ANNOVAR的使用

ANNOVAR的安装

ANNOVAR网址

log in之后才能download，使用教育机构后缀的邮箱即可注册。

该测序是用perl语言写的，所以可以作为独立程序运行于各个已经安装Perl的系统。解压直接用即可。
以下示例皆在linux系统中完成

ANNOVAR的安装包里自带了一些常用的数据库，在humandb/目录下

安装包内容
如果要进行其他注释，需要使用 -downdb 命令下载数据库到 ‘humandb/’ 目录里：

#下载1000g2015Aug数据库
$perl annotate_variation.pl -buildver hg19 -downdb -webfrom annovar 1000g2015aug humandb/

在ANNOVAR的主页面有用于注释的各种数据库的描述，使用者可以根据自行去下载：

annotation database

ANNOVAR的程序模块

ANNOVAR程序有以下几个模块：

(ANNOVAR程序结构
│ annotate_variation.pl #主程序，功能包括下载数据库，三种不同的注释
│ coding_change.pl #可用来推断蛋白质序列
│ convert2annovar.pl #将多种格式转为.avinput的程序
│ retrieve_seq_from_fasta.pl #用于自行建立其他物种的转录本
│ table_annovar.pl #注释程序，可一次性完成三种类型的注释
│ variants_reduction.pl #可用来更灵活地定制过滤注释流程
│
├─example #存放示例文件
│
└─humandb #人类注释数据库)

ANNOVAR的输入文件

ANNOVAR使用.avinput格式，如以上代码所示，该格式每列以tab分割，需要有以下几个信息：

染色体位置

起始位点
终止位点
参考基因组碱基
突变碱基
......

文件示例:

chrM    302     302     -       C       chrM    302     .       A       AC      93.73   PASS    AC=4;AF=0.500;AN=8;ClippingRankSum=0.000;DP=121;ExcessHet=3.0103;MLEAC=1;MLEAF=0.500;set=Intersection   GT:AD:DP:GQ:PL  0/1:16,9:25:99:183,0,384
chrM    963     963     T       -       chrM    962     .       CT      C       258.73  PASS    AC=3;AF=0.500;AN=6;ClippingRankSum=0.000;DP=75;ExcessHet=3.0103;MLEAC=1;MLEAF=0.500;set=variant2-variant3-variant4      GT:AD:DP:GQ:PL  0/1:11,11:22:99:296,0,247
chr1    2178293 2178294 GG      -       chr1    2178292 .       TGG     T       128     PASS    AC=6;AF=1.00;AN=6;DP=31;ExcessHet=3.0103;FS=0.000;MLEAC=2;MLEAF=1.00;set=variant-variant2-variant3      GT:AD:DP:GQ:PL  1/1:0,4:4:12:165,12,0
chr1    2248382 2248382 -       C       chr1    2248382 .       G       GC      98.25   PASS    AC=4;AF=1.00;AN=4;DP=5;ExcessHet=3.0103;FS=0.000;MLEAC=2;MLEAF=1.00;set=variant2-variant3       GT:AD:DP:GQ:PL  1/1:0,3:3:9:135,9,0
chr1    3278899 3278899 -       C       chr1    3278899 .       A       AC      30.71   PASS    AC=2;AF=1.00;AN=2;DP=2;ExcessHet=3.0103;FS=0.000;MLEAC=2;MLEAF=1.00;MQ=37.00;QD=15.35;SOR=0.693;set=variant2    GT:AD:DP:GQ:PL  1/1:0,2:2:6:67,6,0
chr1    3817092 3817092 -       T       chr1    3817092 .       C       CT      22.73   PASS    AC=2;AF=1.00;AN=2;DP=2;ExcessHet=3.0103;FS=0.000;MLEAC=2;MLEAF=1.00;MQ=37.00;QD=11.36;SOR=0.693;set=variant2    GT:AD:DP:GQ:PL  1/1:0,2:2:6:59,6,0
chr1    6067261 6067261 -       G       chr1    6067261 .       T       TG      21.73   PASS    AC=2;AF=1.00;AN=2;DP=2;ExcessHet=3.0103;FS=0.000;MLEAC=2;MLEAF=1.00;MQ=37.00;QD=10.87;SOR=0.693;set=variant2    GT:AD:DP:GQ:PL  1/1:0,2:2:6:58,6,0
chr1    6211850 6211850 -       C       chr1    6211850 .       A       AC      30.71   PASS    AC=2;AF=1.00;AN=2;DP=2;ExcessHet=3.0103;FS=0.000;MLEAC=2;MLEAF=1.00;MQ=37.00;QD=15.35;SOR=0.693;set=variant2    GT:AD:DP:GQ:PL  1/1:0,2:2:6:67,6,0
chr1    7538772 7538772 -       TTTA    chr1    7538772 .       C       CTTTA   53.70   PASS    AC=2;AF=1.00;AN=2;DP=2;ExcessHet=3.0103;FS=0.000;MLEAC=2;MLEAF=1.00;MQ=37.00;QD=26.85;SOR=2.303;set=variant2    GT:AD:DP:GQ:PL  1/1:0,2:2:6:90,6,0
chr1    7709649 7709649 -       T       chr1    7709649 .       C       CT      62.74   PASS    AC=2;AF=0.500;AN=4;ClippingRankSum=0.000;DP=15;ExcessHet=3.0103;MLEAC=1;MLEAF=0.500;MQ=37.00;MQRankSum=0.000;set=variant2-variant3      GT:AD:DP:GQ:PL       0/1:1,3:4:25:100,0,25

ANNOVAR输入文件的格式转换

ANNOVAR主要使用convert2annovar.pl程序进行转换，转换后文件是精简过的，主要包含前面提到的5列内容，如果要将原格式的文件的所有内容都包含在转换后的.avinput文件中，可以使用-includeinfo参数；如果需要分开每个sample输出单一的.avinput文件，可以使用-allsample参数，等等。
代码示例：

$ convert2annovar.pl -format vcf4 example/ex2.vcf > ex2.avinput
# -format vcf4 指定格式为vcf

ANNOVAR还主要支持以下格式转换：

SAMtools pileup format

Complete Genomics format

GFF3-SOLiD calling format

SOAPsnp calling format

MAQ calling format

CASAVA calling format

ANNOVAR注释功能

Table_annovar.pl（可一次完成三种类型的注释）

使用ANNOVAR最简单的方法就是使用table_annovar.pl进行注释，它的输入文件可以是多种格式包括VCF，输出文件已Tab分隔，每一列代表着一种注释。
注释命令示例：

$~/biosoft/ANNOVAR/annovar/table_annovar.pl 15_indel_pre.avinput.hg19.variant2.avinput ~/biosoft/ANNOVAR/annovar/humandb/ -buildver hg19 -out myanno -remove -protocol refGene,cytoBand,genomicSuperDups,esp6500siv2_all,1000g2015aug_all,1000g2015aug_eur,exac03,avsnp147,dbnsfp30a -operation g,r,r,f,f,f,f,f,f -nastring . -csvout
# -buildver hg19 表示使用hg19版本
# -out myanno 表示输出文件的前缀为myanno
# -remove 表示删除注释过程中的临时文件
# -protocol 表示注释使用的数据库，用逗号隔开，且要注意顺序
# -operation 表示对应顺序的数据库的类型（g代表gene-based、r代表region-based、f代表filter-based），用逗号隔开，注意顺序
# -nastring . 表示用点号替代缺省的值
# -csvout 表示最后输出.csv文件

输出的csv文件将包含输入的5列主要信息以及各个数据库里的注释，此外，table_annoval.pl可以直接对vcf文件进行注释（不需要转换格式），注释的内容将会放在vcf文件的“INFO”那一栏。
注释结果示例：

注释结果

Annotate_variation.pl

Annotate_variation.pl的注释方式分为三种：

Gene-based annotation
Region-based annotation
Filter-based annotation

annotate_variation.pl -geneanno -buildver hg19 example/ex1.avinput humandb/
annotate_variation.pl -regionanno -dbtype cytoBand -buildver hg19 example/ex1.avinput humandb/
annotate_variation.pl -filter -dbtype 1000g2014oct_all -buildver hg19 example/ex1.avinput humandb/
#三种命令示例，使用package自带数据进行注释，分别对应三种注释方式

Annotate_variation.pl 实例

Gene-based annotation

顾名思义，Gene-based annotation是根据SNPs以及CNVs的位置信息来确定是否会造成编码序列以及开放阅读框的改变从而影响氨基酸的改变，使用者可以自主选择RefSeq genes, 包括UCSC genes, ENSEMBL genes, GENCODE genes, AceView genes等来进行注释。
命令示例：

$ annotate_variation.pl -geneanno -dbtype refGene -out ex1 -build hg19 example/ex1.avinput humandb/
# -geneanno 表示使用基于基因的注释
# -dbtype refGene 表示使用"refGene"数据库
# -out ex1 表示输出文件以ex1为前缀

因为annotate_variation.pl默认使用gene-based注释类型以及refGene数据库，所以上面的命令可以缺省-geneanno -dbtype refGene
运行结果会产生两个文件：

#ex1.variant_function
[kaiwang@biocluster ~/]$ cat ex1.variant_function
UTR5 ISG15(NM_005101:c.-33T>C) 1 948921 948921 T C comments: rs15842, a SNP in 5' UTR of ISG15
UTR3 ATAD3C(NM_001039211:c.*91G>T) 1 1404001 1404001 G T comments: rs149123833, a SNP in 3' UTR of ATAD3C
splicing NPHP4(NM_001291593:exon19:c.1279-2T>A,NM_001291594:exon18:c.1282-2T>A,NM_015102:exon22:c.2818-2T>A) 1 5935162 5935162 A T comments: rs1287637, a splice site variant in NPHP4
intronic DDR2 1 162736463 162736463 C T comments: rs1000050, a SNP in Illumina SNP arrays
intronic DNASE2B 1 84875173 84875173 C T comments: rs6576700 or SNP_A-1780419, a SNP in Affymetrix SNP arrays
intergenic LOC645354(dist=11566),LOC391003(dist=116902) 1 13211293 13211294 TC - comments: rs59770105, a 2-bp deletion
intergenic UBIAD1(dist=55105),PTCHD2(dist=135699) 1 11403596 11403596 - AT comments: rs35561142, a 2-bp insertion
intergenic LOC100129138(dist=872538),NONE(dist=NONE) 1 105492231 105492231 A ATAAA comments: rs10552169, a block substitution
exonic IL23R 1 67705958 67705958 G A comments: rs11209026 (R381Q), a SNP in IL23R associated with Crohn's disease
exonic ATG16L1 2 234183368 234183368 A G comments: rs2241880 (T300A), a SNP in the ATG16L1 associated with Crohn's disease
exonic NOD2 16 50745926 50745926 C T comments: rs2066844 (R702W), a non-synonymous SNP in NOD2
exonic NOD2 16 50756540 50756540 G C comments: rs2066845 (G908R), a non-synonymous SNP in NOD2
exonic NOD2 16 50763778 50763778 - C comments: rs2066847 (c.3016_3017insC), a frameshift SNP in NOD2
exonic GJB2 13 20763686 20763686 G - comments: rs1801002 (del35G), a frameshift mutation in GJB2, associated with hearing loss
exonic CRYL1,GJB6 13 20797176 21105944 0 - comments: a 342kb deletion encompassing GJB6, associated with hearing loss 
第一个文件包括对于所有突变的注释，通过在文件最前面加入两列，以tab分割
第一列为变异所在基因位置的类型，如外显子，内含子，UTR5，UTR3，基因间等
第二列为对第一列的描述信息，详情见下

详细解释

#ex1.exonic_variant_function
[kaiwang@biocluster ~/]$ cat ex1.exonic_variant_function
line9 nonsynonymous SNV IL23R:NM_144701:exon9:c.G1142A:p.R381Q, 1 67705958 67705958 G A comments: rs11209026 (R381Q), a SNP in IL23R associated with Crohn's disease
line10 nonsynonymous SNV ATG16L1:NM_001190267:exon9:c.A550G:p.T184A,ATG16L1:NM_017974:exon8:c.A841G:p.T281A,ATG16L1:NM_001190266:exon9:c.A646G:p.T216A,ATG16L1:NM_030803:exon9:c.A898G:p.T300A,ATG16L1:NM_198890:exon5:c.A409G:p.T137A, 2 234183368 234183368 A G comments: rs2241880 (T300A), a SNP in the ATG16L1 associated with Crohn's disease
line11 nonsynonymous SNV NOD2:NM_022162:exon4:c.C2104T:p.R702W,NOD2:NM_001293557:exon3:c.C2023T:p.R675W, 16 50745926 50745926 C comments: rs2066844 (R702W), a non-synonymous SNP in NOD2
line12 nonsynonymous SNV NOD2:NM_022162:exon8:c.G2722C:p.G908R,NOD2:NM_001293557:exon7:c.G2641C:p.G881R, 16 50756540 50756540 G comments: rs2066845 (G908R), a non-synonymous SNP in NOD2
line13 frameshift insertion NOD2:NM_022162:exon11:c.3017dupC:p.A1006fs,NOD2:NM_001293557:exon10:c.2936dupC:p.A979fs, 16 50763778 5076377comments: rs2066847 (c.3016_3017insC), a frameshift SNP in NOD2
line14 frameshift deletion GJB2:NM_004004:exon2:c.35delG:p.G12fs, 13 20763686 20763686 G - comments: rs1801002 (del35G), a frameshift mutation in GJB2, associated with hearing loss line15 frameshift deletion GJB6:NM_001110221:wholegene,GJB6:NM_001110220:wholegene,GJB6:NM_001110219:wholegene,CRYL1:NM_015974:wholegene,GJB6:NM_006783:wholegene, 13 20797176 21105944 0 - comments: a 342kb deletion encompassing GJB6, associated with hearing loss
第二个输出文件以.exonic_variant_function结尾，只列出外显子（氨基酸会改变）的变异
第一列为第一个文件中该变异所在的行号；
第二列为该变异的功能性后果，如外现在改变导致的氨基酸变化，阅读框移码等，详情见下
第三列为基因名称，转录识别标志和相应的转录本的序列变化
第四列为原输入文件内容

详细解释

Region-based annotation

其与Gene-based annotation作用相反，它是用来确认在特定区域的突变造成的影响。比如在44个物种的保守基因区域，预测的转录因子结合区域，基因重复区域，GWAS分析区域，基因突变数据库，表观组学位点等。此处以Conserved genomic elements annotation为例介绍region-based annotation的使用：
命令示例：

#数据库下载
[kaiwang@biocluster ~/]$ annotate_variation.pl -build hg19 -downdb phastConsElements46way humandb/
NOTICE: Web-based checking to see whether ANNOVAR new version is available ... Done
NOTICE: Downloading annotation database http://hgdownload.cse.ucsc.edu/goldenPath/hg19/database/phastConsElements46way.txt.gz ... OK
NOTICE: Uncompressing downloaded files
NOTICE: Finished downloading annotation files for hg19 build version, with files saved at the 'humandb' directory
#使用下载数据库进行注释
[kaiwang@biocluster ~/]$ annotate_variation.pl -regionanno -build hg19 -out ex1 -dbtype phastConsElements46way example/ex1.avinput humandb/
NOTICE: Reading annotation database humandb/hg19_phastConsElements46way.txt ... Done with 5163775 regions
NOTICE: Finished region-based annotation on 12 genetic variants in ex1.hg19.avinput
NOTICE: Output files were written to ex1.hg19_phastConsElements46way
# -regionanno 表示使用基于区域的注释
# -dbtype phastConsElements46way 表示使用"phastConsElements46way"数据库，注意需要使用Region-based的数据库

#输出文件
[kaiwang@biocluster ~/]$ cat ex1.hg19_phastConsElements46way
phastConsElements46way Score=387;Name=lod=50 1 67705958 67705958 G A comments: rs11209026 (R381Q), a SNP in IL23R associated with Crohn's disease
phastConsElements46way Score=420;Name=lod=68 16 50756540 50756540 G C comments: rs2066845 (G908R), a non-synonymous SNP in NOD2
phastConsElements46way Score=385;Name=lod=49 16 50763778 50763778 - C comments: rs2066847 (c.3016_3017insC), a frameshift SNP in NOD2
phastConsElements46way Score=395;Name=lod=54 13 20763686 20763686 G - comments: rs1801002 (del35G), a frameshift mutation in GJB2, associated with hearing loss
phastConsElements46way Score=545;Name=lod=218 13 20797176 21105944 0 - comments: a 342kb deletion encompassing GJB6, associated with hearing loss
输出文件:输出的注释文件第1列为“phastConsElements46way”，对应注释的类型，这里的phastCons 46-way alignments属于保守的基因组区域的注释；
第二列包含评分和名称，评分来自UCSC，可以使用--score_threshold和--normscore_threshold来过滤评分低的变异，“Name=lod=x”名称表示该区域的名称；
剩余的部分为输入文件的内容。

Filter-based annotation

Filter-based annotation是用以确认已记录在特定数据库里的突变。例如想要知道突变是否为novel variation就需要知道该突变是否存在于dbSNP库里，它在1000 genome project里面等位基因频率怎样，以及计算一系列突变项目得分并加以过滤。它区别于region-based annotation就在于它针对突变碱基进行工作，而region-based annotation 针对染色体位置。举例来说就是region-based比对chr1:1000-1000而filter-based比对chr1:1000-1000上的A->G。
它拥有多种数据库，包括针对全基因组测序的突变频率，针对全外显子数据测序的突变频率，在孤立或者小类群人群中的突变频率，全基因组数据突变的功能预测，全外显子组突变的功能预测，剪切变异体的功能预测，疾病相关突变，突变确认等，如下：

注释数据库

下面给大家介绍常用的两种过滤注释

1000 Genomes Project annotations

命令示例：

[kaiwang@biocluster ~/]$ annotate_variation.pl -filter -dbtype 1000g2012apr_eur -buildver hg19 -out ex1 example/ex1.avinput humandb/
NOTICE: Variants matching filtering criteria are written to ex1.hg19_EUR.sites.2012_04_dropped, other variants are written to ex1.hg19_EUR.sites.2012_04_filtered
NOTICE: Processing next batch with 15 unique variants in 15 input lines
NOTICE: Database index loaded. Total number of bins is 2766067 and the number of bins to be scanned is 12
NOTICE: Scanning filter database humandb/hg19_EUR.sites.2012_04.txt...Done
#查看数据格式
[kaiwang@biocluster ~/]$ cat ex1.hg19_EUR.sites.2012_04_dropped
1000g2012apr_eur 0.04 1 1404001 1404001 G T comments: rs149123833, a SNP in 3' UTR of ATAD3C
1000g2012apr_eur 0.87 1 162736463 162736463 C T comments: rs1000050, a SNP in Illumina SNP arrays
1000g2012apr_eur 0.81 1 5935162 5935162 A T comments: rs1287637, a splice site variant in NPHP4
1000g2012apr_eur 0.06 1 67705958 67705958 G A comments: rs11209026 (R381Q), a SNP in IL23R associated with Crohn's disease
1000g2012apr_eur 0.54 1 84875173 84875173 C T comments: rs6576700 or SNP_A-1780419, a SNP in Affymetrix SNP arrays
1000g2012apr_eur 0.96 1 948921 948921 T C comments: rs15842, a SNP in 5' UTR of ISG15
1000g2012apr_eur 0.05 16 50745926 50745926 C T comments: rs2066844 (R702W), a non-synonymous SNP in NOD2
1000g2012apr_eur 0.01 16 50756540 50756540 G C comments: rs2066845 (G908R), a non-synonymous SNP in NOD2
1000g2012apr_eur 0.01 16 50763778 50763778 - C comments: rs2066847 (c.3016_3017insC), a frameshift SNP in NOD2
1000g2012apr_eur 0.53 2 234183368 234183368 A G comments: rs2241880 (T300A), a SNP in the ATG16L1 associated with Crohn's disease
# -filter 使用基于过滤的注释
# -dbtype 1000g2012apr_eur 使用"1000g2012apr_eur"数据库

该注释使用2012年4月欧洲发布1000基因组计划数据库，输出文件会有两个，output_dropped file 和 output_filtered file

#dropped file
[kaiwang@biocluster ~/]$ cat ex1.hg19_EUR.sites.2012_04_dropped
1000g2012apr_eur 0.04 1 1404001 1404001 G T comments: rs149123833, a SNP in 3' UTR of ATAD3C
1000g2012apr_eur 0.87 1 162736463 162736463 C T comments: rs1000050, a SNP in Illumina SNP arrays
1000g2012apr_eur 0.81 1 5935162 5935162 A T comments: rs1287637, a splice site variant in NPHP4
1000g2012apr_eur 0.06 1 67705958 67705958 G A comments: rs11209026 (R381Q), a SNP in IL23R associated with Crohn's disease
1000g2012apr_eur 0.54 1 84875173 84875173 C T comments: rs6576700 or SNP_A-1780419, a SNP in Affymetrix SNP arrays
1000g2012apr_eur 0.96 1 948921 948921 T C comments: rs15842, a SNP in 5' UTR of ISG15
1000g2012apr_eur 0.05 16 50745926 50745926 C T comments: rs2066844 (R702W), a non-synonymous SNP in NOD2
1000g2012apr_eur 0.01 16 50756540 50756540 G C comments: rs2066845 (G908R), a non-synonymous SNP in NOD2
1000g2012apr_eur 0.01 16 50763778 50763778 - C comments: rs2066847 (c.3016_3017insC), a frameshift SNP in NOD2
1000g2012apr_eur 0.53 2 234183368 234183368 A G comments: rs2241880 (T300A), a SNP in the ATG16L1 associated with Crohn's disease
#*dropped文件
第一列如region-based注释的结果一样以数据库命名；
第二列为等位基因频率，我们可以用-maf 0.05参数来过滤掉低于0.05的变异；
第三列开始同样是输入文件的内容。
#需要注意的是，我们也可以使用-maf 0.05 -reverse过滤掉高于0.05的变异；但是过滤ALT等位基因的频率，我们更提倡使用-score_threshold参数。

dbSNP annotations

通过dbsnp annotation, annovar可以确认已经出现在dbSNP数据库里面的突变并且注释SNP identifiers
命令如下：

#下载dbsnpp138数据库
[kaiwang@biocluster ~/]$ annotate_variation.pl -downdb -buildver hg19 -webfrom annovar snp138 humandb
NOTICE: Web-based checking to see whether ANNOVAR new version is available ... Done
NOTICE: Downloading annotation database http://www.openbioinformatics.org/annovar/download/hg19_snp138.txt.gz ... OK
NOTICE: Downloading annotation database http://www.openbioinformatics.org/annovar/download/hg19_snp138.txt.idx.gz ... OK
NOTICE: Uncompressing downloaded files NOTICE: Finished downloading annotation files for hg18 build version, with files saved at the 'humandb' directory
#使用dbsnp138注释
[kaiwang@biocluster ~/]$ annotate_variation.pl -filter -out ex1 -build hg19 -dbtype snp138 example/ex1.avinput humandb/
NOTICE: Variants matching filtering criteria are written to ex1.hg19_snp138_dropped, other variants are written to ex1.hg19_snp138_filtered
NOTICE: Processing next batch with 15 unique variants in 15 input lines
NOTICE: Database index loaded. Total number of bins is 2858459 and the number of bins to be scanned is 12
NOTICE: Scanning filter database humandb/hg19_snp138.txt...Done
#输入dropped file
[kaiwang@biocluster ~/]$ cat ex1.hg19_snp138_dropped
snp138 rs35561142 1 11403596 11403596 - AT comments: rs35561142, a 2-bp insertion
snp138 rs149123833 1 1404001 1404001 G T comments: rs149123833, a SNP in 3' UTR of ATAD3C
snp138 rs1000050 1 162736463 162736463 C T comments: rs1000050, a SNP in Illumina SNP arrays
snp138 rs1287637 1 5935162 5935162 A T comments: rs1287637, a splice site variant in NPHP4
snp138 rs11209026 1 67705958 67705958 G A comments: rs11209026 (R381Q), a SNP in IL23R associated with Crohn's disease
snp138 rs6576700 1 84875173 84875173 C T comments: rs6576700 or SNP_A-1780419, a SNP in Affymetrix SNP arrays
snp138 rs15842 1 948921 948921 T C comments: rs15842, a SNP in 5' UTR of ISG15
snp138 rs80338939 13 20763686 20763686 G - comments: rs1801002 (del35G), a frameshift mutation in GJB2, associated with hearing loss
snp138 rs2066844 16 50745926 50745926 C T comments: rs2066844 (R702W), a non-synonymous SNP in NOD2
snp138 rs2066845 16 50756540 50756540 G C comments: rs2066845 (G908R), a non-synonymous SNP in NOD2
snp138 rs2066847 16 50763778 50763778 - C comments: rs2066847 (c.3016_3017insC), a frameshift SNP in NOD2
snp138 rs2241880 2 234183368 234183368 A G comments: rs2241880 (T300A), a SNP in the ATG16L1 associated with Crohn's disease
#*dropped文件
第一列如region-based注释的结果一样以数据库命名；
第二列为已经在数据库的突变的indentifier号；
第三列开始同样是输入文件的内容。

该注释使用2012年4月欧洲发布1000基因组计划数据库，输出文件会有两个，*dropped file 和 *filtered file
filtered file里面包含不在过滤数据库内的突变。

**
当然ANNOVAR还有很多功能，我在这里只赘述我自己用到的一些方面，有兴趣的也可以自己去探究
**

参考文献：
ANNOVAR 注释软件
ANNOVAR 官网

Call Me Chevy

ANNOVAR的使用

ANNOVAR的安装

ANNOVAR的程序模块

ANNOVAR的输入文件

ANNOVAR输入文件的格式转换

ANNOVAR注释功能

Table_annovar.pl（可一次完成三种类型的注释）

Annotate_variation.pl

Annotate_variation.pl 实例

Gene-based annotation

Region-based annotation

Filter-based annotation

1000 Genomes Project annotations

dbSNP annotations

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