17
There area few different influenza virus database resources:
The Influenza Research Database (IRD) (a.k.a FluDB - based upon URL)
A NIAID Bioinformatics Resource Center or BRC which highly curates the data brought in and integrates it with numerous other relevant data types
The NCBI Influenza Virus Resource
A sub-project of the NCBI with data curated ...
12
In any scenario where depth of coverage is an important factor, PCR duplicates erroneously inflate the coverage and, if not removed, can give the illusion of high confidence when it is not really there.
For example, consider the following hypothetical scenario.
*
...
11
It’s a matter of preference I guess but I recommend the Ensembl builds. Decide whether you want the toplevel or primary assembly, and whether you want soft-masked, repeat-masked or unmasked files. The naming schema is very straightforward; the combinations are described in the README file, and all files reside in one directory.
For example, if you want the ...
10
Simulators designed specifically for Oxford Nanopore:
NanoSim
NanoSim-H
SiLiCO
ReadSim
DeepSimulator
General long read simulators:
Loresim
Loresim 2
FASTQsim
LongISLND
For an exhaustive list of existing read simulators, see page 15 of my thesis, Novel computational techniques for mapping and
classifying Next-Generation Sequencing data.
9
tl;dr: Just use the either the downloads on the Bowtie2 homepage or the Illumina iGenomes. Or just uncompress and concatenate the FASTA files found on UCSC goldenpath and then build the index.
A bit longer answer:
There are two components to "genome for a read mapper" such as Bowtie or BWA.
First, you need to choose the actual sequence (genome release ...
9
By chance, just today I've heard of a nanopore read simulator, NanoSim. It is released under a GPL license. I have never used it, though...
7
In addition to the already mentioned NanoSim, there is also SiLiCO and ReadSim (although it hasn't been updated in over 2 years, so I am not sure how relevant it is at this point considering how fast the technology is progressing).
7
PCR polymerases introduce errors. When an error arises in the first few cycles of amplifications, it will appear in a reasonably high fraction of DNA fragments in the library. After sequencing, you may see the same error occur to multiple reads. If you remove PCR duplicates when calling variants, all errors are reduced down to one read. For high-coverage ...
7
There are also third party free and open source basecallers that haven't been developed by Oxford Nanopore.
Of particular note is Chiron, which gave the best uncorrected assembly identity among the base callers that Ryan Wick tested. It's slower than Albacore, but appears to be more customisable, and could theoretically be used to model any DNA feature that ...
5
Early MinION sequencing runs had forward and reverse DNA templates joined together by a hairpin adapter, so that the sequencer would read both strands from the same template. The consensus sequence that was generated by combining the base calls of opposite strands is referred to as a 2D read.
Due to a dispute with Pacific Biosciences, and for other reasons ...
5
It's worth noting two things as of Dec 2018:
Albacore is being deprecated (but is still available from the Nanopore developer portal).
Guppy is under active development, so Ryan Wick's comparisons may not reflect the current state of things. (The claim is that the current, just-released version of Guppy uses a new "flip-flop" algorithm that improves ...
5
First of all - yes, you can generate FAST5 files and basecall later. Basecalling during the sequencing run is useful if you want results more quickly. You can also recall your FAST5 files with multiple basecallers, if desired.
There are several ways to basecall currently:
MinKNOW
Albacore
Guppy
MinKNOW uses an embedded version of Albacore to perform its ...
4
In addition to what others have suggested, I would also recommend PaVE as a resource. This is a curated database maintained by the NIAID and current holds over 300 papilloma virus genomes.
4
Yes, if the insert size is smaller than the read sizes, this would happen. For some applications, for example SNP detection for molecular diagnostics purposes, this approach is used.
4
You would expect to have high coverage, given the plasmids are short, so de novo assembly would be likely very easy. Given that each plasmid is present in different multiples, you would expect different coverage on each plasmid, so it might be best to approach it as a metagenome-type or transcriptome assembly, rather than a classic genome assembly.
...
4
Typically I use samtools for operations like this. Specifically I use samtools view with either -r or -R flag depending on the use case.
-r STR
Output alignments in read group STR [null]. Note that records with no RG tag will also be output when using this option. This behaviour may change in a future release.
-R FILE
Output alignments in read groups ...
4
Update 2:
I looked into this a little more, with the various data sources.
This is related in part to the answer submitted by OP juanjo75es, in addition to discussion on chat. I don't entirely understand the logic, but the general thrust seems to be that SPAdes makes weird assemblies somehow.
Some notes that I made:
REFERENCE ASSEMBLIES
FIV sequence U11820....
3
If you just want the human chromosomes in a FASTA format, why not downloading directly the individual chromosome files (chr*.fa.gz)?
If you don't rely on the "official" releases (for whatever reason), then what you need is first to assemble your reads into genomes, possibly (but not surely) going down to a chromosome-level resolution. Different approaches ...
3
I don't think you can use the --quantMode GeneCounts option with no annotations. I think the error is trying to look for an exon file generated from the annotations to do the quantitation on. Remove that and I think it should work, as the manual specifically states that annotations are optional but highly recommended.
3
The best nanopore read simulators would be associated with the best base-callers. For a base-caller to effectively model the DNA strand, it needs to take into account the expected underlying electrical model together with the associated signal noise (both in the time dimension as well as the amplitude dimension). In theory, it should be possible to reverse ...
3
If you google AGTATGTACAAATACCTACAACTTGTGCT you'll find it's a primer sequence: https://artic.network/resources/ncov/ncov-amplicon-v3.pdf
2
Influenza virus resource at NCBI or FluDB.
2
I've created an issue on the Canu github repository for this. I'm not aware of any existing functionality to output FASTQ files, but think that this would be a useful feature to have.
It would be possible to create something like this by aligning the original reads to the genome, generating a pileup from that alignment, then determining the sequence ...
2
What I wanted to do is called "Consensus Sequence". Two steps were needed:
$ bcftools mpileup -Ou -f ref.fa input.bam | bcftools call -Ou -mv | bcftools norm -f ref.fa Oz -o output.vcf.gz
After that you can create the consensus:
$ bcftools consensus -f ref.fa output.vcf.gz > out.fa
2
Let's take a step back and consider the "perfect" output for a de novo assembly algorithm. Ideally, you would like to see one complete sequence for molecule (chromosome, plasmid, etc.). In reality, this is difficult to achieve due to a couple factors.
By random chance some regions may have low coverage, meaning that there are an insufficient number of reads ...
2
The Illumina HumanOmni1-Quad beadchip is a microarray device consisting of 1,140,419 markers which have derived from the 1,000 genomes project. The markers chosen are is high-value regions of the genome: ABO blood typing SNPs, cSNPs, disease-associated SNPs, eSNPs, SNPs in mRNA splice sites, ADME genes, AIMs, HLA complexes, indels, introns, MHC regions, ...
2
This sounds more like a job for samtools split if you want to split out all the read groups into separate bams in one go.
http://www.htslib.org/doc/samtools-split.html
samtools split [options] merged.sam|merged.bam|merged.cram
Splits a file by read group.
Options:
-u FILE1
Put reads with no RG tag or an unrecognised RG tag into FILE1
-u FILE1:FILE2
As ...
2
Mates in a pair are giving signal for a single strand, though this is only apparent in bisulfite-treated samples. The reason for this is that you are sequencing the ends of fragments of material and it's random which strand of this (or both in different clusters) will get sequenced. Different pairs of reads will then randomly sequence one strand or the other....
2
After many considerations, I am going to accept the response from Maximilian Press. I see now that some viruses have high variability (HIV even 50% of the sequence). Therefore MN630242.1. and U11820.1 are apparently two strains. There are things I still don't understand but these are beyond the initial goal of my question. Concretely:
Why SPAdes returns one ...
2
This is quite a similar question to this one, but I notice that you're specifically asking about a probability distribution rather than differential expression. That sounds like gene dispersion and/or shot noise; a good reference for me on that has been the documentation for DESeq2:
http://www.bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/...
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