Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • #16
    Originally posted by Thomas Doktor View Post
    I'm trying to use htseq-count version 0.4.2-p3 on a sam file produced by TopHat and a hg19 Ensembl GTF file. I'm analysing the reads in non-stranded mode and looking for exons in the gene_id features. The script runs for a while and outputs several warnings about reads incorrectly flagged as proper pairs, but then exits with the following error:
    Is this an error in my sam file and if so how can I identify the read in question?
    Could you post the relevant code?
    --
    Senthil Palanisami

    Comment


    • #17
      Hi Thomas

      Originally posted by Thomas Doktor View Post
      I'm trying to use htseq-count version 0.4.2-p3 on a sam file produced by TopHat and a hg19 Ensembl GTF file. I'm analysing the reads in non-stranded mode and looking for exons in the gene_id features. The script runs for a while and outputs several warnings about reads incorrectly flagged as proper pairs, but then exits with the following error:
      Is this an error in my sam file and if so how can I identify the read in question?
      Line 100 in count.py, where the error occured, was supposed to tell you that htseq-count encountered a read, which has been aligned to a chromosome that did not appear in the GFF file, and that the read has hence been skipped. I've corrected the bug, in version 0.4.2-p4, you not get a proper warning, telling you the ID of the offending read and the name of the unknown chromosome. Please try again.

      As for the warnings about improper pairs: Have you sorted your SAM file before calling htseq-count? This is necessary to make sure that the read pairs appear in adjacent lines (see man page).

      Simon

      Comment


      • #18
        Hi Simon

        Thanks for the updated source. I did sort my sam file prior to analysis and although most read pairs seem to be in adjacent lines, some reads are lacking a mate. I suspect this is because TopHat does not discard unmated reads. The question is if I should remove these unmated reads or if the script considers them in the read count and merely displays a warning?

        As it turns out, my GFF file is lacking the mitochondrial encoded genes.

        On another note, the script seems to read the GFF file before checking if the sam file exists and as my GFF file is quite large it takes a couple of minutes for the script to exit when I - as happens - sometimes forget to supply an existing sam file. I think it would be nice to have the script check that the files exist as the first thing and then exit immediately upon error.

        Comment


        • #19
          Hi Simon,

          I am using htseq-count with the -q option. However I'm still getting warnings telling me that htseq-count encountered a read, which has been aligned to a chromosome that did not appear in the GFF file. Any ideas on how to resolve this?

          The command I'm using is:
          htseq-count -q <sam_file> <gff_file>

          Comment


          • #20
            Originally posted by joro View Post
            \I am using htseq-count with the -q option. However I'm still getting warnings telling me that htseq-count encountered a read, which has been aligned to a chromosome that did not appear in the GFF file.
            I've just fixed this. It now runs properly quiet with the '-q' option.

            Simon

            Comment


            • #21
              Dear Simon,

              thanx for this package.

              So far everything works except when I try to use htseq-count using tophat output sam file as input and a refseq gff file that has worked just fine with tophat.

              This is the error I am getting:


              Code:
              Error: invalid literal for int() with base 10: '0.000000'
              [Exception type: ValueError, raised in __init__.py:200]

              Comment


              • #22
                Hi

                Originally posted by marcora View Post
                This is the error I am getting:


                Code:
                Error: invalid literal for int() with base 10: '0.000000'
                [Exception type: ValueError, raised in __init__.py:200]
                I noticed this bug myself just yesterday and fixed it. Please try again with version 0.4.3-p4 and tell me whether this solves the issue.

                Cheers
                Simon

                Comment


                • #23
                  Great - thanks for the quick reply.

                  Comment


                  • #24
                    Thanx a lot Simon.

                    One more thing. It is unclear from your comments here and from the doc online whether HTseq handles both GTF and GFF interchangeably. I am new to this bioinformatics business, and already all these formats are giving me an headache, expecially when GTF files are easily available but no standard/robust GTF>GFF converter is readily available.

                    Cheers

                    Comment


                    • #25
                      Hi Marcora

                      Yes, there is a very robust GTF->GFF converter available: Just don't do anything, because every GTF file is a GFF file as well.

                      GTF is a tightening of the GFF specification. This means: If your file has tab-separated fields with the contents <seqname> <source> <feature> <start> <end> <score> <strand> <frame> [attributes] [comments], it is a GFF file. The GFF specs are a bit lax about how certain columns are to be filled. Should the ID in the attributes field be called "ID" or "gene_ID" or "gene"? Which words should be used in the feature column? If you want to have a general format, it is hard to give clear rules, but once you have agreed that you want to describe not any kind of feature, but specifically gene models, you can be more explicit. This is what the GTF specification does: it explains how precisely a GFF file should look like if it is used to describe gene models, and if a GFF file follows these rules, it is called a GTF file.

                      Specifically for htseq-count: If you want to count reads in genes and have a GTF file, you can use it out of the box. If you want to count reads in some other kind of feature, and your GFF file hence cannot follow the GTF specs, you have to tell htseq-count which feature types it should use and how the field with the ID is named. (By default, it takes the lines with feature type "exon" and looks for the ID in the attribute field "gene_id", which is what makes sense for GTF files.)

                      I hope that clarifies it.

                      Simon

                      Comment


                      • #26
                        Dear Simon,

                        thanx for the clear explanation. Is the lax part of GFF that makes going from GTF to GFF "difficult" sometimes, for example when a piece of software requires GFF with specific "comments" (tophat?).

                        Thanx again for your time and consideration,

                        Dado

                        Comment


                        • #27
                          Hi Simon,

                          I was trying to use htseq-qa to assess the technique quality of my aligned sam file, but I've encountered the following errors. While, when I used the command on my solexa-fastq file, I got the quality plot successfully. My sam file was generated by bwa-0.5.7.

                          $htseq-qa -t sam q -r 30 s_8.sam
                          Traceback (most recent call last):
                          File "/Library/Frameworks/Python.framework/Versions/2.6/bin/htseq-qa", line 5, in <module>
                          pkg_resources.run_script('HTSeq==0.4.3-p4', 'htseq-qa')
                          File "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/setuptools-0.6c11-py2.6.egg/pkg_resources.py", line 489, in run_script
                          File "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/setuptools-0.6c11-py2.6.egg/pkg_resources.py", line 1207, in run_script
                          File "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/HTSeq-0.4.3_p4-py2.6-macosx-10.3-fat.egg/EGG-INFO/scripts/htseq-qa", line 5, in <module>
                          HTSeq.scripts.qa.main()
                          File "/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/HTSeq-0.4.3_p4-py2.6-macosx-10.3-fat.egg/HTSeq/scripts/qa.py", line 124, in main
                          r.add_qual_to_count_array( qual_arr_A )
                          File "_HTSeq.pyx", line 715, in _HTSeq.SequenceWithQualities.add_qual_to_count_array (src/_HTSeq.c:12251)
                          File "_HTSeq.pyx", line 734, in _HTSeq.SequenceWithQualities.add_qual_to_count_array (src/_HTSeq.c:12169)
                          ValueError: Too large quality value encountered.

                          $ htseq-qa -t solexa-fastq -r 30 s_8_sequence.txt (This time, it works with fastq file).

                          I am not sure is this a problem with my BWA alignment or with htseq-qa. It would be very much appreciated if you could put some of your input here!

                          Yuan

                          Comment


                          • #28
                            Hi Yuan

                            Originally posted by yh253 View Post
                            ValueError: Too large quality value encountered.
                            Usually, SAM files don't contain quality values exceeding 40. When you aligned your _sequence.txt file, did you convert the quality strings from Solexa to Sanger scale? If not, BWA probably might not have found the optimal alignments, and htseq-qa gets confused, too.

                            If you did, and the large quality values are legitimate, I'd be interested to see your SAM file.

                            Simon

                            Comment


                            • #29
                              Hi Simon,

                              I am afraid not. Actually I was not aware of this issue until now.I will try to figure out how to convert the quality strings first then, and give a feedback on this later.Thanks again for your prompt reply!

                              Yuan

                              Comment


                              • #30
                                Hi Simon,

                                I am having difficulty in running the htseq-qa script. I think I have installed HTSeq correctly since I get no error message for "import HTSeq" command. Then on giving the "htseq-qa -t sam accepted.sam" command, I get a Syntax error. I have given the following export command in Unix

                                export PYTHONPATH=$PYTHONPATH:/Library/Python/2.6/

                                Is this wrong? On giving the command "whereis python", I get /usr/local/python. I am confused.

                                Thank you
                                Abhijit

                                Comment

                                Latest Articles

                                Collapse

                                • seqadmin
                                  Best Practices for Single-Cell Sequencing Analysis
                                  by seqadmin



                                  While isolating and preparing single cells for sequencing was historically the bottleneck, recent technological advancements have shifted the challenge to data analysis. This highlights the rapidly evolving nature of single-cell sequencing. The inherent complexity of single-cell analysis has intensified with the surge in data volume and the incorporation of diverse and more complex datasets. This article explores the challenges in analysis, examines common pitfalls, offers...
                                  06-06-2024, 07:15 AM
                                • seqadmin
                                  Latest Developments in Precision Medicine
                                  by seqadmin



                                  Technological advances have led to drastic improvements in the field of precision medicine, enabling more personalized approaches to treatment. This article explores four leading groups that are overcoming many of the challenges of genomic profiling and precision medicine through their innovative platforms and technologies.

                                  Somatic Genomics
                                  “We have such a tremendous amount of genetic diversity that exists within each of us, and not just between us as individuals,”...
                                  05-24-2024, 01:16 PM

                                ad_right_rmr

                                Collapse

                                News

                                Collapse

                                Topics Statistics Last Post
                                Started by seqadmin, 06-21-2024, 07:49 AM
                                0 responses
                                14 views
                                0 likes
                                Last Post seqadmin  
                                Started by seqadmin, 06-20-2024, 07:23 AM
                                0 responses
                                14 views
                                0 likes
                                Last Post seqadmin  
                                Started by seqadmin, 06-17-2024, 06:54 AM
                                0 responses
                                16 views
                                0 likes
                                Last Post seqadmin  
                                Started by seqadmin, 06-14-2024, 07:24 AM
                                0 responses
                                25 views
                                0 likes
                                Last Post seqadmin  
                                Working...
                                X