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Computers are used in several steps of sequencing, from the raw data to finished sequence (or not): Image processing Modern sequencers usually use fluorescent labelling of DNA fragments in solution. The fluorescence encodes the different base types. To achieve high throughput, millions or billions of sequencing reactions are performed in parallel in ...


39

Think about it like this. Suppose you own a hundred copies of "The Lord of the Rings", a 500000 word novel. Unfortunately, you have those hundred copies in the form of several million tiny scraps of paper, each of which contains about ten sequential words from the novel. Your task is to take those several million scraps of paper and put them in order so that ...


8

The Next-Gen sequencers cannot sequence a very long stretch of DNA with good reliability (~150 for the recent model- HiSeq2000; even less for older models such as GA (40), GA-II (70), GA-IIx (90)). For increasing the confidence in a certain hit, it was sequenced from both the ends. For example, if you have selected 500bp DNA fragment, then after ligating ...


7

As you mentioned in the question, current sequencing platforms split the genomic DNA into many small pieces which the machine then analyzes. The product of a sequencing experiment is millions or even billions of short "reads"---strings of A, C, G, and T representing the nucleotides of a single fragment of DNA. The DNA reads in this form aren't particularly ...


7

In a genome, there are usually billions of base pairs. However, it's impossible to read all of them in one go. The DNA is fragmented, and the sequence of the fragments is determined. Next-generation sequencing techniques are faster and cheaper, but produce only short fragments (say, 100 base pairs, this depends on the technology). It's extremely ...


6

There are multiple ways of doing genome assembly. The term you are probably looking for is "De Bruijn-Graph based assembly". Using this you can find a lot more different explanations of how it is done. Another frequently used method is "Overlap Layout Consensus assembly", which in fact is not based on k-mer counting.


5

Let's try and answer all three parts of your question. Sequencing The general method is the same. Sequencing is just sequencing. But as for every single sequencing, there are factors to consider and protocols to be selected. One important thing is, that you might want comparably long reads to cope with the repeats and the general large size of plant ...


4

You can try looking around biostars.org, which is like stackexchange, but for bioinformatics. Velvet is one example of a de novo assembler. But 30 bp is really short, and animals have big genomes (not as tough as lots of plants and fungi, but still tough) What you would get is a bazillion short contigs. It would not be pretty.


4

Sequence alignment It is done for checking sequence similarity between two or more different sequences. This will give information about how two sequences are different, what is their evolutionary relationship, which residues are conserved etc. Take a look at following sequence alignment between different sequences. (Image courtesy: Wikimedia Commons) You ...


4

In Illumina sequencing, the DNA is (usually randomly) sheared into fragments. For paired end sequencing, fragments of a specific size range are selected and then sequenced from both sides. This results in two reads for each fragment. As read length is fixed, also the remaining "middle part" of the fragment is in a specific size range. In some cases there is ...


3

If you only want to use only sequencing techniques, you have a problem. To get a feeling of what kind of results to expect, consider this paper published recently in Nature Genetics. They tried to assemble a whale genome de novo. They had 7 (!) paired-end libraries with different insert lengths ranging from 170bp to 20kb. Read lengths were mostly 100bp and ...


2

I really like the genious software suite. It can multithread and really use the performance of your computer. Even complicated things like De Novo assembly are very very intuitive.


2

It means k-mer coverage. From the velvet manual: 4.2.1 The contigs.fa file This fasta file contains the sequences of the contigs longer than 2 k , where k is the word-length used in velveth. If you have specified a min_contig_length threshold, then the contigs shorter than that value are omitted. Note that the length and coverage ...


2

If you are interested on the topic of how to compare assemblers, have a look at assemblathon. That group has two papers and working on a third about comparing genome assembly algorithms.


2

If the DNA sequence contains repetative elements, and your reads are not long enough to resolve them, you won't know if you have the right path. Usually you split your results into contiguous regions whose sequence you are confident in.


1

I'm going to re-interpret this question slightly to make it easier to answer: "Why do genome assemblies frequently consist of large numbers of short contigs rather than a relatively small number of long chromosomes (or full replicons of other types)? And how could I make my assembly better?" De novo sequence assemblies (usually) consist of a set of ...


1

I have never heard the term “contig based alignment”, and your question is the only Google hit of this exact query (apart from a 2012 patent application). That said, and without knowing the exact context, I am assuming that you are essentially right: contig-based alignment probably refers to the de novo assembly of reads into contigs, which are then aligned ...


1

As clearly stated in the WP article: The molecule is made up of 20 complement control protein (CCP) modules (also referred to as Short Consensus Repeats or sushi domains) connected to one another by short linkers (of between three and eight amino acid residues) and arranged in an extended head to tail fashion. So in your terminology yes, it is a repeat ...


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