In [4]:
#import pandas as pd
In [1]:
### parameters
import pandas as pd
import textwrap

import numpy as np
from collections import defaultdict
import matplotlib.pyplot as plt

mySpecie='Homo_sapiens'
#change base dir to your data location
baseDir='/cellar/users/btsui/Data/SRA/snp/'
skymap_snp_dir=baseDir+'{specie}_snp_pos/'.format(specie=mySpecie)

#7:140753336

read dbSNP annotation

VCF bitfield (VP) is detailed in :
https://ftp.ncbi.nlm.nih.gov/snp/specs/dbSNP_BitField_latest.pdf

In [2]:
inVcfDir='/data/cellardata/users/btsui/dbsnp/Homo_sapiens/All_20170710.f1_byte2_not_00.vcf.gz' 
vcfDf=pd.read_csv(inVcfDir,sep='\t',header=None)
vcfDf.columns=['Chr','Pos','RsId','RefBase','AltBase','','','Annot']
vcfDf['Chr']=vcfDf['Chr'].astype(np.str)
/cellar/users/btsui/anaconda3/lib/python3.6/site-packages/IPython/core/interactiveshell.py:2785: DtypeWarning: Columns (0) have mixed types. Specify dtype option on import or set low_memory=False.
  interactivity=interactivity, compiler=compiler, result=result)
In [3]:
vcfDf['VP']=vcfDf['Annot'].str.extract('VP=0x(\w+);')
In [34]:
vcfDf.head()
Out[34]:
Chr Pos RsId RefBase AltBase Annot VP GENEINFO VP_binary
0 1 14727 rs1045587 G A . . RS=1045587;RSPOS=14727;RV;dbSNPBuildID=117;SSR... 050028040005000002000100 DDX11L1 0000010100000000001010000000010000000000000001...
1 1 630825 rs9783068 T C . . RS=9783068;RSPOS=630825;dbSNPBuildID=119;SSR=1... 050028020005000002000140 LOC101928626 0000010100000000001010000000001000000000000001...
2 1 630833 rs9701099 C T . . RS=9701099;RSPOS=630833;dbSNPBuildID=119;SSR=1... 050028020005000002000140 LOC101928626 0000010100000000001010000000001000000000000001...
3 1 817186 rs3094315 G A . . RS=3094315;RSPOS=817186;RV;dbSNPBuildID=103;SS... 05012802000515053f000101 FAM87B 0000010100000001001010000000001000000000000001...
4 1 833068 rs12562034 G A . . RS=12562034;RSPOS=833068;dbSNPBuildID=120;SSR=... 050128080005170537000100 LINC01128 0000010100000001001010000000100000000000000001...
In [4]:
vcfDf['Annot'].values
Out[4]:
array(['RS=1045587;RSPOS=14727;RV;dbSNPBuildID=117;SSR=0;SAO=0;VP=0x050028040005000002000100;GENEINFO=DDX11L1:100287102|WASH7P:653635;WGT=1;VC=SNV;PM;PMC;R3;ASP',
       'RS=9783068;RSPOS=630825;dbSNPBuildID=119;SSR=1;SAO=0;VP=0x050028020005000002000140;GENEINFO=LOC101928626:101928626;WGT=1;VC=SNV;PM;PMC;R5;ASP',
       'RS=9701099;RSPOS=630833;dbSNPBuildID=119;SSR=1;SAO=0;VP=0x050028020005000002000140;GENEINFO=LOC101928626:101928626;WGT=1;VC=SNV;PM;PMC;R5;ASP',
       ...,
       'RS=41458645;RSPOS=16278;dbSNPBuildID=127;SSR=0;SAO=0;VP=0x050028000005000402000100;WGT=1;VC=SNV;PM;PMC;ASP;HD',
       'RS=41378955;RSPOS=16390;dbSNPBuildID=127;SSR=0;SAO=0;VP=0x050028000005000402000100;WGT=1;VC=SNV;PM;PMC;ASP;HD',
       'RS=3937033;RSPOS=16519;dbSNPBuildID=108;SSR=0;SAO=0;VP=0x050128020005000502000100;GENEINFO=ND6:4541;WGT=1;VC=SNV;PM;PMC;SLO;R5;ASP;HD;GNO'],
      dtype=object)
In [5]:
vcfDf['GENEINFO']=vcfDf['Annot'].str.extract('GENEINFO=(\w+)',expand=False).values
In [6]:
#vcfDf.groupby(['GENEINFO']).size().median()
#somatic mutations vs germlime
In [7]:
num_of_byte=12
num_of_bits=num_of_byte*(8)
def toBin(my_hexdata):
    Hex=int(my_hexdata,base=16)
    return bin( Hex )[2:].zfill(num_of_bits)
In [8]:
dbsnpFlagDf=pd.read_csv('Data/dbsnpFlag.tsv',sep='\t')

#dbsnpFlagDf['Flag']=dbsnpFlagDf['Flag'].str.replace('[A-Z]','')

#dbsnpFlagDf['Flag']=dbsnpFlagDf['Flag'].astype(int)
In [9]:
dbsnpFlagDf_MultI=dbsnpFlagDf.set_index(['byte_left_to_right','bit'])['Link'].sort_index()
In [10]:
vcfDf['VP_binary']=vcfDf['VP'].apply(toBin).values
In [11]:
vcfDf.shape, 18846
Out[11]:
((393242, 11), 18846)
In [12]:
vcfDf=vcfDf#[(vcfDf['Chr']=='7')&(vcfDf['Pos']==140753336)]
In [13]:
#12 byte, 24 hex digits
VP_binary_l=vcfDf.VP_binary.apply(lambda S:pd.Series(textwrap.wrap(S,8)))
In [14]:
byteFieldDf=VP_binary_l#.T.unstack().unstack()#.apply(len)
In [15]:
#VP_binary_l

extract distribution of data

In [16]:
#byte=11
myL=[]
myByteToNameS=pd.Series({1:'resource link properties',
              2:'resource link properties',
              3:'gene function properties',
              4:'gene function properties',
              5:'mapping properties',
              6:'allele frequency properties',
              7:'genotype properties',
              8:'Validation by HapMap/TGP properties',
              9:'phenotype properties',
              10:'variation class',
              11:'quality check',
              12:'Version encoding',
             })


for byte in np.arange(1,12):
    tmpVC=byteFieldDf[byte].value_counts()#.head(n=10)
    bitVectors=tmpVC.index.values

    #dbsnpFlagDf_MultI.loc[byte]

    myDict=defaultdict(str)
    dbsnpFlagDf_MultI_sub=dbsnpFlagDf_MultI.loc[byte]
    for bitVector in bitVectors:
        #right to left, the bit vector from NCBI count from right to left, revert the order first 
        endianCorrectedVect=bitVector[::-1]
        for i in range(len(endianCorrectedVect)):
            if endianCorrectedVect[i]=='1':
                dbSNP_field=dbsnpFlagDf_MultI_sub.loc[i+1]
                myDict[bitVector]+=(dbSNP_field+'\n')

    #dbsnpFlagDf_MultI.loc[byte].values

    bitVectorToFnameS=pd.Series(myDict)

    tmpVC2=tmpVC.head(n=10)
    tmpS=pd.Series(index=bitVectorToFnameS.loc[tmpVC2.index].values, data=tmpVC2.values)
    bitVectorS=pd.Series(index=bitVectorToFnameS.loc[bitVectors],data=bitVectors)
    tmpDf=tmpS.to_frame('count')
    tmpDf['bitVector']=bitVectorS[:]
    myL.append(tmpDf)
/cellar/users/btsui/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:39: FutureWarning: 
Passing list-likes to .loc or [] with any missing label will raise
KeyError in the future, you can use .reindex() as an alternative.

See the documentation here:
https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike
/cellar/users/btsui/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:40: FutureWarning: 
Passing list-likes to .loc or [] with any missing label will raise
KeyError in the future, you can use .reindex() as an alternative.

See the documentation here:
https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike
In [17]:
#tmpDf.shape
In [18]:
#tmpDf
In [19]:
#byteFieldDf[byte]
In [20]:
keys=np.arange(1,12)#myByteToNameS.loc[np.arange(1,12)].values.tolist()
In [21]:
#len(myL),len(keys)
In [22]:
#keys
In [23]:
mergedCountDf=pd.concat(myL,keys=keys,axis=0)#.dropna()
In [24]:
mergedStatDf=mergedCountDf.reset_index()
In [25]:
#mergedStatDf
In [26]:
mergedStatDf.columns=['Byte_left_to_right','Varation properties','Count','bitVector']
In [27]:
mergedStatDf['Variation_area']=myByteToNameS[mergedStatDf['Byte_left_to_right']].values
In [28]:
mergedStatDf['Varation properties']=mergedStatDf['Varation properties'].fillna('N/A')
In [29]:
#mergedStatDf
In [30]:
countDf=mergedStatDf.set_index(['Variation_area','bitVector','Byte_left_to_right','Varation properties'])[['Count']]
In [31]:
excel=pd.ExcelWriter('./Data/snp.count.xlsx')
countDf.to_excel(excel)
excel.close()
In [36]:
#6, 3
#'100100'
In [33]:
!echo $PWD/./Data/snp.count.xlsx
/cellar/users/btsui/Project/METAMAP/notebook/RapMapTest/XGS_WGS/./Data/snp.count.xlsx

extract from byte

input: bitVectors ouutoutput:

In [532]:
byte=5
In [533]:
tmpVC=byteFieldDf[byte].value_counts()#.head(n=10)
bitVectors=tmpVC.index.values

#dbsnpFlagDf_MultI.loc[byte]

myDict=defaultdict(str)
dbsnpFlagDf_MultI_sub=dbsnpFlagDf_MultI.loc[byte]
for bitVector in bitVectors:
    #right to left, the bit vector from NCBI count from right to left, revert the order first 
    endianCorrectedVect=bitVector[::-1]
    for i in range(len(endianCorrectedVect)):
        if endianCorrectedVect[i]=='1':
            ###bit need to have a plus one
            dbSNP_field=dbsnpFlagDf_MultI_sub.loc[i+1]
            myDict[bitVector]+=(dbSNP_field+'\n')

#dbsnpFlagDf_MultI.loc[byte].values

bitVectorToFnameS=pd.Series(myDict)



#pd.Series(index=bitVectorToFnameS.loc[tmpVC2.index].values, data=tmpVC2.values)
bitVectorToFnameS
Out[533]:
00000101    Weight (2 bits). Weight on NCBI reference asse...
00010101    Weight (2 bits). Weight on NCBI reference asse...
00001101    Weight (2 bits). Weight on NCBI reference asse...
dtype: object
In [534]:
dbsnpFlagDf_MultI_sub
Out[534]:
bit
1    Weight (2 bits). Weight on NCBI reference asse...
2    Weight (2 bits). Weight on NCBI reference asse...
3    Is Assembly specific. This bit is 1 if the snp...
4    Has Assembly conflict. This is for weight 1 an...
5    Has other snp. with exatly the same set of map...
Name: Link, dtype: object
In [535]:
fig,ax=plt.subplots(figsize=(10,4))

tmpVC2=tmpVC.head(n=10)
ax=pd.Series(index=bitVectorToFnameS.loc[tmpVC2.index].values,data=tmpVC2.values).plot.bar()
/cellar/users/btsui/anaconda3/lib/python3.6/site-packages/ipykernel_launcher.py:4: FutureWarning: 
Passing list-likes to .loc or [] with any missing label will raise
KeyError in the future, you can use .reindex() as an alternative.

See the documentation here:
https://pandas.pydata.org/pandas-docs/stable/indexing.html#deprecate-loc-reindex-listlike
  after removing the cwd from sys.path.
In [536]:
#100100
#why is this both missense and STOP-GAIN?

tmpVC2
Out[536]:
00000101    376159
00000000     16748
00010101       170
00001101       165
Name: 5, dtype: int64

#

In [520]:
#00000101
#allele frequency properties
In [550]:
vcfDf['GENEINFO'].nunique()
Out[550]:
0
In [551]:
vcfDf['GENEINFO']
Out[551]:
0         NaN
1         NaN
2         NaN
3         NaN
4         NaN
5         NaN
6         NaN
7         NaN
8         NaN
9         NaN
10        NaN
11        NaN
12        NaN
13        NaN
14        NaN
15        NaN
16        NaN
17        NaN
18        NaN
19        NaN
20        NaN
21        NaN
22        NaN
23        NaN
24        NaN
25        NaN
26        NaN
27        NaN
28        NaN
29        NaN
         ... 
393212    NaN
393213    NaN
393214    NaN
393215    NaN
393216    NaN
393217    NaN
393218    NaN
393219    NaN
393220    NaN
393221    NaN
393222    NaN
393223    NaN
393224    NaN
393225    NaN
393226    NaN
393227    NaN
393228    NaN
393229    NaN
393230    NaN
393231    NaN
393232    NaN
393233    NaN
393234    NaN
393235    NaN
393236    NaN
393237    NaN
393238    NaN
393239    NaN
393240    NaN
393241    NaN
Name: GENEINFO, Length: 393242, dtype: object
In [521]:
bitVector='00001111'
endianCorrectedVect=bitVector[::-1]
In [522]:
m_binary=(byteFieldDf[byte]==bitVector).values
In [548]:
#vcfDf['GENEINFO'].value_counts()
In [524]:
#bitVectorToFnameS.values
In [525]:
#bitVectorToFnameS.loc[bitVector]
In [526]:
#m=vcfDf['VP_binary'].str.contains('\w+{}00001010'.format(8*3))
In [527]:
#missense,nc transcript variant for the first couple, missense,nc transcript variant
"""
00001010, seem to be all: missense,nc transcript variant
00000011: rs267598747:synonymous codon, synon codon

r vcfDf and 

Hypothesis on bug: the mapping is mostlikely off 
"""
#
Out[527]:
'\n00001010, seem to be all: missense,nc transcript variant\n00000011: rs267598747:synonymous codon, synon codon\n\nr vcfDf and \n\nHypothesis on bug: the mapping is mostlikely off \n'
In [528]:
bitVectorToFnameS.index[0]
Out[528]:
'00001010'
In [529]:
bitVectorToFnameS.iloc[0]
Out[529]:
'Has reference. A coding region variation where one allele in the set is identical to the reference sequence. FxnCode = 8\nHas non-synonymous missense. A coding region variation where one allele in the set changes protein peptide. FxnClass = 42\n'
In [530]:
"""
byte 4: 00001010
2,4

has one allele: 

"""
Out[530]:
'\nbyte 4: 00001010\n2,4\n\nhas one allele: \n\n'
In [ ]:
 
In [531]:
vcfDf[m_binary]
Out[531]:
Chr Pos RsId RefBase AltBase Annot VP VP_binary
28183 1 235766122 rs80338660 G A,C,T . . RS=80338660;RSPOS=235766122;RV;dbSNPBuildID=13... 050168000f05040026110104 0000010100000001011010000000000000001111000001...
30958 2 1487841 rs121908082 C A,G,T . . RS=121908082;RSPOS=1487841;dbSNPBuildID=132;SS... 050268080f05040002110100 0000010100000010011010000000100000001111000001...
34025 2 31386525 rs119460972 G A,C,T . . RS=119460972;RSPOS=31386525;RV;dbSNPBuildID=13... 050268000f05040002110104 0000010100000010011010000000000000001111000001...
37812 2 47798725 rs63749980 C A,G,T . . RS=63749980;RSPOS=47798725;dbSNPBuildID=137;SS... 050060400f05040002100104 0000010100000000011000000100000000001111000001...
38040 2 47799427 rs63750909 C A,G,T . . RS=63750909;RSPOS=47799427;dbSNPBuildID=137;SS... 050268000f05000002100104 0000010100000010011010000000000000001111000001...
40404 2 61839437 rs202193201 G A,C,T . . RS=202193201;RSPOS=61839437;dbSNPBuildID=137;S... 050068000f05040036110100 0000010100000000011010000000000000001111000001...
64305 2 233682328 rs17863778 C A,G,T . . RS=17863778;RSPOS=233682328;dbSNPBuildID=126;S... 050138080f05150036000104 0000010100000001001110000000100000001111000001...
76916 3 70976982 rs775136381 G A,C,T . . RS=775136381;RSPOS=70976982;dbSNPBuildID=144;S... 050060000f05040002100104 0000010100000000011000000000000000001111000001...
87284 4 1004286 rs121965031 C A,G,T . . RS=121965031;RSPOS=1004286;dbSNPBuildID=133;SS... 050068000f05040002110104 0000010100000000011010000000000000001111000001...
99485 4 154796798 rs144494582 C A,G,T . . RS=144494582;RSPOS=154796798;dbSNPBuildID=134;... 050060000f05040002100124 0000010100000000011000000000000000001111000001...
117339 5 140557175 rs250426 G A,T . . RS=250426;RSPOS=140557175;dbSNPBuildID=79;SSR=... 050128000f05150537000100 0000010100000001001010000000000000001111000001...
125994 6 25777954 rs2328894 C T . . RS=2328894;RSPOS=25777954;dbSNPBuildID=100;SSR... 050128080f05040537000101 0000010100000001001010000000100000001111000001...
127114 6 29942978 rs41542015 C A,G,T . . RS=41542015;RSPOS=29942978;dbSNPBuildID=137;SS... 050260000f05000002100104 0000010100000010011000000000000000001111000001...
127230 6 29943317 rs41561714 G A,C,T . . RS=41561714;RSPOS=29943317;dbSNPBuildID=137;SS... 050260000f05000002100104 0000010100000010011000000000000000001111000001...
127256 6 29943344 rs41556016 C A,G,T . . RS=41556016;RSPOS=29943344;dbSNPBuildID=137;SS... 050260000f05040002100104 0000010100000010011000000000000000001111000001...
127379 6 29943488 rs41558913 C A,G,T . . RS=41558913;RSPOS=29943488;dbSNPBuildID=137;SS... 050260000f05000002100104 0000010100000010011000000000000000001111000001...
128772 6 31271128 rs281860527 G A,C,T . . RS=281860527;RSPOS=31271128;RV;dbSNPBuildID=13... 050260000f05000002100104 0000010100000010011000000000000000001111000001...
129009 6 31271647 rs41549514 G A,C,T . . RS=41549514;RSPOS=31271647;RV;dbSNPBuildID=137... 050260000f05000002100104 0000010100000010011000000000000000001111000001...
129627 6 31356222 rs41557820 G A,C,T . . RS=41557820;RSPOS=31356222;RV;dbSNPBuildID=137... 050260020f05040002100104 0000010100000010011000000000001000001111000001...
129891 6 31356736 rs41541213 G A,C,T . . RS=41541213;RSPOS=31356736;RV;dbSNPBuildID=137... 050260020f05040002100104 0000010100000010011000000000001000001111000001...
153965 7 21748602 rs121908854 C A,G,T . . RS=121908854;RSPOS=21748602;dbSNPBuildID=133;S... 050368000f05040436110104 0000010100000011011010000000000000001111000001...
158813 7 76515138 rs1799125 A C,T . . RS=1799125;RSPOS=76515138;dbSNPBuildID=89;SSR=... 050128080f0515053f000140 0000010100000001001010000000100000001111000001...
169544 7 150950336 rs189014161 G A,C,T . . RS=189014161;RSPOS=150950336;dbSNPBuildID=135;... 050268000f05040036110104 0000010100000010011010000000000000001111000001...
179309 8 86668055 rs267606739 G A,C,T . . RS=267606739;RSPOS=86668055;RV;dbSNPBuildID=13... 050068000f05040026110104 0000010100000000011010000000000000001111000001...
193313 9 100292976 rs267607185 C A,G,T . . RS=267607185;RSPOS=100292976;dbSNPBuildID=137;... 050068000f05040026110104 0000010100000000011010000000000000001111000001...
204773 10 49156232 rs267602505 G A . . RS=267602505;RSPOS=49156232;dbSNPBuildID=137;S... 0500600c0f05000002100120 0000010100000000011000000000110000001111000001...
207374 10 70771398 rs149097055 G A,T . . RS=149097055;RSPOS=70771398;dbSNPBuildID=134;S... 050060840f05040426100120 0000010100000000011000001000010000001111000001...
221031 11 6394209 rs771336819 T A,C . . RS=771336819;RSPOS=6394209;dbSNPBuildID=144;SS... 050068000f05000002100100 0000010100000000011010000000000000001111000001...
227459 11 61397797 rs11230683 C A,G,T . . RS=11230683;RSPOS=61397797;dbSNPBuildID=120;SS... 050068000f05040436110100 0000010100000000011010000000000000001111000001...
232976 11 94447276 rs774277300 G A,C,T . . RS=774277300;RSPOS=94447276;dbSNPBuildID=136;S... 050060000f05040002100100 0000010100000000011000000000000000001111000001...
233099 11 94467821 rs371077728 G A,C,T . . RS=371077728;RSPOS=94467821;dbSNPBuildID=138;S... 050260020f05040002100104 0000010100000010011000000000001000001111000001...
254033 12 100532538 rs113090017 C A,G,T . . RS=113090017;RSPOS=100532538;dbSNPBuildID=132;... 050128080f05040102000104 0000010100000001001010000000100000001111000001...
259803 13 23331644 rs141315518 G A,C,T . . RS=141315518;RSPOS=23331644;dbSNPBuildID=134;S... 050068000f05040036110100 0000010100000000011010000000000000001111000001...
264058 13 32340280 rs80358825 T A,C,G . . RS=80358825;RSPOS=32340280;dbSNPBuildID=132;SS... 050168000f05000002100104 0000010100000001011010000000000000001111000001...
285732 15 40625535 rs191249840 C A,G,T . . RS=191249840;RSPOS=40625535;dbSNPBuildID=135;S... 050128000f05040036000100 0000010100000001001010000000000000001111000001...
286483 15 44573661 rs147713329 G A,C,T . . RS=147713329;RSPOS=44573661;dbSNPBuildID=134;S... 050168080f05000002110104 0000010100000001011010000000100000001111000001...
289049 15 51404533 rs368085516 C A,G,T . . RS=368085516;RSPOS=51404533;dbSNPBuildID=138;S... 050028080f05040002000104 0000010100000000001010000000100000001111000001...
293624 15 89316771 rs144346886 G A,C,T . . RS=144346886;RSPOS=89316771;dbSNPBuildID=134;S... 050268800f05040026100100 0000010100000010011010001000000000001111000001...
310193 16 75556198 rs397514609 A G,T . . RS=397514609;RSPOS=75556198;RV;dbSNPBuildID=13... 050068000f05000002110100 0000010100000000011010000000000000001111000001...
310646 16 79211721 rs372635911 C A,G,T . . RS=372635911;RSPOS=79211721;dbSNPBuildID=138;S... 050260800f05040002100100 0000010100000010011000001000000000001111000001...
316473 17 16940378 rs72553885 G A,C,T . . RS=72553885;RSPOS=16940378;RV;dbSNPBuildID=130... 050028000f05040402000104 0000010100000000001010000000000000001111000001...
317239 17 19347840 rs373478202 G A,C,T . . RS=373478202;RSPOS=19347840;dbSNPBuildID=138;S... 050028000f05040026000100 0000010100000000001010000000000000001111000001...
321820 17 43045729 rs397509295 G A,C,T . . RS=397509295;RSPOS=43045729;RV;dbSNPBuildID=13... 050068800f05000002110104 0000010100000000011010001000000000001111000001...
321925 17 43047687 rs80357358 A G,T . . RS=80357358;RSPOS=43047687;RV;dbSNPBuildID=132... 050368000f05000002100100 0000010100000011011010000000000000001111000001...
326230 17 44352087 rs63751180 C A,G,T . . RS=63751180;RSPOS=44352087;dbSNPBuildID=137;SS... 050160000f05040002100104 0000010100000001011000000000000000001111000001...
328849 17 58206159 rs772719574 G A,T . . RS=772719574;RSPOS=58206159;dbSNPBuildID=144;S... 050028800f05040002000100 0000010100000000001010001000000000001111000001...
341491 19 2853131 rs267605399 C A,G,T . . RS=267605399;RSPOS=2853131;dbSNPBuildID=137;SS... 050260000f05040002100124 0000010100000010011000000000000000001111000001...
344267 19 11105425 rs769318035 C A,G,T . . RS=769318035;RSPOS=11105425;dbSNPBuildID=144;S... 050068080f05000002100104 0000010100000000011010000000100000001111000001...
344478 19 11107402 rs146651743 C A,G,T . . RS=146651743;RSPOS=11107402;dbSNPBuildID=134;S... 050268000f05040436100104 0000010100000010011010000000000000001111000001...
344537 19 11107513 rs13306512 C A,G,T . . RS=13306512;RSPOS=11107513;dbSNPBuildID=121;SS... 050268000f05040137100104 0000010100000010011010000000000000001111000001...
344614 19 11110767 rs13306515 C A,G,T . . RS=13306515;RSPOS=11110767;dbSNPBuildID=121;SS... 050368000f05040536100104 0000010100000011011010000000000000001111000001...
345260 19 11120470 rs112954220 C A,G,T . . RS=112954220;RSPOS=11120470;dbSNPBuildID=132;S... 050268080f05040002100104 0000010100000010011010000000100000001111000001...
367901 22 16807899 rs142425083 G A,C,T . . RS=142425083;RSPOS=16807899;dbSNPBuildID=137;S... 050060000f05040002100124 0000010100000000011000000000000000001111000001...
373131 22 42128212 rs367543000 G A,C,T . . RS=367543000;RSPOS=42128212;RV;dbSNPBuildID=13... 050060020f05040002110104 0000010100000000011000000000001000001111000001...
373880 22 46356865 rs779022860 C A,T . . RS=779022860;RSPOS=46356865;dbSNPBuildID=144;S... 050060000f05040002100100 0000010100000000011000000000000000001111000001...
388490 X 154350109 rs782308324 G A,C,T . . RS=782308324;RSPOS=154350109;dbSNPBuildID=144;... 050060000f05040002100104 0000010100000000011000000000000000001111000001...
389190 X 154928647 rs137852439 G A,C,T . . RS=137852439;RSPOS=154928647;RV;dbSNPBuildID=1... 050268000f05000002110104 0000010100000010011010000000000000001111000001...
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