In this case no single allele is regarded as the standard sequence. Instead there are two or more equally acceptable alternatives.
The arbitrary cut‐off point between a mutation and a polymorphism is 1 per cent.
Ref: Wellcome Trust at http://genome.wellco
me.ac.uk/doc_WTD02
0780.html
Ref: http://humupd.oxfordjournals.org/content/14/4/293/F1.expansion
Basic Biochemistry
Here we see:
• nucleotides, e.g. A, C, G and T
• DNA sequence is the sequential listing of A,C,G and T on one strand.
• The ordered listing of SNPs from one DNA strand is called haplotype.
• A genotype is a pair of nucleotides, e.g. AG or CC, at the same sequencing site (position) but from two different DNA strands of the two chromosomes.
One strand of DNA forms one chromosome. It was descended from one of the two parents.
Another strand of DNA comes from another chromosome, i.e. another parent.
http://novellaqalive2.mhhe.com/sites/dl/free/0071402357/156709/figure56_2.jpg
https://www.msu.edu/course/isb/202/tsao/images/DNA_to_trait2.jpg
Note:
UPE and DPE –
upstream and downstream are promoter elements, influencing gene transcription, regulatory elements.
http://genome.crg.es/courses/Madrid04/exercises/ensembl/
Building Blocks of Proteins: 20 common amino acids
http://lecturer.ukdw.ac.id/dhira/BacterialStructure/Proteins.html
Basic Biology: Cell types and divisions
Meiosis is germ cell division for reproduction.
passing to offspring
Mitosis is somatic cell division for growth.
remain to self
http://mscoppinsbio.wikispaces.com/file/view/meiosis‐and‐mitosis‐comparison.gif/129266029/527x477/meiosis‐and‐mitosis‐comparison.gif
Glossary: Chromosome Banding Pattern and Nomenclature
according to International System for Cytogenetic Nomenclature (ISCN)
arm
centromere
region
major Giemsa‐staining band
ban
d additional bands
sub‐band
individual area
Example
Gene “NLGN4X” was reported located at
• Xp22.33, from 6,147,085 to 5,758,678
Gene “NLGN4Y” was reported located at
• Yq11.221, from 166,344,88 to 169,57,538
Ref: AceView, “http://www.ncbi.nlm.nih.gov/IEB/Research/Acembly/av.c
gi?db=human&term=NLGN4X&submit=Go”
Ref: http://www.nature.com/scitable/topicpage/Chromosome‐Mapping‐Idiograms‐302
Source:
Doris Bachtrog and Brian Charlesworth
(2001) “Minireview: Towards a complete sequence of the human Y chromosome”, Genome Biology, 2(5): reviews 1016.1‐
1016.5
Y‐STR: short tandem repeat (STR) on the Y‐chromosome.
• short tandem repeats (STRs), are repeating sequences of 2‐5 base pairs of DNA
• Y‐STR Analysis: The likelihood of two people having the same number of repeated sequences is extremely small, and becomes even smaller the more regions that are analyzed. This makes up the basis of short tandem repeat analysis.
Y‐Chromosome STRs: important genetic markers on Y chromosome
Source: http://www.cstl.nist.gov/div831/strbase/ystr_fact.htm
Example from FamilyTreeDNA
Source: https://www.familytreedna.com/public/Haplogroup_A/default.aspx?section=yresults
Y‐STR positions
Ref: http://www.cstl.nist.gov/div831/strbase/ystrpos1.htm
Haplogroup
•
•
•
•
•
•
A haplogroup is a group of similar haplotypes that share a common ancestor having the same single nucleotide polymorphism (SNP) mutation in all haplotypes. It is possible to predict a haplogroup from haplotypes. An SNP test confirms a haplogroup. Haplogroups are assigned letters of the alphabet, and refinements consist of additional number and letter combinations, for example R1b1. Y‐chromosome and mitochondrial DNA haplogroups have different haplogroup designations. Haplogroups pertain to deep ancestral origins dating back thousands of years.
The Y‐Chromosome Consortium (YCC) has a naming system naming major Y‐DNA haplogroups from A through T.
http://en.wikipedia.org/wiki/Haplogroup
http://dnaconsultants.com/images/links/49‐conversion.pdf
Y‐chromosome DNA haplogroups
and evolutionary tree
http://en.m.wikipedia.org/wiki/Haplogroup
Glossary: Y‐chromosomal Adam
• In human genetics, Y‐chromosomal Adam (Y‐MRCA) is a hypothetical name given to the most recent common ancestor (MRCA) from whom all currently living people are descended patrilineally (tracing back only along the paternal or male lines of their family tree). However, the title is not permanently fixed on a single individual (see below).
http://en.wikipedia.org/wiki/Y‐chromosomal_Adam
Glossary: Mitochondrial Eve
• Mitochondrial Eve refers to the matrilineal most recent common ancestor (MRCA) of all currently living anatomically modern humans, who is estimated to have lived approximately 100,000–200,000 years ago.
Through random drift or selection lineage will trace back to a single person. In this example over 5 generations, the colors represent extinct matrilineal lines and black the matrilineal line descended from the MRCA.
Ref: http://en.wikipedia.org/wiki/Most_recent_common_ancestor
http://en.wikipedia.org/wiki/Mitochondrial_Eve
MtDNA‐MRCA‐generations‐EvolutionCC
Y‐chromosome DNA haplogroups and markers http://www.phylotree.org/Y/tree/index.htm
Y‐chromosome DNA haplogroups and markers Source: http://www.phylotree.org/Y/marker_list.htm
Source: http://www.yfull.com/tree/CT/
Based on ISOGG v9.29 at 2 March 2014 and YFull Experimental YTree v2.25 at 14 October 2014; © 1000 Genomes Project © HGDP Project STR and SNP
• A STR testing usually yields results of a “number”, which is the counts of the repeats in the DNA segment. This pattern in the segment is called haplotype.
• Introductory level of STR testings includes 37‐marker and 67‐marker tests. Advanced level provides testing to 111 or more markers.
• SNP testing usually reports a result of “‐” or “+”, representing absence or presence of a mutation. Results of SNP testing determine a person’s haplogroup.
• SNP‐based haplogroup correlates with STR‐based haplotype, in terms of tracing evolutionary path.
http://dgmweb.net/DNA/General/DNA‐Haplo‐text‐page.html
Schematic Representation of Formation of Haplogroups on Human Y‐chromosome MRCA‐A
HG‐A1
MRCA‐Aa
HG‐A1a
HG‐A1B...n
“All men carrying mutation A form a single haplogroup, and all … mutation B are part of this haplogroup…”
“… each mutation defines a set of specific Y chromosomes called a haplogroup.”
(http://en.wikipedia.org/wiki/Haplogroup)
Public Databases
http://www.cstl.nist.gov/div831/strbase/y_strs.htm
Public Databases
http://www.usystrdatabase.org/
A simple practical case
•
•
•
•
•
•
•
•
•
Discovery group: male (white) cohort: 883 cases and 445 controls
Contrast group: female (white) cohort: 526 cases and 1073 controls
Contrast‐exploratory cohorts: male (AA) 428:169, female (AA) 253:339.
1481 SNPs (17 homologues genes on X) 480 SNPs (34 genes on Y only)
263 SNPs (PAR1 and PAR2 regions – recombinant regions, on both X and Y) PLINK: AD ~ age + [c1 … c10]PCA; • PCA was performed only on Chr 1‐22, using EIGENSTRAT
• Allelic frequency comparison
• Logistic regression Multitesting correction was done using an adjusted Bonferroni inSNPSpD
• The corrected significance levels were set at 1.3 x 10‐4 in White and 1.0 x 10‐4 for AA.
Power analysis was using pwr in R.
Non‐sex Chromosomes Processing in PLINK
2 Pseudoautosomal Regions
The location of PAR1 and PAR2 on GRCh38 are:
Chr
PAR1
PAR2
Y
X
10,000‐2,781,479 10,000‐2,781,479 56,887,902‐57,217,415 155,701,382‐156,030,895
Ref: • http://genome‐euro.ucsc.edu/cgi‐bin/hgGateway
• http://www.ncbi.nlm.nih.gov/projects/genome/assembl
y/grc/human/
SNPs in allosomal chromosomes
Chr
Counts
Starting
Ending
----------------------------------------------------------------23 (X)
18,055
2,700,157
154,916,845
24 (Y)
1,409
2,655,180
59,032,197
25 (XY)
473 62,321 - 2,697,868
154,939,018 - 155,236,747
-----------------------------------------------------------------
Example SNP Data: no Chr
SNP
BP
Chr XY data ‐ Beginning
1
2
no
Data
GSGT Version
1.8.4
Processing Date 8/26/2011 2:59 PM
Content
HumanOmniExpress12v1_H.bpm
Num SNPs
730,525
Total SNPs
730,525
Num Samples
1,728
Total Samples
1,728
The location of PAR1 and PAR2 on GRCh38
Chr
PAR1
PAR2
-------------------------------------------------Y
10,000-2,781,479 56,887,902-57,217,415
X
10,000-2,781,479
155,701,382-156,030,895
‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐‐
no
Chr
SNP
BP
1
2
3
4
5
6
7
Chr X data ‐ Beginning
1
2
16
17
18
19
20
21
22
23
24
25
26
23 rs5939319
2,700,157 8
23 rs1419931
2,703,633 9
data omitted
23 rs1905995
2,778,526 23
23 rs17330993
2,779,749
23 rs5939137
2,783,555
23 rs5939382
2,787,455
23 rs5982603
2,788,707
23 rs5939384
2,789,848
23 rs12011788
2,792,160
23 rs6567674
2,794,461
23 rs211665
2,802,368
23 rs211666
2,802,568
23 rs11796830
2,811,185 24
25
data omitted
3912
23 rs10126493 28,762,640
data omitted
3916 23 rs7888309
28,789,883
data omitted
3920 23 rs4633214
28,823,041
3921 23 rs1384575
28,841,156
data omitted
7614 23 rs4384157
58,483,247
7615 23 rs9778500
61,694,576
data omitted
18041 23 rs28582039 154,668,682
data omitted
18055 23 rs669237
154,916,845
Ending
25 rs28503286
62,321
25 rs6423165
169,805
data omitted
Chr
SNP
BP
Chr Y data ‐ Beginning
380 25 rs17808254
2,642,269
24 rs11575897 2,655,180 381 25 rs312259
2,658,299
24 rs2534636
2,657,176 382 25 rs312257
2,658,698
24 rs35840667 2,661,306
continue
24 rs2253109
2,661,694
24 rs35067692 2,663,685
24 rs2058276
2,668,456 383 25 rs35193207
2,665,647
data omitted
24 rs13303871 2,679,100
continued
394 25 rs2534634
2,697,868
24 rs28813670 2,703,038
24 rs11799203 2,705,854
data omitted
24 rs13304723 2,810,628
continued
24 rs13303695
24 rs11799194
2,810,629
2,818,883
continued
data omitted
1403 24 rs9785925 28,792,268
data omitted
1407 24 rs9786224 28,817,458
continued
1408 24 rs9786720 58,883,690
1409 24 rs28715603 59,032,197
Ending
395 25 rs28814596 154,939,018
data omitted
473 25 rs2981828 155,236,747
Ending
SNPs in allosomal chromosomes
Chr
Counts
Starting
Ending
----------------------------------------------------------------23 (X)
18,055
2,700,157
154,916,845
24 (Y)
1,409
2,655,180
59,032,197
25 (XY)
473 62,321 - 2,697,868
154,939,018 - 155,236,747
-----------------------------------------------------------------
Haplogroup Markers (SNPs) matching
List of markers included in the minimal reference tree (partial)
Position relative Marker
Alias(es)
rsSNP ID
Mutation
to GRCh37
Z142
S211
‐
1,519,693
A>G
M236
‐
2,649,696
G>C
M176
SRY465; Page63
rs11575897
2,655,180
G>A
SRY10831 SRY1532; Page65
rs2534636
2,657,176 T>C; C>T
CTS6
Z2469; S3403
‐
2,657,349
T>C
M6529
rs113717750
2,657,411
G>A
M177
SRY9138
rs369688174
2,658,869
C>T
M40
SRY4064; SRY8299
rs9786608
2,663,943
C>T
Z5865
‐
2,667,783
C>T
Z1828
CTS15
‐
2,669,716
C>T
Z2220
‐
2,687,198
G>C
Z161
‐
2,696,497
C>G
P305
rs72625368
2,710,154
G>A
M7104
rs112887592
2,711,408
C>G
CTS94
‐
2,726,402
T>G
M130
RPS4Y711; Page51
rs35284970
2,734,854
C>T
M8495
rs368790958
2,736,732
T>G
M386
CTS117
‐
2,738,986
C>T
M4
rs3895
2,744,628
A>G
M406
PF3285
‐
2,749,995
T>G
M410
rs371079691
2,751,678
A>G
Z5857
‐
2,759,285
C>G
L1085
‐
2,790,726
T>C
V244
rs112298449
2,798,459
C>T
F11
KL4
rs17276393
2,815,303
C>G
M324
rs13447361
2,821,786
G>C
L1086
‐
2,826,312
A>T
P201
JST021354
rs2267801
2,828,196
T>C
JST021355
rs2267802
2,828,425
A>G
DF13
S521; CTS241
rs373989227
2,836,431
A>C
M7583
rs374589940
2,844,095
G>T
Z5899
‐
2,852,640
T>C
Z5867
‐
2,866,232
C>T
M347
‐
2,877,479
A>G
http://www.phylotree.org/Y/marker_list.htm
Major clade
R
B
O
A4=BCDEF; R
R
B
M
E
H
J
J
I
A1'2'3'4
B
D
C
B
C
M
G
J
H
A0'1'2'3'4
B
O
O
A00
O
D
R
B
C
H
C
no Chr
SNP
BP
Chr XY data ‐ Beginning
1
2
no
no
Chr
SNP
BP
1
2
3
4
5
6
7
Chr X data ‐ Beginning
1
2
16
17
18
19
20
21
22
23
24
25
26
23 rs5939319
2,700,157 8
23 rs1419931
2,703,633 9
data omitted
23 rs1905995
2,778,526 23
23 rs17330993
2,779,749
23 rs5939137
2,783,555
23 rs5939382
2,787,455
23 rs5982603
2,788,707
23 rs5939384
2,789,848
23 rs12011788
2,792,160
23 rs6567674
2,794,461
23 rs211665
2,802,368
23 rs211666
2,802,568
23 rs11796830
2,811,185 24
25
data omitted
3912
23 rs10126493 28,762,640
data omitted
3916 23 rs7888309
28,789,883
data omitted
3920 23 rs4633214
28,823,041
3921 23 rs1384575
28,841,156
data omitted
7614 23 rs4384157
58,483,247
7615 23 rs9778500
61,694,576
data omitted
18041 23 rs28582039 154,668,682
data omitted
18055 23 rs669237
154,916,845
Ending
25 rs28503286
62,321
25 rs6423165
169,805
data omitted
Chr
SNP
BP
Chr Y data ‐ Beginning
380 25 rs17808254
2,642,269
24 rs11575897 2,655,180 381 25 rs312259
2,658,299
24 rs2534636
2,657,176 382 25 rs312257
2,658,698
24 rs35840667 2,661,306
continue
24 rs2253109
2,661,694
24 rs35067692 2,663,685
24 rs2058276
2,668,456 383 25 rs35193207
2,665,647
data omitted
24 rs13303871 2,679,100
continued
394 25 rs2534634
2,697,868
24 rs28813670 2,703,038
24 rs11799203 2,705,854
data omitted
24 rs13304723 2,810,628
continued
24 rs13303695
24 rs11799194
2,810,629
2,818,883
continued
data omitted
1403 24 rs9785925 28,792,268
data omitted
1407 24 rs9786224 28,817,458
continued
1408 24 rs9786720 58,883,690
1409 24 rs28715603 59,032,197
Ending
395 25 rs28814596 154,939,018
data omitted
473 25 rs2981828 155,236,747
Ending
Distribution of 1409 SNPs along Y Chr
91 SNPs (of 1409) that matched HG listing.
1409 SNPs rs1558843
M306
Genotype data in diploid (PLINK) format
FID
WEI0002
WEI0004
WEI0005
WEI0007
WEI0010
WEI0011
WEI0012
WEI0014
WEI0015
WEI0016
WEI0017
WEI0018
WEI0019
WEI0023
WEI0027
WEI0028
WEI0029
WEI0030
WEI0031
WEI0032
IID
WEI0002
WEI0004
WEI0005
WEI0007
WEI0010
WEI0011
WEI0012
WEI0014
WEI0015
WEI0016
WEI0017
WEI0018
WEI0019
WEI0023
WEI0027
WEI0028
WEI0029
WEI0030
WEI0031
WEI0032
PID MID Sex Pheno 1
2
3
4
5
6
7
8
9
10
0
0 1
2G G G G G G A A 0 0A A G G A A G G G G
0
0 1
2G G G G G G A A G A G G G G A A A A G G
0
0 1
2G G G G G G A A 0 0G G G G A A A A G G
0
0 1
2G G G G G G A A G A G G G G A A A A G G
0
0 1
2G G G G G G A A 0 0G G G G A A A A G G
0
0 1
2G G G G G G A A G A G G G G A A A A G G
0
0 1
2G G G G G G A A G A G G G G A A A A G G
0
0 1
2G G G G G G A A 0 0G G G G A A A A G G
0
0 1
2G G G G G G A A 0 0G G G G A A A A G G
0
0 1
2G G G G G G A A 0 0G G G G A A A A G G
0
0 1
2G G G G G G A A G A G G G G A A A A G G
0
0 1
2G G G G G G A A G A G G G G A A A A G G
0
0 1
2G G G G G G A A 0 0G G G G A A A A G G
0
0 1
2G G G G G G A A 0 0G G G G A A A A G G
0
0 1
2G G A A G G A A G A G G G G A A A A G G
0
0 1
2G G G G G G A A G A G G G G A A A A G G
0
0 1
2G G G G G G A A 0 0G G G G A A A A G G
0
0 1
2G G G G G G A A 0 0G G G G A A A A G G
0
0 1
2G G G G G G A A G A G G G G A A A A G G
0
0 1
2G G G G G G A A G A G G G G A A A A G G
11
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
12
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
13
A
C
A
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
A
C
A
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
14
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
15
G
G
G
G
G
G
G
G
G
G
G
G
G
G
A
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
A
G
G
G
G
G
16
G
G
G
A
G
A
A
G
G
G
G
A
G
G
G
G
G
A
G
G
G
G
G
A
G
A
A
G
G
G
G
A
G
G
G
G
G
A
G
G
17
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
18
C
A
C
A
A
A
A
A
A
A
A
A
A
A
C
A
A
A
A
A
C
A
C
A
A
A
A
A
A
A
A
A
A
A
C
A
A
A
A
A
19
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
20
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
21
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
0A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
22
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
23
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
24
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
25
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
26
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
27
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
Genotype data in haploid format
WEI0002
WEI0004
WEI0005
WEI0007
WEI0010
WEI0011
WEI0012
WEI0014
WEI0015
WEI0016
WEI0017
WEI0018
WEI0019
WEI0023
WEI0027
WEI0028
WEI0029
WEI0030
WEI0031
WEI0032
GGGAXAGAGGCAAGGGGCAXAGGAGAGAAAGGAGGAAAGGGAAAAAGGGGGAGGGAGTGAAAAACGCAGGAGAGGAGGAGCAAGCGGAGAA
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCAAGGGGCAXAGGAGAGAAAGGAAGAAAGGGAAAAAGAGGGAGGGAGTGAAAAACGCAGGAAAGGAGGAGCAAGCGGAGAA
GGGAXGGAAGCACGGAGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGAAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGAGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGAGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGAGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GAGAXGGAAGCACGAGGCAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAAAAACGCAGGAGAGGAGGAGCAAGAGGAGTC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGAGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGXCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
GGGAXGGAAGCACGGGGAAXAGGAGAGAAAGGAGGAAAGGGAAACAGAGGGAGAGAGTGAGGAAGGCCAGAGAGGAGGAGCAAGAGGAGAC
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
G
Counting “singletons”
Total 881 “singletons” in 1409 SNPs of 1302 samples (batch 1 data set).
singletons without "X"
No SNP_pos label Allele:Counts Total (size)
1
7 <S1> <G:1302>
<sum=1302>
2
40 <S1> <A:1302>
<sum=1302>
3
185 <S1> <G:1302>
<sum=1302>
4
249 <S1> <G:1302>
<sum=1302>
5
266 <S1> <A:1302>
<sum=1302>
6
270 <S1> <A:1302>
<sum=1302>
7
271 <S1> <G:1302>
<sum=1302>
8
282 <S1> <A:1302>
<sum=1302>
9
361 <S1> <A:1302>
<sum=1302>
omitted
38
1139 <S1> <A:1302>
<sum=1302>
39
1212 <S1> <G:1302>
<sum=1302>
40
1236 <S1> <A:1302>
<sum=1302>
41
1261 <S1> <G:1302>
<sum=1302>
42
1312 <S1> <C:1302>
<sum=1302>
43
1347 <S1> <G:1302>
<sum=1302>
44
1374 <S1> <G:1302>
<sum=1302>
45
1389 <S1> <A:1302>
<sum=1302>
46
1393 <S1> <G:1302>
<sum=1302>
singletons with "X"
No SNP_pos label Allele:Count X:Count
1
1 <SX> <G:1293>
<X:9>
2
3 <SX> <A:1291>
<X:11>
3
4 <SX> <G:1294>
<X:8>
4
5 <SX> <A:1292>
<X:10>
5
8 <SX> <C:1294>
<X:8>
6
9 <SX> <G:1292>
<X:10>
7
10 <SX> <A:1292>
<X:10>
8
11 <SX> <G:1292>
<X:10>
9
13 <SX> <C:1294>
<X:8>
10
14 <SX> <G:1293>
<X:9>
11
17 <SX> <G:1294>
<X:8>
12
19 <SX> <A:1292>
<X:10>
13
20 <SX> <T:1294>
<X:8>
omitted
831
1405 <SX> <G:1294>
<X:8>
832
1406 <SX> <A:1294>
<X:8>
833
1407 <SX> <C:1294>
<X:8>
834
1408 <SX> <A:1294>
<X:8>
835
1409 <SX> <G:1268>
<X:34>
Total (size)
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
<sum=1302>
Get GWAS Data Set (370K SNPs)
Examining Sex Effect on a sub‐phenotype
Case – diseased
Control ‐ separate sourced no‐diseased sample
Case – diseased with e.g. HPV
Control ‐ diseased without HPV
Focus on SNPs on Y Chromosome
Extracting SNPs using HaploGroup Markers List
Preliminary Analysis PLINK
‐
Logistic regression adjusted by age or not
Checking Data Narrow Down to a small set of SNPs
‐
overall data set
male
female
non‐diseased 2483
2024
diseased 1685
500
Total 4168
2524
p‐value < 0.0001
sub data set ‐ batch 1
male
female
non‐diseased
976
566
diseased
899
255
Total 1875
821
p‐value < 0.0001
‐
‐
Remove females
Remove genotype with heterozygous
Allelic frequency comparison
Total
4507
2185
6692
male
diseased others
712
diseased HPV
973
Total 1685
p‐value
female
338
162
500
< 0.0001
Total
1542
1154
2696
male
diseased others
343
diseased HPV
556
Total
899
p‐value
female
171
84
255
< 0.0001
overall data set
Total
1050 diseased others
1135
diseased NHPV
2185
Total
sub data set ‐ batch 1
Total
514
diseased others
640
diseased NHPV
1154
Total
male
1386
299
1685
p‐value
female
408
92
500
0.7371
Total
1794
391
2185
male
758
141
899
p‐value
female
205
50
255
0.1369
Total
963
191
1154
Logistic regression "sex" = age, HPV (or NHPV)
Result: Sex may be a factor on HPV ?
batch 1 data set, with diseased and non‐diseased
2182 (1532) samples were used
1733 (1117) samples were used
p‐value
OR
p‐value
OR
95% IC
95% IC
age
<.0001
0.976
0.969
0.984
age
<.0001
0.973
0.965
0.981
hpv
<.0001
0.276
0.214
0.356
nhpv
0.0987
0.747
0.528
1.056
batch 1 data set, with diseased only
1154 (899 males) samples were used
1154 (899 males) samples were used
95% IC
95% IC
p‐value
OR
p‐value
OR
age
0.246
0.992
0.98
1.005
age
0.9295
0.999
0.987
1.012
hpv1
<.0001
0.295
0.219
0.397
nhpv1
0.138
1.314
0.916
1.885
Example Analysis (1)
•
•
•
Retrieve the SNP list from the Haplogroup Marker list, total 338 rsIDs.
91 of 338 rsIDs were matched in the data, 1154 (batch1) and 1031 (batch2) samples were available.
Check data for heterozygous, basic QA step.
39 (batch1) and 47 (batch2) of 91 SNPs found het.
–
•
•
To take the advantage of PLINK’s function, run a preliminary analysis, e.g. logistic regression using “PLINK’s genotypic model” setting. A trait‐1 and trait‐2 were selected, in which anyone was previously assigned as case for trait‐1 (or trait‐2) and the rest as controls.
Four SNPs were noticed as significant (here listed is from batch 1 only)
CHR
SNP
BP
A1 TEST NMISS OR
SE
L95
24 rs895530 7963031 A ADD
898 1.564 0.1562 1.152
24 rs9785994 16222561 G ADD
897 1.558 0.1562 1.147
24 rs9785659 18248698 A ADD
899 1.499 0.1458 1.126
24 rs1558843 22750583 C ADD
899 1.578 0.1556 1.163
freq_b1_HN_male_cases freq_b2_HN_male_cases
A1 A2 MAF NCHROBS A1 A2 MAF
A
G
A
C
C
A
G
A
0.3051
0.3055
0.3871
0.3092
898 A
897 G
899 A
899 C
C
A
G
A
0.3092
0.3099
0.4084
0.3134
U95
2.124
2.117
1.995
2.14
STAT
2.864
2.841
2.775
2.93
P
0.004185
0.004504
0.005516
0.003385
HaploGroup Marker Info
Position
NCHROBS Marker Name
Alias(es)
rsSNP ID
Mutation
GRCh37
786 P295
PF5866; S8
rs895530 7,963,031 T>G
784 P331
M1221; PF5911 rs9785994 16,222,561 C>T
786 P311
S128
rs9785659 18,248,698 A>G
785 M306
S1
rs1558843 22,750,583 C>A
map file
ped file
PLINK commad
output
log file
Output from checking heterozygous SNPs in batch 1 and batch 2 data sets
snp 5
snp 6
snp 8
snp 11
snp 12
snp 18
snp 20
snp 22
snp 24
snp 25
snp 29
snp 30
snp 31
snp 32
snp 33
snp 34
snp 35
snp 36
snp 37
snp 38
snp 41
snp 42
snp 43
snp 45
snp 46
snp 47
•
•
•
•
•
•
No_Het_b1 No_Het_b2
311
481
11
1
2
4
10
3
3
7
8
2
2
3
3
6
6
2
3
2
9
5
4
7
14
2
7
2
15
5
2
11
1
4
5
1
4
9
13
2
7
3
5
1
1
13
No
5
6
8
11
12
18
20
22
24
25
29
30
31
32
33
34
35
36
37
38
41
42
43
45
46
47
CHR
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
SNP
rs2071394
rs9786139
rs34555473
rs16981290
rs7892855
rs9786194
rs35617575
rs16980473
rs34043621
rs9786371
rs2032597
rs2032598
rs2032601
rs35285796
rs2032600
rs20320
rs20321
rs34442126
rs2032603
rs2032604
rs8179021
rs2032590
rs9341290
rs2032624
rs2032668
rs2032666
bp
6736154
6753519
6893093
7568568
7879415
9170545
14028148
14159846
14486667
14636457
14847792
14850341
14869076
14871976
14888783
14898163
14902414
14922583
14968527
14969634
15018582
15019613
15020578
15026424
15437333
15437564
A1
G
A
C
A
C
C
C
A
0
A
C
G
0
A
C
A
A
G
G
C
A
C
0
A
0
0
A2
A
G
A
C
A
A
A
G
A
G
A
A
G
G
A
G
G
A
A
A
G
A
A
C
A
G
MAF batch 1 A1 A2 MAF batch 2
NA
0
G A
0
1
0.07675
899 A G 0.08015
786
0.001115 897 0 A
0
775
0
897 0 C
0
785
0.05575
879 C A 0.06041
778
0.3737
899 C A 0.3873
785
0.3548
31
0 0
NA
0
0.04672
899 A G 0.05089
786
0
890 G A
0
779
0.001119 894 0 G
0
784
0.1752
896 C A 0.1802
777
0.003341 898 G A 0.003822 785
0
898 0 G
0
784
0.004459 897 0 G
0
783
0.001117 895 0 A
0
780
0.005574 897 A G 0.001277 783
0.03782
899 A G 0.02554
783
0.003337 899 G A 0.001274 785
0.001112 899 0 A
0
784
0.03007
898 C A 0.03831
783
0.002225 899 A G 0.002554 783
0.001112 899 0 A
0
785
0
897 0 A
0
783
0.3096
898 A C 0.3125
784
0
899 0 A
0
786
0
898 0 G
0
783
snp 48
snp 50
snp 52
snp 53
snp 55
snp 59
snp 60
snp 61
snp 63
snp 64
snp 65
snp 67
snp 68
snp 69
snp 71
snp 77
snp 78
snp 81
snp 82
snp 86
snp 88
snp 89
snp 90
snp 91
sum
No_Het_b1 No_Het_b2
3
13
17
16
18
6
4
1
6
2
6
6
16
1
2
9
6
12
9
2
15
3
5
2
2
1
3
2
8
13
18
8
5
10
2
1
10
4
28
2
474
845
No
48
50
52
53
55
59
60
61
63
64
65
67
68
69
71
77
78
81
82
86
88
89
90
91
CHR
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
24
SNP
rs9786043
rs2032659
rs7892889
rs34893929
rs16980588
rs16980502
rs9786420
rs9786076
rs17316592
rs3897
rs9785702
rs17276338
rs9786283
rs9786111
rs34534058
rs2032629
rs2032612
rs2032617
rs2032648
rs13447357
rs34459399
rs34954951
rs17250535
rs2033003
bp
15472863
15576203
15668070
15999244
16253694
17294958
17398598
17844018
18560005
18571026
18656508
18842841
18907236
19054889
19136822
21865821
21866491
21896261
21904023
22751863
22942897
23292782
23473201
23550924
A1
G
0
G
0
A
A
G
A
0
0
C
0
A
G
G
A
0
0
0
A
G
0
T
A
A2
A
G
A
G
G
G
A
G
A
A
G
C
C
A
A
G
G
C
A
G
A
G
A
C
MAF batch 1 A1 A2 MAF batch 2
0.2962
898 G A 0.3078
783
0
899 0 G
0
781
0.007786 899 G A 0.003841 781
0
899 0 G
0
778
0.002225 899 A G 0.003822 785
0.002227 898 A G 0.003827 784
0.04799
896 G A 0.0535
785
0.3871
899 A G 0.4084
786
0
897 0 A
0
784
0
899 0 A
0
778
0.3746
897 C G 0.4078
748
0
898 0 C
0
779
0.3871
899 A C 0.4089
785
0.3737
899 G A 0.3865
784
0.01763
397 G A 0.01175
766
0.002225 899 A G 0.006402 781
0
899 0 G
0
786
0
896 A C 0.001279 782
0
898 G A 0.005096 785
0.002225 899 0 G
0
786
0.02004
898 G A 0.02163
786
0
898 A G 0.002554 783
0.04983
883 T A 0.05628
764
0.3538
766 A C 0.3127
774
Columns “No_Het_b1” and “No_Het_b2” list the counts of detected heterozygous genotypes corresponding the SNPs in rows among the samples in batches 1 and 2.
Columns in gray representing the info for batch 1 and blue for batch 2.
Columns “batch 1” and “bath 2” next “MAF” (minor allele frequency) represent the number of non‐missing genotypes counted.
Columns “A1” represents the value for minor allele detected in the samples.
Note: MAF calculation was based on PLINK’s tool and it treated Y chromosome different from other autosomal sections, i.e. whenever a heterozygous genotype in Y chromosome is encountered, it treats it automatically as missing, and when the missing reaches over a certain threshold, this SNP will not be calculated. This was exact the case for “snp5” (the first one) in the table.
This is also indicating that those analytical tools in PLINK may or may not be suitable to the data in Y chromosome, without modification.
Example Analysis (2)
Note: what are listed here are only from batch 1 set (males).
original data format
13 54 62 85
A A G G A A C C
C C A A G G A A
A A G G A A C C
C C A A G G A A
C C A A G G A A
snp13
A
C
A
C
C
C C A A G G A A
C C A A G G A A
C
C
simplified format
snp54 snp62
G
A
A
G
G
A
A
G
A
G
A
A
G
G
snp85 FID
IID
C
WEI0002
WEI0002
A
WEI0004
WEI0004
C
WEI0005
WEI0005
A
WEI0007
WEI0007
A
WEI0010
WEI0010
omitted for space saving
A
WEI1690
WEI1690
A
WEI1692
WEI1692
Pheno
2
2
2
2
2
2
2
phenotype info
Age
Sex
HPV
73
1
24
1
67
1
18
1
64
1
60
80
1
1
NHPV
2
1
1
1
1
1
1
1
1
1
2
2
1
1
Counting alleles in cases and controls, and then run Fisher’s exact test
Ratio Exact Test
snp13 missing A C Total A vs ? p‐value
others
1
86 256 343 0.34
HPV
188 368 556 0.51 0.0071595
Total
1
274 624 899
Ratio Exact Test
snp13 missing A C Total A vs ? p‐value
others
1
239 518 758 0.46
NHPV
35 106 141 0.33 0.1124057
Total
1
274 624 899
rs9785994 snp54 missing A G Total
others
2
255 86 343 2.97
HPV
368 188 556 1.96 0.0071681
Total
2
623 274 899
snp54 missing A G Total
others
1
518 239 758 2.17
NHPV
1
105 35 141 3.00 0.1343267
Total
2
623 274 899
rs9785659 snp62 missing A G Total
others
113 230 343 0.49
HPV
235 321 556 0.73 0.0059557
Total
348 551 899
snp62 missing A G Total
others
297 461 758 0.64
NHPV
51 90 141 0.57 0.5117231
Total
348 551 899
rs1558843 snp85 missing A C Total
others
256 87 343 2.94
HPV
365 191 556 1.91 0.0047702
Total
621 278 899
snp85 missing A C Total
others
515 243 758 2.12
NHPV
106 35 141 3.03 0.0923098
Total
621 278 899
rs895530
The 4th SNP, rs1558843, is found located in gene EIF1AY, which has a female (chr X) counter part EIF1AY.
The 4th SNP, rs1558843, is found located in gene EIF1AY, which has a female (chr X) counter part EIF1AY.
SNP, rs1558843, in the human Y‐chromosome phylogeny
• This was just a simple example of analysis running allelic frequency comparison.
• Further analysis of SNP halotypes
may yield more results.
Example: HPV vs “haplotype” (4 SNPs)
"haplotype"
block 1
AGAC
block 2
CAAA
block 3
CAGA
control (freq)
343
86 0.250729
25 0.072886
229 0.667638
case (freq)
556
188 0.338129
44 0.079137
321 0.577338
Partial section of sequence data files
Example Sequencing Data: SNP site length of Y region in 431 VCF files
0
3500
Quality Score
PASS
low_coverage;low_qual
low_VariantReads;low_coverage;low_qual
low_coverage;read_end_ratio;low_qual
low_qual
low_VariantReads;low_coverage
low_VariantReads;low_VariantRatio;read_end_ratio;low_qual
low_VariantReads;low_coverage;read_end_ratio
low_VariantReads;low_coverage;read_end_ratio;low_qual
low_VariantReads
read_end_ratio;low_qual
low_VariantReads;read_end_ratio;low_qual
low_VariantReads;low_VariantRatio;low_qual
low_VariantRatio;low_qual
low_coverage
low_VariantReads;low_VariantRatio
low_coverage;read_end_ratio
low_VariantReads;low_qual
sum
3000
2500
samples
2000
1500
1000
Counts
22
1128
4653
1
85
3929
1
33
367
36
1
1
4
1
1020
2
1
62
11347
500
0
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61
Mbp