@@ -25,7 +25,7 @@ to clusterize them. We tried to summarize the pro and cons of classification fea
||pros|cons|
|:--:|--|--|
|`--clu-type gene`|detect problem of missens predictions|overlaps of UTR merge different genes, not suitable for compact genomes|
|`--clu-type cds`|detect problem of missens predictions|could not correct splitted CDS|
|`--clu-type cds`|detect problem of missens predictions|could not correct split CDS|
|`--clu-type gene``--clu-stranded`|resolve conflict between genes and possible non-coding RNA on the opposite strand|will not detect severe problem due to divergent prediction on opposite strand, overlaps of UTR merge different genes|
|`--clu-type cds``--clu-stranded`|resolve conflict between genes and possible non-coding RNA on the opposite strand|will not detect severe problem due to divergent prediction on opposite strand|
...
...
@@ -77,9 +77,7 @@ As described above, the SO classification was originally based on exon boundarie
that could be highly problematic for de-novo annotations with poorly
defined UTR parts. To avoid such problem, you can choose to perform
the same classification based on CDS coordinates. In this case you
will obtained less biased results. We tried
to summarize the pro and cons of classification feature type in
the following table.
will obtained less biased results (See table above for pros/cons of clustering).
