Samtools

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于 2020-06-11 17:26:59 首次发布

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本文详细介绍了SAMtools的使用方法，包括BAM文件的生成、排序、索引、提取、比对分析及变异检测。涵盖了常用命令如view、sort、merge、index、tview、flagstat、depth等的功能解析与实践案例，适合生物信息学研究者学习。

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安装

去官网下载想要的版本

tar jxvf samtools-1.9.tar.bz2
cd samtools-1.9
./configure --prefix=全路径/samtools-1.9
make
make install

1.0之前的版本没有configure步骤
下载后直接make

SAM


Op  BAM Description                                             query  reference
M   0   alignment match (can be a sequence match or mismatch)   yes   yes
I   1   insertion to the reference                              yes   no
D   2   deletion from the reference                             no    yes
N   3   skipped region from the reference                       no    yes
S   4   soft clipping (clipped sequences present in SEQ)        yes   no
H   5   hard clipping (clipped sequences NOT present in SEQ)    no    no
P   6   padding (silent deletion from padded reference)         no    no
=   7   sequence match                                          yes   yes
X   8   sequence mismatch                                       yes   yes

op    Description
M    Alignment match (can be a sequence match or mismatch
I    Insertion to the reference
D    Deletion from the reference
N    Skipped region from the reference
S    Soft clip on the read (clipped sequence present in <seq>)
H    Hard clip on the read (clipped sequence NOT present in <seq>)
P    Padding (silent deletion from the padded reference sequence)

https://stackoverflow.com/questions/39710796/infer-the-length-of-a-sequence-using-the-cigar
https://github.com/brentp/cigar/blob/754cfed348364d390ec1aa40c951362ca1041f7a/cigar.py#L88-L93

from itertools import groupby

def query_len(cigar_string):
    """
    Given a CIGAR string, return the number of bases consumed from the
    query sequence.
    """
    read_consuming_ops = ("M", "I", "S", "=", "X")
    result = 0
    cig_iter = groupby(cigar_string, lambda chr: chr.isdigit())
    for _, length_digits in cig_iter:
        length = int(''.join(length_digits))
        op = next(next(cig_iter)[1])
        if op in read_consuming_ops:
            result += length
    return result

clipped alignment[S,H]：read只有中间比对上，两侧在比对过程中被忽略

# 3S4M1D5M3S(3 soft, 4 match, 1 deletion, 5 match and 3 soft)
Read:       CGATTGC-TCCGCCAGG
|              |||| ||||||
Ref:CCGATCGAGACTTGCGTCCGCCTCCCGATCA

soft-clipped: bases in 5’ and 3’ of the read are NOT part of the alignment. 部分没比对上但保留在SAM/BAM比对结果中。 if your cigar is 10S10M10S then the SEQ and base-quals will be 30 bases long. 利用soft-clipping算法可以避开由于read两侧质量低而导致整条read比对不上的现象。不过即使被标记为soft clipped保留下来，依然不会在找变异、基因组浏览器可视化、计算覆盖度等过程中被使用（https://www.biostars.org/p/255062/：在计算基因组覆盖度时，几乎全部工具bamCoverage/multiBamSummary甚至samtools view -c都会忽略soft clip）
hard-clipped: bases in 5’ and 3’ of the read are NOT part of the alignment AND those bases have been removed from the read sequence in the BAM file 部分没比对上并且没有保留在SAM/BAM比对结果中。 if your cigar is: 10H10M10H then the SEQ will only be 10 bases long.

in bwa, HARD clipping is used for supplementary reads.
if the read has a chimeric alignment, the paired or the top hit uses soft clipping ；All the other hits part of the chimeric alignment will use hard clipping
chimeric alignment: “嵌合比对” 的形成是由于一条测序read比对到基因组上时分别比对到两个不同的区域，而这两个区域基本没有overlap。因此它在sam文件中需要占用多行记录显示。只有第一个记录被称作"representative",其他的都是"supplementary"【Chimeric reads are also called split reads】；RNA-seq中的chimeric read或许可以说明有融合基因存在，但在基因组中一般作为结构变异的证据

spliced alignment：read一端比对上，跳过中间，然后另一端也比对上【CIGAR中用“N”表示】如果是转录组数据的比对结果，N表示内含子；其他类型组学数据中N也可以用，但没有意义，和deletion一个意思

# 3M1D4M13N5M
#  This only makes sense when you're aligning things like cDNA/expression data.
REF:  ATCGATCGATCGATCGATCGATCGATCGATCG
          ||||||||||||||||||||||||||
QUERY:    ATC-ATCG-------------ATCAT
# 如果是DNA测序reads的比对，也可以全部用D来表示：即3M1D4M13D3M

COMMANDS

提取bed区间内的reads

samtools view -bh -L target.bed bamfile.bam > target.bam
samtools view -hb  bamfile.bam chr:start-end  > target.bam

对bed区间进行window拆分

# 以300K为窗口，每个窗口间隔100K 分割bed
bedtools makewindows -g wgs.bed.txt -w 300000 -s 100000 > windows300k_step100k.bed

计算bed区间的深度，返回区间内覆盖碱基数

samtools bedcov yourbedfile.bed file1.bam

1.view

view主要是将sam文件转换成bam文件；对bam文件进行各种操作，如数据排序(不属于本命令的功能)和提取(这些操作是对bam文件进行，因而当输入为sam文件的时候，不能进行该操作)；最后将排序或提取得到的数据输出为bam或sam（默认的）格式。

bam文件优点：bam二进制文件占用磁盘空间小；bam二进制文件运算速度快。

view命令中，对sam文件头部的输入(-t或-T）和输出(-h)是单独的一些参数来控制的。

Usage: samtools view [options] <in.bam>|<in.sam> [region1 […]]
默认情况下不加 region，则是输出所有的 region.

Options: 【-b】       output BAM
                  默认下输出是 SAM 格式文件，该参数设置输出 BAM 格式
         【-h】       print header for the SAM output
                  默认下输出的 sam 格式文件不带 header，该参数设定输出sam文件时带 header 信息
         【-H】       print header only (no alignments)
         【-S】       input is SAM
                  默认下输入是 BAM 文件，若是输入是 SAM 文件，则最好加该参数，否则有时候会报错。
         -u       uncompressed BAM output (force -b)
                  该参数的使用需要有-b参数，能节约时间，但是需要更多磁盘空间。
         -c       Instead of printing the alignments, only count them and print the  total number. All filter options, such as ‘-f’, ‘-F’ and ‘-q’ , are taken into account.
         -1       fast compression (force -b)
         -x       output FLAG in HEX (samtools-C specific)
         -X       output FLAG in string (samtools-C specific)
         -c       print only the count of matching records
        【-L】 FILE output alignments overlapping the input BED FILE [null]
         -t FILE  list of reference names and lengths (force -S) [null]
                  使用一个list文件来作为header的输入
         【-T】 FILE  reference sequence file (force -S) [null]
                  使用序列fasta文件作为header的输入
         【-o】 FILE  output file name [stdout]
         -R FILE  list of read groups to be outputted [null]
         -f INT   required flag, 0 for unset [0]
         【-F】 INT   filtering flag, 0 for unset [0] 
                  Skip alignments with bits present in INT [0]
                  数字4代表该序列没有比对到参考序列上
                  数字8代表该序列的mate序列没有比对到参考序列上
         【-q】 INT   minimum mapping quality [0]
         -l STR   only output reads in library STR [null]
         -r STR   only output reads in read group STR [null]
         -s FLOAT fraction of templates to subsample; integer part as seed [-1]
         -?       longer help

-f INT only include reads with all of the FLAGs in INT present [0]
-F INT only include reads with none of the FLAGS in INT present [0]
-G INT only EXCLUDE reads with all of the FLAGs in INT present [0]
这里设置的FLAG再记录一下
samtools view bwa.bam | cut -f2 | uniq

| 1 | template having multiple segments in sequencing |
| 2 | each segment properly aligned according to the aligner |
| 4 | segment unmapped |
| 8 | next segment in the template unmapped |
| 16 | SEQ being reverse complemented |
| 32 | SEQ of the next segment in the template being reversed |
| 64 | the first segment in the template |
| 128 | the last segment in the template |
| 256 | secondary alignment |
| 512 | not passing quality controls |
| 1024 | PCR or optical duplicate |
| 2048 | supplementary alignment |

flag解释链接

将sam文件转换成bam文件
$ samtools view -bSabc.sam > abc.bam
$ samtools view -b -Sabc.sam -o abc.bam

提取比对到参考序列上的比对结果
$ samtools view -bF4 abc.bam > abc.F.bam

提取paired reads中两条reads都比对到参考序列的比对结果，只需要把两个4+8的值12作为过滤参数即可
$ samtools view -bF 12abc.bam > abc.F12.bam

提取没有比对到参考序列上的比对结果
$ samtools view -bf 4abc.bam > abc.f.bam

提取bam文件中比对到caffold1上的比对结果，并保存到sam文件格式
$ samtools view abc.bam scaffold1> scaffold1.sam

提取scaffold1上能比对到30k到100k区域的比对结果
$ samtools view abc.bam scaffold1:30000-100000 $gt; scaffold1_30k-100k.sam
$gt?

根据fasta文件，将 header 加入到 sam 或 bam 文件中
$ samtools view -T genome.fasta-h scaffold1.sam > scaffold1.h.sam

2.sort

sort对bam文件进行排序。

Usage: samtools sort [-n] [-m ] <in.bam> <out.prefix>
-m 参数默认下是 500,000,000 即500M（不支持K，M，G等缩写）。对于处理大数据时，如内存够用则设置大点的值以节约时间
-n 设定排序方式按short reads的ID排序。默认下是按序列在fasta文件中的顺序（即header）和序列从左往右的位点排序。

$ samtools sort abc.bam abc.sort ###注意 abc.sort 是输出文件的前缀，实际输出是 abc.sort.bam
$ samtools view abc.sort.bam | less -S

3.merge

将2个或2个以上的已sort了的bam文件融合成一个bam文件。融合后的文件已排序。

Usage: samtools merge [-nr] [-h inh.sam] <out.bam> <in1.bam> <in2.bam>[…]

Options: -n       sort by read names
         -r       attach RG tag (inferred from file names)
         -u       uncompressed BAM output
         -f       overwrite the output BAM if exist
         -1       compress level 1
         -R STR   merge file in the specified region STR [all]
         -h FILE  copy the header in FILE to <out.bam> [in1.bam]

Note: Samtools’ merge does not reconstruct the @RG dictionary in the header. Usersmust provide the correct header with -h, or uses Picard which properly maintains the header dictionary in merging.

4.index

必须对bam文件进行默认情况下的排序后才能进行index

建立索引后将产生后缀为.bai的文件，用于快速的随机处理。很多情况下需要有bai文件的存在，特别是显示序列比对情况下。比如samtool的tview命令需要bai；gbrowse2显示reads的比对图形的时候也需要。

Usage: samtools index <in.bam> [out.index]

以下两种命令结果一样
$ samtools index abc.sort.bam
$ samtools index abc.sort.bam abc.sort.bam.bai

5.faidx

对fasta文件建立索引,生成的索引文件.fai。该命令也能依据索引文件快速提取fasta文件中的某一条（子）序列

Usage: samtools faidx <in.bam> [ […]]

对基因组文件建立索引
$ samtools faidx genome.fasta
生成了索引文件genome.fasta.fai,是一个文本文件，分成了5列。第一列是子序列的名称；第二列是子序列的长度；个人认为“第三列是序列所在的位置”，因为该数字从上往下逐渐变大，最后的数字是genome.fasta文件的大小；第4和5列不知是啥意思。于是通过此文件，可以定位子序列在fasta文件在磁盘上的存放位置，直接快速调出子序列。

由于有索引文件，可以使用以下命令很快从基因组中提取到fasta格式的子序列
$ samtools faidx genome.fasta scffold_10 > scaffold_10.fasta

6.tview

tview能直观的显示出reads比对基因组的情况，和基因组浏览器有点类似。

Usage: samtools tview <aln.bam> [ref.fasta]

当给出参考基因组，第一排显示参考基因组的序列，否则第一排全用N表示。
按下 g，则提示输入要到达基因组的某一个位点。例子“scaffold_10:1000"表示到达第10号scaffold的第1000个碱基位点处。使用H(左）J（上）K（下）L（右）移动显示界面。大写字母移动快，小写字母移动慢。使用空格建向左快速移动（和 L 类似），使用Backspace键向左快速移动（和 H 类似）。Ctrl+H 向左移动1kb碱基距离； Ctrl+L 向右移动1kb碱基距离可以用颜色标注比对质量，碱基质量，核苷酸等。30～40的碱基质量或比对质量使用白色表示；20～30黄色；10～20绿色；0～10蓝色。
使用点号’.'切换显示碱基和点号；使用r切换显示read name等
还有很多其它的使用说明，具体按？键来查看help。

samtools tview -p chr1:3128088 NA12878.bam hg38.fasta
-p 染色体位置
bam需索引
不提供ref则第一行显示N. 需fai
tview 符号用Pileup_format表示，参考https://handwiki.org/wiki/Biology:Pileup_format

Pileup format is a text-based format for summarizing the base calls of aligned reads to a reference sequence. This format facilitates visual display of SNP/indelcalling and alignment. It was first used by Tony Cox and Zemin Ning at the Wellcome Trust Sanger Institute, and became widely known through its implementation within the SAMtools software suite
Column 5: The bases string
. (dot)means a base that matched the reference on the forward strand
, (comma)means a base that matched the reference on the reverse strand
</>(less-/greater-than sign) denotes a reference skip. This occurs, for example, if a base in the reference genome is intronic and a read maps to two flanking exons. If quality scores are given in a sixth column, they refer to the quality of the read and not the specific base.
AGTCN(upper case) denotes a base that did not match the reference on the forward strand
agtcn(lower case) denotes a base that did not match the reference on the reverse strand
A sequence matching the regular expression +[0-9]+[ACGTNacgtn]+ denotes an insertion of one or more bases starting from the next position. For example, +2AG means insertion of AG in the forward strand
A sequence matching the regular expression -[0-9]+[ACGTNacgtn]+ denotes a deletion of one or more bases starting from the next position. For example, -2ct means deletion of CT in the reverse strand
^ (caret)marks the start of a read segment and the ASCII of the character following `^’ minus 33 gives the mapping quality
$ (dollar)marks the end of a read segment
\* (asterisk)is a placeholder for a deleted base in a multiple basepair deletion that was mentioned in a previous line by the -[0-9]+[ACGTNacgtn]+ notation

“shift+?” 显示帮助菜单栏

7.flagstat

给出BAM文件的比对结果

Usage: samtools flagstat <in.bam>

$ samtools flagstat example.bam
11945742 + 0 in total (QC-passed reads + QC-failed reads)
#总共的reads数
0 + 0 duplicates
7536364 + 0 mapped (63.09%:-nan%)
#总体上reads的匹配率
11945742 + 0 paired in sequencing
#有多少reads是属于paired reads
5972871 + 0 read1
#reads1中的reads数
5972871 + 0 read2
#reads2中的reads数
6412042 + 0 properly paired (53.68%:-nan%)
#完美匹配的reads数：比对到同一条参考序列，并且两条reads之间的距离符合设置的阈值
6899708 + 0 with itself and mate mapped
#paired reads中两条都比对到参考序列上的reads数
636656 + 0 singletons (5.33%:-nan%)
#单独一条匹配到参考序列上的reads数，和上一个相加，则是总的匹配上的reads数。
469868 + 0 with mate mapped to a different chr
#paired reads中两条分别比对到两条不同的参考序列的reads数
243047 + 0 with mate mapped to a different chr (mapQ>=5)
#同上一个，只是其中比对质量>=5的reads的数量

8.depth

得到每个碱基位点的测序深度,并输出到标准输出

Usage: bam2depth [-r reg] [-q baseQthres] [-Q mapQthres] [-b in.bed] <in1.bam> […]
-r 后面跟染色体号（region）

-r : 指定区域生成深度
samtools depth -r chr2:25965491-25965491 bam
-b : bed 文件指定区域生成深度

注意：做depth之前必须做samtools index；

samtools depth in.bam > out.depth.txt
注意：in.bam 必须经过了排序。

9.其他

reheader 替换bam文件的头

$ samtools reheader <in.header.sam> <in.bam>
cat 连接多个bam文件，适用于非sorted的bam文件

$ samtools cat [-h header.sam] [-o out.bam] <in1.bam> <in2.bam> [ … ]
idxstats 统计一个表格，4列，分别为”序列名，序列长度，比对上的reads数，unmapped reads number”。第4列应该是paired reads中有一端能匹配到该scaffold上，而另外一端不匹配到任何scaffolds上的reads数。

$ samtools idxstats <aln.bam>

10.将bam文件转换为fastq文件

有时候，我们需要提取出比对到一段参考序列的reads，进行小范围的分析，以利于debug等。这时需要将bam或sam文件转换为fastq格式。
该网站提供了一个bam转换为fastq的程序：http://www.hudsonalpha.org/gsl/information/software/bam2fastq

$ wget http://www.hudsonalpha.org/gsl/static/software/bam2fastq-1.1.0.tgz
$ tar zxf bam2fastq-1.1.0.tgz
$ cd bam2fastq-1.1.0
$ make
$ ./bam2fastq <in.bam>

11.mpileup

samtools还有个非常重要的命令mpileup，以前为pileup。该命令用于生成bcf文件，再使用bcftools进行SNP和Indel的分析。bcftools是samtool中附带的软件，在samtools的安装文件夹中可以找到。

最常用的参数有2： -f 来输入有索引文件的fasta参考序列；-g 输出到bcf格式。用法和最简单的例子如下

Usage: samtools mpileup [-EBug] [-C capQcoef] [-r reg] [-f in.fa] [-l list] [-M capMapQ] [-Q minBaseQ] [-q minMapQ] in.bam [in2.bam […]]

$ samtools mpileup -fgenome.fasta abc.bam > abc.txt
$ samtools mpileup -gSDfgenome.fasta abc.bam > abc.bcf
$ samtools mpileup -guSDfgenome.fasta abc.bam |
bcftools view -cvNg- > abc.vcf
mpileup不使用-u或-g参数时，则不生成二进制的bcf文件，而生成一个文本文件(输出到标准输出)。该文本文件统计了参考序列中每个碱基位点的比对情况；该文件每一行代表了参考序列中某一个碱基位点的比对结果。比如：

scaffold_1      2841    A       11      ,,,...,....     BHIGDGIJ?FF
scaffold_1      2842    C       12      ,$,,...,....^I. CFGEGEGGCFF+
scaffold_1      2843    G       11      ,,...,.....     FDDDDCD?DD+
scaffold_1      2844    G       11      ,,...,.....     FA?AAAA<AA+
scaffold_1      2845    G       11      ,,...,.....     F656666166*
scaffold_1      2846    A       11      ,,...,.....     (1.1111)11*
scaffold_1      2847    A       11      ,,+9acggtgaag.+9ACGGTGAAT.+9ACGGTGAAG.+9ACGGTGAAG,+9acggtgaag.+9ACGGTGAAG.+9ACGGTGAAG.+9ACGGTGAAG.+9ACGGTGAAG.+9ACGGTGAAG       %.+....-..)
scaffold_1      2848    N       11      agGGGgGGGGG     !!$!!!!!!!!
scaffold_1      2849    A       11      c$,...,.....    !0000000000
scaffold_1      2850    A       10      ,...,.....      353333333

mpileup生成的结果包含6行：参考序列名；位置；参考碱基；比对上的reads数；比对情况；比对上的碱基的质量。其中第5列比较复杂,解释如下：

1 ‘.’代表与参考序列正链匹配。
2 ‘,’代表与参考序列负链匹配。
3 ‘ATCGN’代表在正链上的不匹配。
4 ‘atcgn’代表在负链上的不匹配。
5 ‘*’代表模糊碱基
6 ‘^’代表匹配的碱基是一个read的开始；’^'后面紧跟的ascii码减去33代表比对质量；这两个符号修饰的是后面的碱基，其后紧跟的碱基(.,ATCGatcgNn)代表该read的第一个碱基。
7 ‘$’代表一个read的结束，该符号修饰的是其前面的碱基。
8 正则式’+[0-9]+[ACGTNacgtn]+’代表在该位点后插入的碱基；比如上例中在scaffold_1的2847后插入了9个长度的碱基acggtgaag。表明此处极可能是indel。
9 正则式’-[0-9]+[ACGTNacgtn]+’代表在该位点后缺失的碱基；

pileup具体的参数如下：

输入参数
-6 Assume the quality is in the Illumina 1.3+ encoding. -A Do not skip anomalous read pairs in variant calling.
-B Disable probabilistic realignment for the computation of base alignment quality (BAQ). BAQ is the Phred-scaled probability of a read base being misaligned. Applying this option greatly helps to reduce false SNPs caused by misalignments.
-b FILE List of input BAM files, one file per line [null]
-C INT Coefficient for downgrading mapping quality for reads containing excessive mismatches. Given a read with a phred-scaled probability q of being generated from the mapped position, the new mapping quality is about sqrt((INT-q)/INT)*INT. A zero value disables this functionality; if enabled, the recommended value for BWA is 50. [0]
-d INT At a position, read maximally INT reads per input BAM. [250]
-E Extended BAQ computation. This option helps sensitivity especially for MNPs, but may hurt specificity a little bit.
-fFILE The faidx-indexed reference file in the FASTA format. The file can be optionally compressed by razip. [null]
-lFILE BED or position list file containing a list of regions or sites where pileup or BCF should be generated [null]
-M INT cap mapping quality at INT [60]
-qINT Minimum mapping quality for an alignment to be used [0]
-QINT Minimum base quality for a base to be considered [13]
-r STR Only generate pileup in region STR [all sites]

输出参数
-D Output per-sample read depth (require -g/-u)
-g Compute genotype likelihoodsand output them in the binarycall format (BCF).
-S Output per-sample Phred-scaled strand bias P-value (require -g/-u)
-u Similar to -g except that the output is uncompressed BCF, which is preferred for piping.

Options for Genotype Likelihood Computation(for -g or -u):
-e INT Phred-scaled gap extension sequencing error probability. Reducing INT leads to longer indels. [20]
-h INT Coefficient for modeling homopolymer errors. Given an l-long homopolymer run, the sequencing error of an indel of size s is modeled as INT*s/l. [100]
-I Do not perform INDEL calling
-L INT Skip INDEL calling if the average per-sample depth is above INT. [250]
-o INT Phred-scaled gap open sequencing error probability. Reducing INT leads to more indel calls. [40]
-P STR Comma dilimited list of platforms (determined by @RG-PL) from which indel candidates are obtained. It is recommended to collect indel candidates from sequencing technologies that have low indel error rate such as ILLUMINA. [all]

12. samtools rmdup

NGS上机测序前需要进行PCR一步，使一个模板扩增出一簇，从而在上机测序的时候表现出为1个点，即一个reads。若一个模板扩增出了多簇，结果得到了多个reads，这些reads的坐标(coordinates)是相近的。在进行了reads比对后需要将这些由PCR duplicates获得的reads去掉，并只保留最高比对质量的read。使用rmdup命令即可完成.

13.bcftools

bcftools和samtools类似，用于处理vcf(variant call format)文件和bcf(binary call format)文件。前者为文本文件，后者为其二进制文件。

bcftools使用简单，最主要的命令是view命令，其次还有index和cat等命令。index和cat命令和samtools中类似。此处主讲使用view命令来进行SNP和Indel calling。该命令的使用方法和例子为：

$ bcftools view [-AbFGNQSucgv] [-D seqDict] [-l listLoci] [-s listSample]
[-i gapSNPratio] [-t mutRate] [-p varThres] [-P prior]
[-1 nGroup1] [-d minFrac] [-U nPerm] [-X permThres]
[-T trioType] in.bcf [region]

$ bcftools view -cvNg abc.bcf > snp_indel.vcf
生成的结果文件为vcf格式，有10列，分别是：1 参考序列名；2 varianti所在的left-most位置；3 variant的ID（默认未设置，用’.'表示)；4 参考序列的allele；5 variant的allele(有多个alleles，则用’,'分隔);6 variant/reference QUALity;7 FILTersapplied;8 variant的信息，使用分号隔开；9 FORMATof the genotype fields, separated by colon (optional)； 10 SAMPLE genotypes and per-sample information (optional)。
例如：

scaffold_1      2847    .       A       AACGGTGAAG      194     .       INDEL;DP=11;VDB=0.0401;AF1=1;AC1=2;DP4=0,0,8,3;MQ=35;FQ=-67.5   GT:PL:GQ        1/1:235,33,0:63
scaffold_1      3908    .       G       A       111     .       DP=13;VDB=0.0085;AF1=1;AC1=2;DP4=0,0,5,7;MQ=42;FQ=-63   GT:PL:GQ        1/1:144,36,0:69
scaffold_1      4500    .       A       G       31.5    .       DP=8;VDB=0.0034;AF1=1;AC1=2;DP4=0,0,1,3;MQ=42;FQ=-39    GT:PL:GQ        1/1:64,12,0:21
scaffold_1      4581    .       TGGNGG  TGG     145     .       INDEL;DP=8;VDB=0.0308;AF1=1;AC1=2;DP4=0,0,0,8;MQ=42;FQ=-58.5    GT:PL:GQ        1/1:186,24,0:45
scaffold_1      4644    .       G       A       195     .       DP=21;VDB=0.0198;AF1=1;AC1=2;DP4=0,0,10,10;MQ=42;FQ=-87 GT:PL:GQ        1/1:228,60,0:99
scaffold_1      4827    .       NACAAAGA        NA      4.42    .       INDEL;DP=1;AF1=1;AC1=2;DP4=0,0,1,0;MQ=40;FQ=-37.5       GT:PL:GQ        0/1:40,3,0:3
scaffold_1      4854    .       A       G       48      .       DP=6;VDB=0.0085;AF1=1;AC1=2;DP4=0,0,2,1;MQ=41;FQ=-36    GT:PL:GQ        1/1:80,9,0:16
scaffold_1      5120    .       A       G       85      .       DP=8;VDB=0.0355;AF1=1;AC1=2;DP4=0,0,5,3;MQ=42;FQ=-51    GT:PL:GQ        1/1:118,24,0:45

第8列中显示了对variants的信息描述，比较重要，其中的 Tag 的描述如下：

Tag Format Description
AF1 double Max-likelihood estimate of the site allele frequency (AF) of the first ALT allele
DP int Raw read depth (without quality filtering)
DP4 int[4] # high-qualityreferenceforward bases, ref reverse, alternate forand alt revbases
FQ int Consensus quality. Positive: sample genotypes different; negative: otherwise
MQ int Root-Mean-Square mapping quality of covering reads
PC2 int[2] Phred probability of AF in group1 samples being larger (,smaller) than in group2
PCHI2 double Posterior weighted chi^2 P-value between group1 and group2 samples
PV4 double[4] P-value for strand bias, baseQ bias, mapQ bias and tail distance bias
QCHI2 int Phred-scaled PCHI2
RP int # permutations yielding a smaller PCHI2
CLR int Phred log ratio of genotype likelihoods with and without the trio/pair constraint
UGT string Most probable genotype configuration without the trio constraint
CGT string Most probable configuration with the trio constraint
bcftools view 的具体参数如下：

Input/Output Options:
-A Retain all possible alternate alleles at variant sites. By default, the view command discards unlikely alleles.
-b Output in the BCF format. The default is VCF.
-D FILE Sequence dictionary (list of chromosome names) for VCF->BCF conversion [null]
-F Indicate PL is generated by r921 or before (ordering is different).
-G Suppress all individual genotype information.
-l FILE List of sites at which information are outputted [all sites]
-N Skip sites where the REF field is not A/C/G/T
-Q Output the QCALL likelihood format
-s FILE List of samples to use. The first column in the input gives the sample names and the second gives the ploidy, which can only be 1 or 2. When the 2nd column is absent, the sample ploidy is assumed to be 2. In the output, the ordering of samples will be identical to the one in FILE. [null]
-S The input is VCF instead of BCF.
-u Uncompressed BCF output (force -b).

Consensus/Variant Calling Options:
-c Call variants using Bayesian inference. This option automatically invokes option -e.
-d FLOAT When -v is in use, skip loci where the fraction of samples covered by reads is below FLOAT. [0]
当有多个sample用于variants calling时，比如多个转录组数据或多个重测序
数据需要比对到参考基因组上，设置该值，表明至少有该<float 0~1>比例的
samples在该位点都有覆盖才计算入variant.所以对于只有一个sample的情况
下，该值设置在0～1之间没有意义，大于1则得不到任何结果。
-e Perform max-likelihood inference only, including estimating the site allele frequency, testing Hardy-Weinberg equlibrium and testing associations with LRT.
-g Call per-sample genotypes at variant sites (force -c)
-i FLOAT Ratio of INDEL-to-SNP mutation rate [0.15]
-p FLOAT A site is considered to be a variant if P(ref|D)
-t FLOAT Scaled muttion rate for variant calling [0.001]
-T STR Enable pair/trio calling. For trio calling, option -s is usually needed to be applied to configure the trio members and their ordering. In the file supplied to the option -s, the first sample must be the child, the second the father and the third the mother. The valid values of STR are ‘pair’, ‘trioauto’, ‘trioxd’ and ‘trioxs’, where ‘pair’ calls differences between two input samples, and ‘trioxd’ (‘trioxs’) specifies that the input is from the X chromosome non-PAR regions and the child is a female (male). [null]
-v Output variant sites only (force -c)

Contrast Calling and Association Test Options:
-1 INT Number of group-1 samples. This option is used for dividing the samples into two groups for contrast SNP calling or association test. When this option is in use, the following VCF INFO will be outputted: PC2, PCHI2 and QCHI2. [0]
-U INT Number of permutations for association test (effective only with -1) [0]
-X FLOAT Only perform permutations for P(chi^2)
使用bcftools得到variant calling结果后。需要对结果再次进行过滤。主要依据比对结果中第8列信息。其中的 DP4 一行尤为重要，提供了4个数据：1 比对结果和正链一致的reads数、2 比对结果和负链一致的reads数、3 比对结果在正链的variant上的reads数、4 比对结果在负链的variant上的reads数。可以设定（value3 + value4）大于某一阈值，才算是variant。比如：

$ perl -ne 'print $_ if /DP4=(\d+),(\d+),(\d+),(\d+)/ && ($3+$4)>=10 && ($3+$4)/($1+$2+$3+$4)>=0.8' snp_indel.vcf > snp_indel.final.vcf

samtools 版本问题

Note that using “samtools mpileup” to generate BCF or VCF files is now deprecated. To output these formats, please use “bcftools mpileup” instead.
查看之前服务器的版本配置samtools 0.1.18
bcftools 0.1.17-dev