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genetica:bioinf_process:fastqc

The evaluation of data quality of the fatsq files is the first one of several Quality Control (QC) steps in the analysis of Next Generation Sequnecing (NGS) data. For such purpose we will use the software FastQC.

The process is quite simple:

  1. Download and install FastQC in your local server following instructions. In detritus it can be found at /opt/exoma/bin/fastqc.
  2. Create a directory where to save the outputs of FastQC, for example name it fastqcRawdata
  3. Check the quality by typing: $ fastqc -o fastqcRawdata *_1_sequence.fq.gz
    1. the file does not need to be decompressed to run FastQc
  4. This generates a folder for each file analyzed with several files:
    1. fastqc_data.txt - this contains the quality statistics in txt format.
    2. summary.txt - contains a summary of this file quality statistics in form of pass or not pass
    3. fastqc_report.html - same as before but it can be opened with $ firefox fastqc_report.html which allows viewing graphs
    4. Icons - folder with
    5. Images - folder with graphs as png

To understand the output, there is a nice explanatory video by Babraham Institute.


Example of running FastQC in one of our samples:

Bonn's fastq files are stored at directory: Bonn_0_fastq, under different folders according to its plate of origin, hence:

[vifehe@detritus bonn_data]$ ls Bonn_0_fastq/
P1_001-040     P1_041-080          P1_081-095
P2_001-040     P2_041-080          P2_081-095 
P3_001-040     P3_041-080          P3_081-095
P4_001-040     P4_081-095          P4_041-080  P5_001-017

# we create the directory where we will save FastQC output:

[vifehe@detritus Bonn_0_fastq]$ touch fastqcRawdata

# and we further create directories for each of the plates

[vifehe@detritus Bonn_0_fastq]$ cd fastqcRawdata
[vifehe@detritus fastqcRawdata]$ touch fastqcRawdata_P1 fastqcRawdata_P2 fastqcRawdata_P3 fastqcRawdata_P4

# to run fastqc on a single file, return to folder where we have our vcf files

[vifehe@detritus fastqcRawdata]$ cd ..
[vifehe@detritus Bonn_0_fastq]$ cd P1_001-040
#to see just the first two files
[vifehe@detritus P1_001-040]$ ls | head -n2    
SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
SN7640211_14074_P1A01_MND1014_2_sequence.fq.gz
[vifehe@detritus P1_001-040]$ fastqc -o ../fastqcRawdata/fastqcRawdata_P1 Started analysis of SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
Started analysis of SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz  # started at 13:57
Approx 5% complete for SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
Approx 10% complete for SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
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Approx 35% complete for SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
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Approx 45% complete for SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
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Approx 95% complete for SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
Approx 100% complete for SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
Analysis complete for SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz # finished at 14:09
# the process per sample takes about 12 minutes
#this can be run in a loop
[vifehe@detritus P1_001-040]$  for x in P1_001-040/*.gz; do fastqc -o ../fastqcRawdata/fastqcRawdata_P1/ $x; done
# to examine the output 
[vifehe@detritus P1_001-040]$ cd ../fastqcRawdata/fastqcRawdata_P1

#the program has created a folder named like the sequence and another compressed folder
[vifehe@detritus fastqcRawdata_P1]$ ls | head -n2 
SN7640211_14074_P1A01_MND1014_1_sequence.fq_fastqc
SN7640211_14074_P1A01_MND1014_1_sequence.fq_fastqc.zip

#list the contents of the folder created
[vifehe@detritus fastqcRawdata_P1]$ cd SN7640211_14074_P1A01_MND1014_1_sequence.fq_fastqc
[vifehe@detritus SN7640211_14074_P1A01_MND1014_1_sequence.fq_fastqc]$ ls
fastqc_data.txt  fastqc_report.html  Icons  Images  summary.txt

#examine Summary.txt output
[vifehe@detritus SN7640211_14074_P1A01_MND1014_1_sequence.fq_fastqc]$ cat summary.txt
PASS	Basic Statistics	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
PASS	Per base sequence quality	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
PASS	Per sequence quality scores	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
PASS	Per base sequence content	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
PASS	Per base GC content	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
WARN	Per sequence GC content	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
PASS	Per base N content	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
PASS	Sequence Length Distribution	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
WARN	Sequence Duplication Levels	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
PASS	Overrepresented sequences	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz
PASS	Kmer Content	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz

# examine fastqc_data.txt output
[vifehe@detritus SN7640211_14074_P1A01_MND1014_1_sequence.fq_fastqc]$ more -n20  fastqc_data.txt
##FastQC	0.10.1
>>Basic Statistics	pass
#Measure	Value	
Filename	SN7640211_14074_P1A01_MND1014_1_sequence.fq.gz	
File type	Conventional base calls	
Encoding	Sanger / Illumina 1.9	
Total Sequences	44012752	
Filtered Sequences	0	
Sequence length	101	
%GC	49	
>>END_MODULE
>>Per base sequence quality	pass
#Base	Mean	Median	Lower Quartile	Upper Quartile	10th Percentile	90th Percentile
1	31.64506284451379	33.0	31.0	34.0	28.0	34.0
2	31.880190722906853	34.0	31.0	34.0	28.0	34.0
3	31.972653289210363	34.0	31.0	34.0	28.0	34.0
4	35.39369340049448	37.0	35.0	37.0	32.0	37.0
5	35.09201710449735	37.0	35.0	37.0	32.0	37.0
6	35.08697933726116	37.0	35.0	37.0	32.0	37.0
7	35.06162818448617	37.0	35.0	37.0	32.0	37.0
....
....
....
>>Sequence Duplication Levels	warn
#Total Duplicate Percentage	33.90859348891959
#Duplication Level	Relative count
1	100.0
2	29.769972680482393
3	10.634235430848415
4	4.525832792477321
5	1.99009856157457
6	1.1335335758380753
7	0.6905347682369101
8	0.447526904442063
9	0.296590343078804
10++	1.4482363062804704
>>END_MODULE
>>Overrepresented sequences	pass
>>END_MODULE
>>Kmer Content	pass
>>END_MODULE


# Explore html file
[vifehe@detritus SN7640211_14074_P1A01_MND1014_1_sequence.fq_fastqc]$ firefox fastqc_report.html 
# this opens the file in firefox in which the following pictures can be seen

per base quality  per sequence quality  per base sequence content  per base gc content per sequence GC content per base N contentsequence length distribution  sequence duplication levels


Because examining each file is time consuming, I've created a couple of scripts with which we can extract the information of our interest:

script1 - to summarize output from summary.txt

script2 - to summarize output from fastqc_data.txt

genetica/bioinf_process/fastqc.txt · Last modified: 2023/01/02 15:31 by osotolongo