Closed mattdoug604 closed 4 years ago
Some warnings showing up that should be fixed
tools/generate_ensembl_json.py:129: DeprecationWarning: time.clock has been deprecated in Python 3.3 and will be removed from Python 3.8: use time.perf_counter or time.process_time instead
elapsed = time.clock() - last_time_called[0]
tools/generate_ensembl_json.py:136: DeprecationWarning: time.clock has been deprecated in Python 3.3 and will be removed from Python 3.8: use time.perf_counter or time.process_time instead
Merging #207 into develop will increase coverage by
10.69%
. The diff coverage isn/a
.
@@ Coverage Diff @@
## develop #207 +/- ##
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+ Coverage 80.48% 91.18% +10.69%
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Files 52 52
Lines 9123 9123
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+ Hits 7343 8319 +976
+ Misses 1780 804 -976
Flag | Coverage Δ | |
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#unittests | 91.18% <ø> (+10.69%) |
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Impacted Files | Coverage Δ | |
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mavis/annotate/fusion.py | 96.02% <0.00%> (+0.33%) |
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mavis/bam/cigar.py | 98.14% <0.00%> (+0.61%) |
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mavis/schedule/job.py | 78.26% <0.00%> (+0.72%) |
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mavis/cluster/main.py | 90.24% <0.00%> (+0.81%) |
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mavis/annotate/genomic.py | 93.12% <0.00%> (+1.03%) |
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mavis/breakpoint.py | 94.61% <0.00%> (+1.15%) |
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mavis/illustrate/elements.py | 96.37% <0.00%> (+1.69%) |
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mavis/blat.py | 90.27% <0.00%> (+1.85%) |
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mavis/align.py | 92.65% <0.00%> (+2.23%) |
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mavis/annotate/file_io.py | 88.73% <0.00%> (+2.25%) |
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... and 15 more |
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I realized the hugo alias file is a misnomer. The hugo name is the 'gene_name' taken from the pyensembl annotations. We've only used the "hugo file" to add other aliases like RefSeq IDs.
Therefore I think it makes more sense to rename the "hugo file" to a generic "gene alias" file.
generate_ensembl_json.py is running but it is very slow.
The old Ensembl Perl api had a 'canonical transcript' value for each gene that we can't get using the pyensembl package (the reason is the Perl api queries Ensembl directly whereas pyensembl just uses downloaded gtf files, less info).
There are different lists of canonical transcripts floating around (USCS, MANE, APPRIS) but getting those programmatically and mapping them back to Ensembl IDs is going to be a bit of a headache.
What we can do is choose a canonical transcript using the same rules Ensembl uses for choosing a canonical transcript (see http://uswest.ensembl.org/Help/Glossary?id=346):
The canonical transcript is used in the gene tree analysis in Ensembl and does not necessarily reflect the most biologically relevant transcript of a gene. For human, the canonical transcript for a gene is set according to the following hierarchy: 1. Longest CCDS translation with no stop codons. 2. If no (1), choose the longest Ensembl/Havana merged translation with no stop codons. 3. If no (2), choose the longest translation with no stop codons. 4. If no translation, choose the longest non-protein-coding transcript.
generate_ensembl_json.py is running but it is very slow.
Yes unfortunately it is very slow the first time as it has to query Ensembl a bunch of times to download the protein domains for each protein.
Thanks for your reply.
For Human and Mouse genome how long it should take to complete?
Regards
On Thu, 9 Jul 2020 at 21:49, Matt Douglas notifications@github.com wrote:
generate_ensembl_json.py is running but it is very slow.
Yes unfortunately it is very slow the first time as it has to query Ensembl a bunch of times to download the protein domains for each protein.
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Nitin Mandloi Bioinformatics Associate Scientist
For Human and Mouse genome how long it should take to complete?
I recall it taking ~1 day. It's heavily dependent on how fast Ensembl's server responds.
That said, I just increased the request rate in the script so hopefully that speeds things up somewhat.
Re-wrote 'generate_ensembl_json.pl' in python to avoid having to deal with Perl dependency issues.