Ok, thanks for your response Luvina.
Padraig
On 06/01/2012 00:30, Luvina Guruvadoo wrote:
Hi Padraig,
Unfortunately your question is beyond the scope of this mailing list
as we do not provide advice regarding scientific direction, but focus
on browser usage issues.
Regards,
---
Luvina Guruvadoo
UCSC Genome Bioinformatics Group
On 1/5/2012 5:07 AM, padraig doolan wrote:
Dear Brooke,
Thanks for your very informative response, it was very helpful.
Apologies also for the delay in responding; the University here had a
lot of campus-wide email outages in weeks approaching christmas and
we were without email access for several weeks prior to the holidays.
I was also wondering if you could help me with an associated issue;
we are interested in using the newly available chinese hamster ovary
(CHO) genome information to generate a commercially-available
microarray chip and I was wondering; what are the steps that would be
required in constructing a CHO chip from that data? For instance,
* How well assembled would the sequence need to be?
* Level of annotation?
Best regards,
Padraig
On 14/12/2011 18:55, Brooke Rhead wrote:
Hi Padraig,
I queried our engineers and got this list of recommendations for you:
1) Aligning all genbank mRNAs from Chinese Hamster
2) Aligning all of their own transcriptome data
3) Aligning all of genbank ESTs from Chinese Hamster
4) Mapping human proteins as derived from either the UCSC gene set
or RefSeq
5) Mapping mouse proteins from UCSC or RefSeq
6) Doing a multiple species genome alignment with mouse, rat,
rabbit, dog, elephant, opossum, platypus, chicken. Do pairwise
alignments as well.
7) Mine the genomic reads and transcriptomic reads for SNPs. Be
careful not to call recently duplicated and only slightly diverged
regions slight divergences as SNPs though.
8) Run several repeat finders.
9) Run a CpG island detector.
10) Run a good gene prediction program like Augustus.
11) Try to find a wet lab group willing to do some DNAse assays....
I hope this is helpful. Good luck with your work!
--
Brooke Rhead
UCSC Genome Bioinformatics Group
On 12/9/11 1:25 AM, padraig doolan wrote:
Dear UCSC Genome Bioinformatics,
My name is Padraig Doolan and I am the Program Leader for Expression
Microarrays and Bioinformatics at the National Institute for Cellular
Biotechnology (NICB), Ireland (www.nicb.ie/). We are a publicly-funded
basic science research institute.
Our small bioinformatics group are just starting the process of
analysisng a new genome (and transcriptome) for the Chinese Hamster
Ovary (CHO) cell line which was recently published (Xu et al., The
genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line. Nat
Biotechnol. 2011 Jul 31;29(8):735-41. doi: 10.1038/nbt.1932.) by
another
group. We do a lot of functional work on this organism and we're
looking
for some good guidelines (published papers, online resources, etc.)
which might help us map out some achievable goals with regard to the
in-silico characterisation of this genome.
For example, after the sequence is published, what are the next
step(s)
in providing relevant information? Lists of SNPs? Predicted
proteome/secretome/numbers of predicted protein types (e.g.
kinases/g-coupled/nuclear-/membrane-localised), etc.?
I'm looking through the Human Genome Project Publications list
(http://www.ornl.gov/sci/techresources/Human_Genome/publicat/publications.shtml)
for inspiration, but this type of analysis output is relatively new
for
our group (we are usually more focussed on translational medicine). Is
there any recommended guidelines your institute can suggest for
following in the footsteps of the HGP in in silico analysis of novel
genomes/transcriptomes? Can your organisation suggest a couple of key
papers or maybe a good analysis strategy?
Best regards,
Padraig Doolan
_______________________________________________
Genome maillist - [email protected]
https://lists.soe.ucsc.edu/mailman/listinfo/genome
_______________________________________________
Genome maillist [email protected]
https://lists.soe.ucsc.edu/mailman/listinfo/genome
_______________________________________________
Genome maillist - [email protected]
https://lists.soe.ucsc.edu/mailman/listinfo/genome
