Hello,
Your post is very difficult to read with the formatting. The best place
to find out more about the FastQC program is through the tool
documentation, linked from the tool form but also here:
http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/
More below.
On 7/31/13 11:08 PM, Ng Kiaw Kiaw wrote:
Dear Galaxy Officer,
Good day.
I am a new user of Galaxy main server. The tools provided are very
user-friendly. Thanks for the establishment of these.
I just new to the RNA-seq analysis and now in the learning process of
Bioinformatics.
I would like to inquire on the FastaQC report generated on my data.
For your information:
Samples: Plant (dicotyledon)
Type of data: RNA-seq (Illumina HiSeq 2000 with CASAVA v 1.8.2)
Paired ends
Adapter sequence: RPI 15 ( 5'
CAAGCAGAAGACGGCATACGAGA*TTGACATG*TGACTGGAGTTCCTTGGCACCCGAGAATTCCA)
Main purpose of my analysis: Identification of novel transcript and
gene expression studies
I run FastQC on my raw RNA-seq data both forward and reverse. I attach
the FastQC report in this email.
My questions are:
1) The basic statistics shows that my data encoding is Sanger/illumina
1.9. When I grooming my data for downstream analysis in Galaxy, is
that correct I choose "Sanger" for the input FASTQ quality score type?
Yes, if you choose to groom, Sanger is the correct input. Or you can
just assign the datatype to .fastqsanger by clicking on the pencil icon.
More help is in this screencast "FASTQ Prep - Illumina"
https://main.g2.bx.psu.edu/u/galaxyproject/p/screencasts-usegalaxyorg
2) Based on the per base sequence quality, the quality scores are
above 20.0 for both forward and reverse data. Do I still need to trim
off my data?
No, most likely not, this is a reasonable quality score to use as a
baseline.
3) The result for "Per base sequence content", "Per base GC content",
"sequence duplication level" are fail. What are these three results
indicate? What are the solution for these problems?
These are quality metrics and indicate that the data is skewed away from
what would be expected in a normal distribution. You could investigate
the library preparation methods is this is your own data.
4) What the overrepresented sequence indicate? Do I need to trim off
the overrepresented sequence?
Same as above. And yes, if it is a great portion of your data,
repetitive, or causes problem later on, as it effectively "shortens" the
length of the sequence being aligned, even though the sequence is longer
- and this could cause you to pick the wrong length parameters in Tophat.
5) Based on the K-mer content, how could I analyse and justify whether
this is good data or not?
Same as above.
6) In the reverse data FastQC report, "per sequence GC content" seem
not good. What do this indicate?
Same as above.
7) How could I identify the adapter sequence in my RNA-seq data and
how could could I remove?
Locating the methods associated with the preparation of the data is the
first place to look. You could also just trim the reads if the
"overrepresented sequence" is localized to where the adapter is most
likely to be, then trim based off of that range.
8) After grooming data, running FastQC on data, adapter removal, is
there any other pre-processing steps need to be done before running
bowtie and top hat?
Because quality is not an issue, no trimming is necessary. You could
however filter out short sequences that will never be able to meet the
alignment criteria. See the Tophat documentation about how to best tune
parameters to match data based on the length of reads.
All of this said, most of the time, very little needs to be done most of
the time. Poor reads will simply fall out and not align in the first
steps of the pipeline. Trimming and setting Tophat parameters will have
the greatest impact.
Take care,
Jen
Galaxy team
Many Thanks in advance for your kind assistance and supports.
Best regards
Ng Kiaw Kiaw
PhD student
RIKEN Yokohama Campus
Japan.
___________________________________________________________
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--
Jennifer Hillman-Jackson
Galaxy Support and Training
http://galaxyproject.org
___________________________________________________________
The Galaxy User list should be used for the discussion of
Galaxy analysis and other features on the public server
at usegalaxy.org. Please keep all replies on the list by
using "reply all" in your mail client. For discussion of
local Galaxy instances and the Galaxy source code, please
use the Galaxy Development list:
http://lists.bx.psu.edu/listinfo/galaxy-dev
To manage your subscriptions to this and other Galaxy lists,
please use the interface at:
http://lists.bx.psu.edu/
To search Galaxy mailing lists use the unified search at:
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