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The answer is in the supplementary methods page 3. Finally, all fragments in the same library with duplicate start and end coordinates were removed using Picard


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To clear up what may be a possible misunderstanding about RAxML: RAxML (and most/all other maximum likelihood phylogenetic inference programs using reversible models of sequence evolution) explicitly infer unrooted trees. This is because, for a reversible model of sequence evolution, changing the position of the root does not affect the likelihood of the ...


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I think you have a bug raxmlHPC -m PROTGAMMAILG -n output.tre -o outgroup -p 10000 -s /Users)/username/Desktop/alignment_file.phy Try the above, where username is your username. I'll check my codes later. The most important bit is the space between the -p and word outgroup. You can omit the -p 10000 it is only needed for very geeky maximum likelihood and ...


2

You might want to have a look at What is the difference between orthologs, paralogs and homologs?. Paralogs are duplicates by definition, and whether a gene is a pseudogene or still active has no bearing on whether it comes from a duplication. In any case, to figure out what's going in in your target genome, you should use the target's genes. So, first get ...


2

GeneBlocks is a Python library for comparing DNA sequences. It can be used to find common blocks (identical regions) in a group of DNA sequences. Using a modified version of your example (I duplicated a small region): import geneblocks sequence = geneblocks.load_record('sequence.gb', name='seq') sequence2 = geneblocks.load_record('sequence.gb', name='seq2') ...


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If you know approximately where are the duplicated regions, you can cut them out from the genome and align the two block using tools like MUMmer or Mauve. Although Mauve is not scalable solution (You can not scan genomes for duplicates with it) it's very handy for aligning small(ish) blocks. It can also align multiple sequences if you would like to check ...


1

This is really tough to do with highly heterozygous animals. What are your genome assembly stats? Specifically, what is your number of contigs, scaffolds, assembly size, and the N50? If you have proximity ligation data it will be easier to determine if potential paralogs are truly from different regions of the genome or are just from homologous locations on ...


1

To finish you need bootstrap support using a model-based tree building algorhithm, I use RAxML, specifically raxmlHPC (easily downloadable and compiles on Linux and OSX). The codes are quite complicated and I've given them below. A robust maximum likelihood tree is, raxmlHPC -m PROTGAMMAILG -n output.tre -o outgroup-p 10000 -s alignment_file.phy To make ...


1

The first thing is the Sequence 5-2 and 5-3 are on very long branches. This is often indicative of sequence problems. You mentioned 5-2 and 5-3 are possibly two fragments of the same gene. My advice is to do a psuedo-annotation and reassess the phylogeny to see whether that super long branch length falls back in line The branches close to 5-1 are of interest ...


1

So this is what I did to produce the phylogenetic tree: I performed a BLASTp using the query sequence (lets call it sequence 5 from species A, which is thoroughly annotated) against full NCBI protein database (ref-seq database) I downloaded all the hits in fasta format (very cool feature indeed!) Here I was a bit confused, so what I did was to take the ...


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The strategy from here is to determine duplication/parology through phylogeny, notably amino acid phylogeny using statistical support. The basic result is whether the genes under investigation are: A. monophyletic to the given species under investigation B. Paraphyletic against protist species which are not under investigation, Point A is compatible with ...


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Many thanks for your response! What I don't understand is why you haven't performed a blast back over the original highly annotated genome? You must have done this? Yes, I have performed a blast back over the original highly annotated genome and, as expected, the first hit is the sequence that I used as query in the first blast analysis. There are a ...


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The tBlastn looks good and looks like some sort of parology, although the hits you are getting need to be checked to make sure they are not psuedo-genes. The shot-gun genome however appears poorly annotated because it had misannotated 5-1 and 5-2. What I don't understand is why you haven't performed a blast back over the original highly annotated genome? You ...


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