Transcription group entry (3): Learn about fastq Sequencing data and fastq sequencing

Transcription group entry (3): Learn about fastq Sequencing data and fastq sequencing
Sra file to fastq format

fastq-dump -h

-- Split-3: If the SRA file contains only one file, this parameter is ignored. If the original file contains two files, it will separate the files in pairs by * _ 1. fastq, * _ 2. fastq. If a third file exists, it means that the file itself is not paired. It may be that some data was deleted because it was filtered out in advance during the initial submission. -- The gzip output file is compressed into the gzip format ( Generally, gzip is only used to compress a single file. The upload or. tgz file is called the "tar compressed package" or "tarball") -- Compress bzip2 output files to bzip2 format (bzip2 is more efficient than traditional gzip or ZIP files, but it is slower to compress)

ls *.sra|while read id;do(fastq-dump --split-3 $id);done

Our data is the double-end sequencing of Illumina, so we use the fastq-dump -- split-3 command to convert the sra format data to fastq. There are A total of 7 sequencing data, so it is best to change the name synchronously, with the-A parameter, to save space, use -- gzip compression.

perl -F'\t' -alne 'if($F[7]=~/SRR/){$F[6]=~s/\s/_/g;$F[13]=~s/\s|#/_/g;$F[13]=~s/\(|\)//g;print "$F[7]\t$F[6]_$F[13]"}' SraRunTable.txt > Rename.txtperl -F'\t' -alne 'print "fastq-dump --split-3 --gzip -A $F[1] $F[0].sra"' Rename.txt > sratofq.sh
bash sratofq.sh

Before data verification and backup storage, you should perform md5sum data transmission integrity verification. Or, after obtaining your own data, compress the data, produce the MD5 file, and back up and save the data.

md5sum *.fastq.gz > md5sum.txt

Quality control FastQC

Mkdir rna_seq/work & cd rna_seq/workln .. /data /*. # create a soft connection mkdir using fastqc_raw_datals *. gz | while read id; do (fastqc $ id-o Required fastqc_raw_data-t 3); done

Q: What are important in the FastQC report? Note: 1. Data quality control is a comprehensive evaluation standard. The main indicators are base quality and content distribution. If the two indicators are qualified, most of the subsequent indicators can pass. If the two items fail, the remaining items will be affected. 2. Some of these indicators are not suitable for all data. You must analyze the data according to the specific data type.