This is a table with all of the data used for our manuscript: "From high to low: the potential of genetics in identifying women at lower risk of breast cancer". There is one row per participant. 25,591 participants total. The P_VUS column indicates whether the individual has a P (pathogenic) variant or a VUS (variant of uncertain significance) in one of 5 genes: BRCA1, BRCA2, PALB2, ATM and CHEK2. The PRS_percentile column provides the polygenic risk score percentile for this individual. It is between 0 and 99 included. The carrier_status column indicates whether the individual is in the low-risk group or the 'at_risk' group which corresponds to women at average or high risk. The censor_surv_BrCa column indicates whether the individual was diagnosed with breast cancer (1) or not (0).The age_surv_BrCa indicates the age of first diagnosis for those diagnosed with breast cancer or the current age for those not diagnosed with breast cancer.

This is a table with all of the data used for our manuscript: "From high to low: the potential of genetics in identifying women at lower risk of breast cancer". There is one row per participant. 25,591 participants total. The P_VUS column indicates whether the individual has a P (pathogenic) variant or a VUS (variant of uncertain significance) in one of 5 genes: BRCA1, BRCA2, PALB2, ATM and CHEK2. The PRS_percentile column provides the polygenic risk score percentile for this individual. It is between 0 and 99 included. The carrier_status column indicates whether the individual is in the low-risk group or the 'at_risk' group which corresponds to women at average or high risk. The censor_surv_BrCa column indicates whether the individual was diagnosed with breast cancer (1) or not (0).The age_surv_BrCa indicates the age of first diagnosis for those diagnosed with breast cancer or the current age for those not diagnosed with breast cancer.

We hypothesized that some individuals may be co-infected by Delta and Omicron, or that some individuals may be infected by a virus resulting from the recombination of Delta and Omicron during a period when the two SARS-CoV-2 variants were co-circulating. To identify co-infection and recombinant samples, we looked at the sequencing results of SARS-CoV-2 genomes. We specifically looked and visualized the alternate allele fraction for mutations specific to Delta and mutations specific to Omicron. For co-infection samples, we expect that all of the mutations specific to Delta and all of the mutations specific to Omicron be present with complementary alternate allele fractions. While the sequencing of viruses resulting from a recombination will show all of the mutations specific to one variant on the 5'-end and all of the mutations specific to the other variant on the 3'-end. Importantly the alternate allele fraction at each site should be either 0 or 1 for sequences of a virus resulting from a clonal recombination. In this repository, we have the python code used to visualize the alternate allele fractions. This code was used to create the figures of our manuscript.In this repository, we also have the supplemental tables of the paper, which have all of the raw data that were used to create the figures of the paper.

We hypothesized that some individuals may be co-infected by Delta and Omicron, or that some individuals may be infected by a virus resulting from the recombination of Delta and Omicron during a period when the two SARS-CoV-2 variants were co-circulating. To identify co-infection and recombinant samples, we looked at the sequencing results of SARS-CoV-2 genomes. We specifically looked and visualized the alternate allele fraction for mutations specific to Delta and mutations specific to Omicron. For co-infection samples, we expect that all of the mutations specific to Delta and all of the mutations specific to Omicron be present with complementary alternate allele fractions. While the sequencing of viruses resulting from a recombination will show all of the mutations specific to one variant on the 5'-end and all of the mutations specific to the other variant on the 3'-end. Importantly the alternate allele fraction at each site should be either 0 or 1 for sequences of a virus resulting from a clonal recombination. In this repository, we have the python code used to visualize the alternate allele fractions. This code was used to create the figures of our manuscript.In this repository, we also have the supplemental tables of the paper, which have all of the raw data that were used to create the figures of the paper.

We hypothesized that some individuals may be co-infected by Delta and Omicron, or that some individuals may be infected by a virus resulting from the recombination of Delta and Omicron during a period when the two SARS-CoV-2 variants were co-circulating. To identify co-infection and recombinant samples, we looked at the sequencing results of SARS-CoV-2 genomes. We specifically looked and visualized the alternate allele fraction for mutations specific to Delta and mutations specific to Omicron. For co-infection samples, we expect that all of the mutations specific to Delta and all of the mutations specific to Omicron be present with complementary alternate allele fractions. While the sequencing of viruses resulting from a recombination will show all of the mutations specific to one variant on the 5'-end and all of the mutations specific to the other variant on the 3'-end. Importantly the alternate allele fraction at each site should be either 0 or 1 for sequences of a virus resulting from a clonal recombination. In this repository, we have the python code used to visualize the alternate allele fractions. This code was used to create the figures of our manuscript.

We report on the sequencing of 74,348 SARS-CoV-2 positive samples collected across the United States and show that the Delta variant, first detected in the United States in March 2021, comprised the majority of SARS-CoV-2 infections by July 1, 2021, and accounted for >99.9% of infections by September 2021. Not only did Delta displace variant Alpha, which was the dominant variant at the time, it also displaced the Gamma, Iota and Mu variants. Through an analysis of quantification cycle (Cq) values, we demonstrate that Delta infections tend to have a 1.7x higher viral load compared to Alpha infections (a decrease of 0.8 Cq) on average. Our results are consistent with the hypothesis that the increased transmissibility of the Delta variant could be due to the Delta variant’s ability to establish a higher viral load earlier in the infection compared to the Alpha variant.The dataset attached includes the raw numbers to regenerate all of the figures from this paper. Specifically, the different tabs correspond to: Data_Figure_1A, related to Figure 1AData_Figure_1B, related to Figure 1BData_Figure_1C, related to Figure 1CData_Figure_2A, related to Figure 2AData_Figure_2CD_S1CD, related to Figures 2C, 2D, S1C, S1D

We report on the sequencing of 74,348 SARS-CoV-2 positive samples collected across the United States and show that the Delta variant, first detected in the United States in March 2021, comprised the majority of SARS-CoV-2 infections by July 1, 2021, and accounted for >99.9% of infections by September 2021. Not only did Delta displace variant Alpha, which was the dominant variant at the time, it also displaced the Gamma, Iota and Mu variants. Through an analysis of quantification cycle (Cq) values, we demonstrate that Delta infections tend to have a 1.7x higher viral load compared to Alpha infections (a decrease of 0.8 Cq) on average. Our results are consistent with the hypothesis that the increased transmissibility of the Delta variant could be due to the Delta variant’s ability to establish a higher viral load earlier in the infection compared to the Alpha variant.The dataset attached includes the raw numbers to regenerate all of the figures from this paper. Specifically, the different tabs correspond to: Data_Figure_1A, related to Figure 1AData_Figure_1B, related to Figure 1BData_Figure_1C, related to Figure 1CData_Figure_2A, related to Figure 2AData_Figure_2CD_S1CD, related to Figures 2C, 2D, S1C, S1D