Might help us if you demonstrated that the file is indeed not empty. How about a 'ls -l' on the file. Or an 'od -c yourfile.sff | head --lines 4' or the actual command you sent to SeqIO.convert so that we can be sure that you did send your file to it.
Unconfigured Ad
Collapse
X
-
Hi,
I was actually able to get it to run today.. Not sure what the problem was yesterday. But i got some funny results anyhow. Some of the nt's are uppercase and some are lowercase. This caused problems for some of the Galaxy fastx tools that summarize quality data.
Any thoughts?
@HH42GP401CAJLD
gactagactcgacgtGTACTCAGGCTCGCACCGTGGCATGTCGCACTGTACTCAAGGCTCGCACCGTGGCATGTCGCACTGTACTTAAGGCTCACACCGTGGCATGTCGCACTGTACTCAAGGCACACAGGGGntaggnn
+
IIIIIIIIIIIIIIIIIIIGD666IIIIIIIIGDDDIIIIIIIIIIIIIIIGB;;;;IIIGGGGGCC>>>CIHID@@@C==:99==GGIIIIHIIIIIIIGGGCCCHIDDDC@777@C>1111AA@>;84445!;:44!!
@HH42GP401B4BC5
gactagactcgacgtGCAGTAGCTGCAATGGCGCAGAAGGCGTGCTTCtctctcncacgcacacacgagagagagngnnn
+
FFFFFFFFFFFFFFFIIIIIIIIIFFFFDDAAAB?<4444<>>9422323663/!//5///59=///2222////!2!!!
The code that I ran is here, (117,221 is the right number of reads for this file)
>>> SeqIO.convert("454Reads.JA11255_155_RL13.sff", "sff", "untrimmed.fastq", "fastq")
117221
Comment
-
-
You'll see the same from Roche's own tools. The lower case are the bits which would be trimmed off as adapters or low quality bases.Originally posted by lplough81 View PostHi,
I was actually able to get it to run today.. Not sure what the problem was yesterday. But i got some funny results anyhow. Some of the nt's are uppercase and some are lowercase.
That could be an oversight in fastx - ask them about it.Originally posted by lplough81 View PostThis caused problems for some of the Galaxy fastx tools that summarize quality data.
Any thoughts?
Or, what you probably want to do is ask for the trimmed sequences (which will be all upper case):
Code:SeqIO.convert("454Reads.JA11255_155_RL13.sff", "sff-trim", "trimmed.fastq", "fastq")
Comment
-
-
There are two things to consider - getting rid of the adapter sequences and quality trimming. Roche does a good job of this as part of the base calling and production of the SFF file. When reading SFF files, Biopython (and other tools like sff_extract and Roche's own tools) will just apply the trimming information recorded in the SFF file. Using the Roche trimming is usually fine.Originally posted by lplough81 View PostGot it. Fairly new work for me, so I appreciate the patient replies. Can I specify the quality cutoff for trimming? Or what is the default that the biopython fastq trimmer uses?
You may need to further trim off PCR primers or other library specific adapters if the Roche software wasn't told about them.
You may decide to further apply some quality cutoff trimming as well. This may be a good idea for some downstream analysis, not for others.
It is possible to do this kind of trimming in Biopython, but not in one line. There are some examples in the tutorial. I've written some SFF trimming tools using Biopython available within the Galaxy Tool Shed (if your institute runs its own Galaxy instance that may be interesting).
There are also other tools which will do it for you - especially if you want to work with the FASTQ file (or FASTA+QUAL) instead of the SFF file.
Comment
-
-
how to trim FASTA name
Hi,
Is there a simple way to reduce the fasta name (e.g /
"> HH42GP401CAJLD length=118 xy=0823_0287 region=1 run=R_2012_01_27_13_59_03_ "
to ">HH42GP401CAJLD"?
Similar to trimming an SFF file to FASTA with biopython SeqIOconvert(), but taking a fasta file as the input and then outputting another fasta file?
Thanks,
Louis
Comment
-
-
Try something like this, untested:
print "Saved %i records" % countCode:from Bio import SeqIO in_file = "example.fasta" out_file = "new.fasta" file_format = "fasta" def remove_descr(record): record.description="" return record #This is a generator expression - not all in memory at once! wanted = (remove_descr(r) for r in SeqIO.parse(in_file, file_format)) count = SeqIO.write(wanted, out_file, file_format)
Comment
-
-
I don't think you need a script for that. If your file is "454reads.fas" then just do:Originally posted by lplough81 View PostHi,
Is there a simple way to reduce the fasta name (e.g /
"> HH42GP401CAJLD length=118 xy=0823_0287 region=1 run=R_2012_01_27_13_59_03_ "
to ">HH42GP401CAJLD"?Code:sed 's/\s.*//' 454reads.fas > 454reads_trimmedheader.fas
Comment
-
-
@kmcarr: I found your script very useful and I am currently as a MSc Bioinformatics students working on an assignment which involves developing a web interface to a little mapping pipeline. This is purely for educational purposes. Would I be allowed to use your script to prepare the fastq file for the pipeline?Originally posted by kmcarr View PostNice catch drio, thanks. One of those really subtle things you don't catch until you work with a different set of files.
Eugeni, sorry I didn't get back to you on this; got really crushed at work. I have uploaded a modified version of the script incorporating drio's fix.
I really would appreciated it.
Comment
-
Latest Articles
Collapse
-
by SEQadmin2
Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
...-
Channel: Articles
07-09-2026, 11:10 AM -
-
by SEQadmin2
Cancer survival rates have significantly increased in the last few decades in the United States, reaching a combined 70% 5-year survival rate by 2021. Behind this number, there are years of research to find new therapies, drug targets, and early detection methods. But there is one core challenge that keeps slowing down these advances, and it’s about drug resistance.
There is no single reason why many patients don’t respond to treatment as expected. Cancer is...-
Channel: Articles
07-08-2026, 05:17 AM -
-
by GATTACATLove this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
-
Channel: Articles
07-01-2026, 11:43 AM -
ad_right_rmr
Collapse
News
Collapse
| Topics | Statistics | Last Post | ||
|---|---|---|---|---|
|
Started by SEQadmin2, 07-13-2026, 10:26 AM
|
0 responses
22 views
0 reactions
|
Last Post
by SEQadmin2
07-13-2026, 10:26 AM
|
||
|
Started by SEQadmin2, 07-09-2026, 10:04 AM
|
0 responses
32 views
0 reactions
|
Last Post
by SEQadmin2
07-09-2026, 10:04 AM
|
||
|
Started by SEQadmin2, 07-08-2026, 10:08 AM
|
0 responses
20 views
0 reactions
|
Last Post
by SEQadmin2
07-08-2026, 10:08 AM
|
||
|
Started by SEQadmin2, 07-07-2026, 11:05 AM
|
0 responses
34 views
0 reactions
|
Last Post
by SEQadmin2
07-07-2026, 11:05 AM
|
Comment