Which statements regarding sequence similarities are correct?
1) If two sequences are 60% identical, they are also 60% homologous
2) Two paralogous sequences are also two homologous sequences
3) 1 to 1 orthologous genes are often assumed to have the same function
4) If a duplication of Gene G occured on the lineage to species A after the split of species A and B, species A has two paralogs of gene G and these two be orthologues of G in species B
5) if two sequences in two species are reciprocal best hits they are usually defined as paralogs
1) If two sequences are 60% identical, they are also 60% homologous -> wrong; sequence similarity is quantitative and being homologous is qualitativ (yes or no)
2) Two paralogous sequences are also two homologous sequences -> correct
3) 1 to 1 orthologous genes are often assumed to have the same function -> correct
4) If a duplication of Gene G occured on the lineage to species A after the split of species A and B, species A has two paralogs of gene G and these two be orthologues of G in species B -> correct
5) if two sequences in two species are reciprocal best hits they are usually defined as paralogs -> wrong, this is the defintion/ identification of orthologs
A global alignment is...
1) An alignment of two genomes
2) A sequence alignment with more than two species
3) A sequence alignment along the entire length of the compared sequences
4) A sequence alignment of a subset of two sequences
5) A heursitic search algorithm
1) An alignment of two genomes -> wrong, of two sequences
2) A sequence alignment with more than two species -> wrong
3) A sequence alignment along the entire length of the compared sequences -> correct
4) A sequence alignment of a subset of two sequences -> wrong
5) A heursitic search algorithm -> wrong
Which statement are correct for scoring matrices for alignments?
1) A scoring matrix is a mathematically proven algorithm
2) If all mismatches in a scoring matrix are scored equally, one assumes that all nucleotides or amino acids have the same frequency in the alignment
3) A global alignment is independent of the scoring matrix
4) The Smith-Waterman alignment finds the optimal alignment independent of the scoring matrix
5) One can run Blast with and without a scoring Matrix
1) A scoring matrix is a mathematically proven algorithm -> wrong, not an algorithm, just a matrix (would be correct for Smith-Waterman / Needleman-Wunsch algorithm)
3) A global alignment is independent of the scoring matrix -> wrong, you cannot do an alignment without a scoring matrix
4) The Smith-Waterman alignment finds the optimal alignment independent of the scoring matrix -> wrong, dependent of the scoring matrix
5) One can run Blast with and without a scoring Matrix -> wrong does an alignment which needs a scoring matrix
Which statements regarding the BLAST algorithm are true?
1) BLAST uses the needleman-Wunsch algorithm
2) BLAST can only be used to align protein sequences
3) BLAST is a global alignment algorithm
4) BLAST is a heuristic, i.e. it does not guarantee to find the best alignment
5) BLAST does not use scoring matrices and hence is faster than optimal alignment algorithms
1) BLAST uses the needleman-Wunsch algorithm -> wrong; with Needleman-Wunsch it would take too long/expensive; it also doesnt use Smith-Waterman
2) BLAST can only be used to align protein sequences -> wrong, also DNA sequences
3) BLAST is a global alignment algorithm -> wrong, its a local alignment algorithm
4) BLAST is a heuristic, i.e. it does not guarantee to find the best alignment -> correct
5) BLAST does not use scoring matrices and hence is faster than optimal alignment algorithms -> wrong, uses scoring matrices
If you set k=3 for the query sequence "AWKLTSVCAGQL", how many words has the k-letter word list of blast?
1) Depends on the scoring matrix
2) 3
3) 4
4) 9
5) 10
5) 10 -> correct
Which statement regarding mapping of short reads is true?
1) BLAT was invented to map the billions of reads generated by NGS seqencers
2) Mapping of short reads requires alignments optimized for sensitivity
3) BWA and Bowtie are two commonly used mappers of NGS data
4) BLASTN is commonly used to map NGS reads
5) Burrow-Wheeler transformation is an algorithm that speeds up mapping by allowing the reference genome to be more compressed
1) BLAT was invented to map the billions of reads generated by NGS seqencers -> wrong, for HGP; its too slow for NGS data
2) Mapping of short reads requires alignments optimized for sensitivity -> wrong; not more sensitive and more speed at a time; actually the opposite is true. So for short reads someone needs more speed
3) BWA and Bowtie are two commonly used mappers of NGS data -> correct
4) BLASTN is commonly used to map NGS reads -> wrong; not at all used for mapping NGS reads (not the right tool)
5) Burrow-Wheeler transformation is an algorithm that speeds up mapping by allowing the reference genome to be more compressed -> correct
Last changed8 days ago