Metagenomics and binning Flashcards
1
Q
Functional metagenomics
A
Look for one gene in an environment.
Fragment DNA, ligate into vectors, transform into host, screen, amplify and sequence
2
Q
Sequence based metagenomics
A
MGWGS. All organisms and viruses can be found, sensitive to strand variation. Fragment, libprep and seq.
3
Q
16s rRNA amplicon seq
A
Only look at rRNA to see what you have. Amplify rRNA and seq.
4
Q
Describe the MG workflow
A
Preprocess
Align or assemble
After assembly, one can predict genes, bin and align to ref
5
Q
What are the problems of MG seq?
A
Extreme depth is needed Low coverage Kmer correction not possible since many different things are present. Optimal kmer varies between species Read errors cannot be corrected Large data sets No N50 Gene prediction is difficult since different organisms have different fingerprints What even is bacterial species?
6
Q
What is binning?
A
Sorting of reads that “belong” together
7
Q
How to bin?
A
Alignment based (does it look like something we know from a reference? Remove low-quality hits)
Composition based (small fingerprints in DNA, fast and easy but not so accurate, needs long DNA to do statistics, no-one knows how it works)
Co-abundance based ("copy number", needs cn variation)
