how do i expand this into 1000 words for a result section of a report The objective is to interpret the results of an RNA-Seq analysis to identify differentially expressed genes in breast cancer using figure 1. The data provided includes gene symbols, chromosome location, start and end points, strand, fold change, log2 fold change, p-value, and false discovery rate (FDR). The RNA-Seq analysis has identified several genes that are differentially expressed in breast cancer. These genes are
how do i expand this into 1000 words for a result section of a report
The objective is to interpret the results of an RNA-Seq analysis to identify differentially expressed genes in breast cancer using figure 1. The data provided includes gene symbols, chromosome location, start and end points, strand, fold change, log2 fold change, p-value, and false discovery rate (FDR). The RNA-Seq analysis has identified several genes that are differentially expressed in breast cancer. These genes are located on various chromosomes and have varying levels of fold change, indicating the degree to which their expression levels differ between normal and cancerous cells. The gene with the highest fold change is EYA4, located on chromosome 6, with a fold change of 3604.4176. This indicates that the expression of this gene is over 3600 times higher in cancer cells compared to normal cells. The log2 fold change is 11.81555, which is a measure of the magnitude of the difference in gene expression. The p-value for this gene is extremely low (2.85E-284), indicating that the difference in expression is highly statistically significant. The FDR is also extremely low (1.55E-282), suggesting that the likelihood of this result being a false positive is very low. The gene with the second highest fold change is GALNT13, located on chromosome 2, with a fold change of 1099.1348. The log2 fold change is 10.102153, and the p-value is 4.99E-95, both of which indicate a significant difference in gene expression. The FDR is 5.49E-94, suggesting a low likelihood of a false positive result. Other genes with high fold changes include GABRA3, NCAM1, ISL1, IP6K3, PINCR, ZFPM2-AS1, HPCAL4, CUX2, LPL, NTSR1, HOXB13, FABP4, CPVL, LOC1004205, SAMSN1, LOC642366, CSF2, SPOCK3, DPYSL5, CCDC178, and MT1A. All these genes have fold changes ranging from 215.16056 to 847.28604, indicating significant differences in gene expression between normal and cancer cells.
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