Analyses of Omicron genomes from India reveal BA.2 as a more transmissible variant
Bibliographic record
Abstract
Abstract This is the first study on omicron genomes from India to focus on phylodynamics and phylogenomics trait to provide an insight into the evolution of omicron variants. We analyzed 564 genomes deposited to GISAID database from various states of India. Pangolin COVID-19 Lineage Assigner tool was used to determine lineage assignment of all retrieved genomes. A Maximum likelihood (MLE) tree construction further confirms the separation of genomes into two distinct clades, BA. 1. and BA. 2. A very high reproduction number (R0) of 2.445 was estimated for the lineage BA.2. The highest R0 value in Telangana confirms the prevalence of lineage BA.2 in the state. Construction of the Reduced Median (RM) network shows evolution of some autochthonous haplogroups and haplotypes, which further supports the rapid evolution of omicron as compared to its previous variants. Phylogenomic analyses using maximum likelihood (ML) and RM show the potential for the emergence of sub-sublineages and novel haplogroups respectively. Due to the recombinant property and high transmissibility of omicron virus, we suggest continuous and more widespread genome sequencing in all states of India to track evolution of SARS-CoV-2 in real time.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".