FASTQ 数据质量统计工具

主流工具:

拿到测序数据的第一步就是做质量控制

fqcheck之后得到的结果:

image

它会统计每条reads,按read 1-100位点计算每个位置的ACGTN含量,以及0-41质量值的个数

最终会得到整体的错误率,GC,Q20,Q30

the default quality shift value is: -64, 27877224 sequences, 2787722400 total length, Max length:100, average length:100.00
Standard deviations at 0.25:  total 0.00%, per base 0.01%
···
Error Rate      %GC     Q20     Q30
0.61    48.35   96.26   89.88

 

adapter.list

#reads_id   reads_len   reads_start   reads_end   adapter_id   adapter_len   adapter_start   adapter_end   align_len   mismatch
FCD0JN9ACXX:6:1101:13637:2052#AGAGATCT/1        100     57      90      iPE-3+  34      0       33      34      13
FCD0JN9ACXX:6:1101:15321:2200#AGAGATCT/1        100     53      86      iPE-3+  34      0       33      34      0
FCD0JN9ACXX:6:1101:5318:2346#AGAGATCT/1 100     60      93      iPE-3+  34      0       33      34      0
FCD0JN9ACXX:6:1101:5745:2411#AGAGATCT/1 100     64      97      iPE-3+  34      0       33      34      0
FCD0JN9ACXX:6:1101:13286:2320#AGAGATCT/1        100     89      99      iPE-3+  34      0       10      11      2
FCD0JN9ACXX:6:1101:15982:2390#AGAGATCT/1        100     80      99      iPE-3+  34      0       19      20      0

接头序列,一般都要去掉

Illumina Adapter Sequences Document (1000000002694 v01)

 

过滤

使用SOAPnuke

SOAPnuke filter -l 20 -q 0.5 -n 0.1 -d -i -Q 1 -5 0 -1 1.fq.gz -2 2.fq.gz -f 1.adapter.list.gz -r 2.adapter.list.gz $tile -o 16_1.fq -D 16_2.fq -c 21

过滤后的reads同样要做质量统计

fqcheck -r 16_1.fq.gz -c 16_1.fqcheck

之后还会写个脚本作 fqcheck_distribute 分析

 

过滤后统计 FilterStat

得到

Type    Raw data        Clean data
Number of Reads 52293338        48926594
Data Size       5229333800      4892659400
N of fq1        146135  35060
N of fq2        399754  16287
GC(%) of fq1    45.53   45.36
GC(%) of fq2    45.58   45.39
Q20(%) of fq1   97.03   97.99
Q20(%) of fq2   92.83   95.92
Q30(%) of fq1   91.66   93.58
Q30(%) of fq2   86.07   89.72
Discard Reads related to N      24406   
Discard Reads related to low qual       2917634 
Discard Reads related to Adapter        135524

catRS

drawPizza

 

参考:

质量值体系 Phred33 和 Phred 64 的由来 及其在质量控制中的实际影响 - Part 2

原文地址:https://www.cnblogs.com/leezx/p/6418888.html