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I would like to phase whole-genome datasets, some of which are single-end read datasets and some of which are paired-end datasets. Does anyone have experience with this? Should I simply generate a list of SNPs and feed it to existing phasing algorithms? Is there software that can take the raw read data into account (IE SNPs that appear on the same read)?
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Cancer research has been transformed through numerous molecular techniques, with RNA sequencing (RNA-seq) playing a crucial role in understanding the complexity of the disease. Maša Ivin, Ph.D., Scientific Writer at Lexogen, and Yvonne Goepel Ph.D., Product Manager at Lexogen, remarked that “The high-throughput nature of RNA-seq allows for rapid profiling and deep exploration of the transcriptome.” They emphasized its indispensable role in cancer research, aiding in biomarker...09-07-2023, 11:15 PM -
Ribonucleic acid (RNA) represents a range of diverse molecules that play a crucial role in many cellular processes. From serving as a protein template to regulating genes, the complex processes involving RNA make it a focal point of study for many scientists. This article will spotlight various methods scientists have developed to investigate different RNA subtypes and the broader transcriptome.
Whole Transcriptome RNA-seq
Whole transcriptome sequencing...08-31-2023, 11:07 AM
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