User: colindaven
colindaven • 1.1k
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Posts by colindaven
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Comment:
C: MMR for variant calling ?
... I tried AlignerBoost once https://github.com/Grice-Lab/AlignerBoost
but never really got it established or saw major advantages. However, I do see opportunities for improving short read mapping quality estimates, since incorrect alignments cause many problems in my work. ...
written 10 days ago by
colindaven • 1.1k
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C: Aligment rate vs called peaks
... In short - no. More detail needed. genome, read length, goal, antibody, etc etc etc etc.
Have a look at Deeptools in Freiburg and especially their excellent **plotFingerprint** plots to assess your ChIP signal. ...
written 14 days ago by
colindaven • 1.1k
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... Canu is also very good for long read assemblies ...
written 20 days ago by
colindaven • 1.1k
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... Another very helpful alternative to MAKER is Gmap for mapping transcript assemblies (think Cufflinks (old), Trinity, Stringtie etc results) to the genome.
Use the excellent GFF3 output and compare and contrast with MAKER results. ...
written 20 days ago by
colindaven • 1.1k
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... We did some analysis on Hadoop. Turns out the RNA-seq analysis ran quicker on 4 servers (think Cassandra?) rather than one, something like 23 versus 16 minutes, but the cost of chunking and copying the data onto the workers (that is, the map reduce step), then reconstituting the results, was about 7 ...
written 20 days ago by
colindaven • 1.1k
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... This is not in BED12 format but I find it very helpful for human regulatory regions which you appear to be looking for (I think):
See file in (use firefox or an ftp client, not chrome)
ftp://ftp.ensembl.org/pub/release-95/regulation/homo_sapiens/
...
written 20 days ago by
colindaven • 1.1k
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... Not sure such a thing exists. Do you mean all round summary statistics ? ...
written 21 days ago by
colindaven • 1.1k
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104
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... I would use a local installation of gitlab for this, it's very easy and very flexible. Also allows sharing, commenting, public/private restrictions and is very interactive. ...
written 4 weeks ago by
colindaven • 1.1k
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... Yes, 2.5X is too low for de novo.
For structural variant detection vs a reference genome about 10X is recommended.
For de novo I would suggest 30-40X, whereby the longest reads are the most important.
Sorry, but 2.5 X is likely only maybe useful for somehow scaffolding Illumina contigs if you ...
written 4 weeks ago by
colindaven • 1.1k
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... If you mean one variant and you're not planning to check your VCF any further, you might want to convert your VCF to a TSV to be able to
count more easily.
This tool is available in Galaxy:
**NGS: VCF Manipulation
VCFtoTab-delimited: Convert VCF data into TAB-delimited format**
Otherwise, I like ...
written 4 weeks ago by
colindaven • 1.1k
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