Hi Susanne, The liftOver output has both the query and the target in the output lines, but it is based on the region captured by the filter coordinates. And identifiers are lost during this processing. This is the expected result.
The choice of using liftOver for cross-species identification of Orthologs is probably not appropriate. LiftOver identifies the best match on one direction from-> to. It is a "best homology" tool. An Ortholog is in general recognized as a "best reciprocal match" but pseudogenes and other complications (in particular the quality/completeness of the genomes) get in the way of finding a clean result. Gene duplications, Cognate groupings that involve more that one gene in any of the targeted genomes, etc. can make a simple, automated analysis using just these types of rules can be misleading. In many cases, even for closely related species, the best hit in one direction is not the Ortholog, it is down farther in the hit list. These are the recommended tracks to use: Use the UCSC Genes track. If your gene is here, many have Orthologs identified, some with supporting evidence that goes beyond a simple homology comparision. Read the track description to see if this is something that would work for you. Use the TransMap track. An explanation is here: https://lists.soe.ucsc.edu/pipermail/genome/2008-July/016784.html For more distantly related species - the process becomes more complicated, but some suggestions are: Use the conservation track's MAF alignments. These are filtered to be reciprocal-best between the main reference genome (human) and each target. Again, the track description provides details for methods. Use Nets as a starting place (liftOver is based on Chains, and Chains are used to build Nets). This is still in one direction, but it is a summary of sorts - Nets are a better choice as the results are ranked in different way that can be informative. And don't forget to also look at the net in the opposite direction, contained in the target genome's browser. Net methods are also in the track description to explain the ranking rules. For future queries: For a full merge (between any two tracks - including custom tracks), try using the tools in Galaxy. The output can be formatted to return both the query and the target in the same line. Galaxy understand the data formats used by UCSC and can perform "interval" comparisons. Data can be directly exported from the Table browser to Galaxy as an output option and returned as a custom track if it fits one of the formats accepted by the Custom Track submission tool. You may need to reformat the data and use the name, name2 fields to store information. Hopefully this helps to explain the data a bit better and you are able to determine the best method for your experiment. Good luck and please let us know if we can help more, Jennifer ------------------------------------------------ Jennifer Jackson UCSC Genome Bioinformatics Group ----- "Susanne Knapp" <[email protected]> wrote: > From: "Susanne Knapp" <[email protected]> > To: "[email protected]" <[email protected]> > Sent: Wednesday, January 27, 2010 8:32:52 AM GMT -08:00 US/Canada Pacific > Subject: [Genome] ortholog positions human chimp > > Dear UCSC, > > I have discovered the LiftOver function on your website which I wanted > to use to convert a list of 12,000 positions in the human genome to > their ortholog positions in the chimpanzee genome in order to see and > plot their location. However, using the LiftOver function, I only was > able to create a list of output positions, where I can't see anymore > to which position on the human chromosome they relate, and as some > positions fail to be mapped (due to gaps in the chimp chromosome?), > it is impossible to keep track as the failed markers are listed in a > separate file. Any better way to do this? > > Looking forward to your solution to my problem, > > Kind regards, > > Susanne Knapp > _______________________________________________ > Genome maillist - [email protected] > https://lists.soe.ucsc.edu/mailman/listinfo/genome _______________________________________________ Genome maillist - [email protected] https://lists.soe.ucsc.edu/mailman/listinfo/genome
