Cluster refinement

WARNING: Under construction!!!

Sorry for the dust! We’re working hard to make this website available.

Links might fail, content might be incomplete and layout might be very ugly.


After the validation, we proceeded with the retrieval of a subset of high-quality clusters. At first, we removed the clusters containing ≥10% bad-aligned ORFs and a Jaccard similarity index < 1 and the clusters with ≥ 30% shadow ORFs. From the remaining set of clusters, we removed the single shadow, spurious and/or bad-aligned ORFs. Steps:

I) Filter out “bad” clusters (≥ 10% bad-aligned ORFs & Jaccard similarity index <1) II) Filter out “shadow” clusters (≥ 30% shadow ORFs) III) Remove the single rejected/bad ORFs (shadow, spurious and bad-aligned)

  • Scripts and description: The main script is: It takes the output from the cluster validation and the shadows and spurious ORFs, and returns a refined set of clusters (tables plus ffindex databases). More info in the


From the set of 3,003,897 clusters, we removed 57,052 clusters classified as “bad” after the validation. From the remaining 2,946,845 clusters we removed 6,252 clusters with more than 30% shadow ORFs. At the end from each of the left 2,940,593 clusters, we removed a total of 2.7 million single shadow, spurious and bad-aligned ORFs, and we obtained a set of 2,940,592 refined clusters with a total of 260,142,446 ORFs. In this last step we lost 336 clusters: 244 resulted composed of only spurious and bad aligned ORFs, one in the annotated set of clusters and 243 in the not annotated set, and 92 clusters were discarded/moved to the singletons set because left with only one sequence. Moreover, 1,190 annotated clusters became non annotated after the refinement/removal of the single ”unwanted”/”rejected” ORFs, which represented the only annotated ORFs in those clusters. Steps in numbers are shown in the tables below:

Steps of the cluster refinement both in terms of number of clusters and number of ORFs (kept and removed).



Summarising: we removed 63,640 clusters and a total of 8,325,409 ORFs; they constitute the 2% and the 3% of the initial cluster and ORF sets respectively. The majority of the clusters (98%) resulted, therefore, having good quality concerning homogeneity and real/actual ORFs content. The 2.9 million refined clusters are made of ~993K annotated clusters, containing ~174M ORFs, and 1.9M unannotated clusters with about 86M ORFs.

Let's Get In Touch!

Ready to start your next project with us? That's great! Give us a call or send us an email and we will get back to you as soon as possible!