为了便于测序数据的发布和共享,高通量测序数据以FASTQ 格式来记录所测的碱基读段和质量分数.如下图 所示,FASTQ 格式以测序读段为单位存储,每条读段占4 行,其中第1 行和第3行由文件识别标志和读段名(ID)组成(第1 行以“@”开头而第3 行以“+”开头;第3 行中ID 可以省略,但“+”不能省略),第2 行为碱基序列,第4行为对应的测序质量分数.






HWUSI-EAS100R the unique instrument name
6 flowcell lane
73 tile number within the flowcell lane
941 'x'-coordinate of the cluster within the tile
1973 'y'-coordinate of the cluster within the tile
#0 index number for a multiplexed sample (0 for no indexing)
/1 the member of a pair, /1 or /2 (paired-end or mate-pair reads only)  


Versions of the Illumina pipeline since 1.4 appear to use #NNNNNN instead of #0 for the multiplex ID, where NNNNNN is the sequence of the multiplex tag.

With Casava 1.8 the format of the '@' line has changed:

@EAS139:136:FC706VJ:2:2104:15343:197393 1:Y:18:ATCACG
EAS139 the unique instrument name
136 the run id
FC706VJ the flowcell id
2 flowcell lane
2104 tile number within the flowcell lane
15343 'x'-coordinate of the cluster within the tile
197393 'y'-coordinate of the cluster within the tile
1 the member of a pair, 1 or 2 (paired-end or mate-pair reads only)
Y Y if the read fails filter (read is bad), N otherwise
18 0 when none of the control bits are on, otherwise it is an even number
ATCACG index sequence


传统测序的质量值是基于Phred quality scores,定义如下:

Phred quality scores are defined as a property which is logarithmically related to the base-calling error probabilities P.

Q=-10 log10P
Phred quality scores are logarithmically linked to error probabilities

Phred Quality Score Probability of incorrect base call Base call accuracy
10 1 in 10 90 %
20 1 in 100 99 %
30 1 in 1000 99.9 %
40 1 in 10000 99.99 %
50 1 in 100000 99.999 %

The Solexa pipeline (i.e., the software delivered with the Illumina Genome Analyzer) earlier used a different mapping, encoding the odds p/(1-p) instead of the probability p:


Although both mappings are asymptotically identical at higher quality values, they differ at lower quality levels (i.e., approximately p > 0.05, or equivalently, Q < 13).

FastQ格式介绍为了便于序列存储,通常采用单字符来标示序列的质量值。至于序列的quality values值,是通过一些算法得出来的。即:用字母的ASCII值减去相应的数(不同测序平台数值不一样),然后就得到Q值,然后通过前面的计算公式计算出碱基的测序错误率。



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