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Cоntestа lаs preguntаs. (6 pts) En tu оpinión, ¿cuál es la injusticia más chоcante de este país? ¿Qué recomiendas que hagan los líderes políticos para resolverla?
In оur wоrk tо аlgorithmicаlly аssemble genomes, we made (at least) two assumptions about our data that are entirely inconsistent with reality. First, we assumed there were no errors in our sequencing reads. However, Illumina sequencers, the most used next-generation sequencing technology, have an average error rate of ~1%. To further complicate things, the error rate changes across the sequence read. Typically, sequence reads are 100-250 base pairs in length. Close to the beginning of the reads, there are fewer errors than near the end. Second, we assumed that the insert size (the textbook called this d) between the reads is identical for every pair. In even the most stringent protocols, the insert size is never equal for all reads. Considering our algorithm for assembling read pairs above, answer the following two questions. 1) If we remove these assumptions, what complications will occur with the algorithm as we learned it? 2) If we remove these assumptions, would we need to modify our algorithm above? If yes, how? (For the record, De Bruijn graphs are the most popular approach for genome assembly, and we do not have the luxury of making the assumptions above but still manage to assemble new genomes accurately.)