Artemis, Apollo Or Anything For Genome Annotation Editing With Next Gen Sequence Data
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14.1 years ago
Darked89 4.6k


I am looking at a bunch of standalone genome browsers / annotation editors. I am having trouble finding something which can:

  • load 800Mbp draft sequence
  • read gff files from few gene predictors /blast matches
  • load RNA-Seq next gen mapping data
  • will let me compare genome slices with these from other species
  • editing annotations (splitting/merging genes)
  • tagging, i.e. "confirmed_gene", "pseudogene"

So far only Artemis and Apollo have more extensive editing annotation capability. Argo and IGB/GenViz should have some basic editing (i.e delete feature) but do not seem to be concentrating on that function.

Hence my question: is there anything out there which you can recommend, or at least you have tried?

EDIT: There are two other tools used for manual annotation:

Next release of Argo (Argo2) is one probably to watch.

Also: loading and indexing that much data in a text form does not make sense to do at the startup time (loading time 20mins + of FASTA alone). Precomputing/converting the data and loading it into a database looks like a must have feature.

genome next-gen-sequencing annotation • 6.1k views
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I've mainly been using Artemis, which I like a lot. But I don't have as many needs as you do ;)

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13.6 years ago
Yannick Wurm ★ 2.5k

We've been using Apollo... it has many features & offers a great overview of what types of evidence you have for your genes. And it can open many different file formats & remote databaes. But there still is clearly still a lot of potential.

For example it seems like it should be trivial for a non-computational person to provide an additional source of evidence (eg: the cDNA they just sequenced in the lab to help choose between two potential gene models). But afaik thats impossible.

Maybe Apple or Google should make a genome annotation tool :)

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14.1 years ago

We've been using artemis to annotate our bacterial genome. Nothing in the 100Mb+ range, more 1-10Mb.

It worked very well for this. I would guess it would work for your dataset(s) if you have a massive(memory-wise) desktop to run it.

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Artemis, venerable but still useful, we use it too.


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