转录组入门(3)：了解fastq测序数据
需要用安装好的sratoolkit把sra文件转换为fastq格式的测序文件，并且用fastqc软件测试测序文件的质量！
作业，理解测序reads，GC含量，质量值，接头，index，fastqc的全部报告
来源于生信技能树：http://www.biotrainee.com/forum.php?mod=viewthread&tid=1750#lastpost
fastq-dump将sra数据转换成fastq格式
for i in {59..62};
do
echo $i
fastq-dump --gzip --split-3 -O /mnt/hgfs/Labubuntu_data/GSE81916.RNAseq/RNA-Seq -A SRR35899$i.sra;
done
59
Written 30468155 spots for SRR3589959.sra
Written 30468155 spots total
60
Written 52972617 spots for SRR3589960.sra
Written 52972617 spots total
61
Written 36763726 spots for SRR3589961.sra
Written 36763726 spots total
62
Written 43802631 spots for SRR3589962.sra
Written 43802631 spots total
fastq-dump参数：
fastq-dump -h #参看帮助
INPUT
-A|--accession <accession> #路径下文件名
--table <table-name>
OUTPUT
-O|--outdir <path> #结果文件输出路径
-Z|--stdout #标准输出
--gzip #结果压缩成格式gzip
--bzip2 #结果压缩成格式bzip2
Multiple File Options
--split-files
--split-3 #PE squence产生files *_1.fastq and *_2.fastq 两个文件
fastq文件
fastq文件格式
fastq格式是一种基于文本用来储存生物序列和序列对应质量的文件格式；生物序列和质量均使用单一ASCII码编码。
@E00491:115:H3G7WCCXY:1:1101:30787:1731 1:N:0:ACAAGCTA
TGAATAAGTTGGTTCTAGCGGAGTTTCTGTTCCTTGTCCATAAAGCATCTAACCGCCCTGTGCTCAACTCACGCCGTCTAAAGACAGGAAAGGGAAGTGTCAAGCAGTGTACGATTTGTTTCTAAACTGTACAGTGGCGATTTTTCTAGA
\+
AAAFAJAAF7AJFF<JFJFF-JJFJJ-F----F7<F-<--<-<FAAF--<FFJJAJ<FAF------<--7<F--77----7--------7---<77-<------7---77A-----7-<--7AF-<A<---7----)))))-77------
第1行：以@开头的序列ID，空格后跟着描述性内容；
第2行：序列（碱基序列或者核酸序列）；
第3行：以+开头的序列ID，空格后跟着描述性内容；有时为了节省存储空间会只保留+；
第4列：序列测序质量，每个质量字符与序列字符一一对应；
测序质量对应的ASCII码（由低到高排列）：
!"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[]^_`abcdefghijklmnopqrstuvwxyz{|}~
Illumina sequence identifiers
@HWUSI-EAS100R:6:73:941:1973#0/1
| 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) |
从版本illumina 1.4以后，有所改变：
@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 is filtered, N otherwise |
| 18 | 0 when none of the control bits are on, otherwise it is an even number |
| ATCACG | index sequence |
质量Q值的计算：
Q值与p值对应。 #P值是每个碱基测序错误率
这儿有两个转换公式：
The first is the standard Sanger variant to assess reliability of a base call, otherwise known as Phred quality score:
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).
Q与p值之间的关系：红色的为phred对应方程，黑色的为Illumina对应方程，虚线表明p=0.05，对应的质量得分为Q≈13
Phred+33与Phred+64：
Phred+64：质量字符的ASCII值 = Q + 64
Phred+33: 质量字符的ASCII值= Q + 33
