# Ct Value from RT-qPCR Can Predict SARS-CoV-2 Virus Assembly and Lineage Assignment Success
## 1 Introduction  
SARS-CoV-2 virus appeared at the end of 2019, when it was found to cause a disease, today known as COVID-19 [1]. To date, a number of different lineages have emerged. Some of the variants that have emerged so far have become widely spread or even dominant for a time. The Alpha variant (B.1.1.7) from September 2020 carries a mutation in the S protein (N501Y) that affects the conformation of the receptor-binding domain and 13 other B.1.1.7 lineage-defining mutations [2]. The Beta variant (B.1.351), which appeared in May 2020, was characterized by seven mutations in the spike protein. Later, the Gamma variant (P.1) appeared with 17 unique mutations, followed by the Delta variant (B.1.617.2) with 29 mutations in multiple proteins, and Omicron (B.1.1.529), which carried more than 50 new point mutations (30 associated with residue changes in the spike protein). Occasionally, coinfection can occur, leading to recombination and the appearance of recombinants among other variants that have actually been documented [3]. Scientists around the world have been collecting genomic or transcriptomic data on SARS-CoV-2 and infected patients, which has made it possible to study the infection and how the host responds to it at the molecularlevel. To date, 16,011,577 SARS-CoV-2 genome data have been submitted into the Gisaid system [4].  
Assembling the SARS-CoV-2 genome became standard procedure, since it is necessary for NGS data analysis. When it comes to the routinely used methods utilized in standard clinical sample processing during this pandemic, mostly targeted enrichment strategies were used, based on either amplicon or hybridization-probe approaches. There are different designs or protocols that became routinely used, based on standardized academic research or commercially available solutions, e.g., the ARTIC nCoV2019 protocol, which is available in a standardized set of oligonucleotides from IDT as a result of the ARTIC network initiative focused on SARS-CoV-2 [5] or Respiratory Virus Oligo Panel kit from Illumina. Such targeted solutions are perfect when it comes to the need for high throughput, short turnaround times for sample analysis, as well as good economical effectiveness in cases where focused analysis--on detection of SARS-CoV-2 or panel of clinically relevant respiratory viruses--is the issue. However, from a scientific perspective, this brings only a limited amount of disease-related information as the response of the patient to the viral infection is complex and should be studied in association with the currently known relevant biological context. For studying the biological context at the least local (or global) microbiome and local host transcriptome should be involved. Therefore, if we would like to go over this limitation (of focused viral detection analysis), we should use metatranscriptomic analyses as the method of choice [6].  
In contrast with procedures focused on viral genome assembly, in our study, the virus genome was assembled by using short-read RNA-seq metatranscriptomic data originating from clinical samples represented by nasopharyngeal swabs. As a part of the project with a wider focus, this paper is focused on describing how RT-qPCR Ct value can predict the feasibility of further analysis of viral RNA in studies with such an experimental design.