8

tldr - The I*.fastq.gz file contains the read index sequences. long explanation Illumina uses a program called bcl2fastq to demultiplex sequencing runs. This software takes a list of samples and their associated indices and uses those sequences to make one or more fastq files per sample, binned by one or two index sequences on either end of the sequencing ...


6

To answer your direct question, there are a few reasons why there might be high levels of sequence duplication. From the FastQC help: The underlying assumption of this module is of a diverse unenriched library. Any deviation from this assumption will naturally generate duplicates and can lead to warnings or errors from this module. As @DevonRyan ...


6

FastQC assumes that all samples are for whole genome sequencing and will flag them as failed if they differ too much from that assumption. This will, for example, cause essentially all RNA-seq, ChIP-seq, and ATAC-seq samples to fail in one module or another. This is not any cause for concern and is completely expected. Primarily concern yourself with whether ...


6

Perhaps, grep is not the best tool to use in this case, but it should be in principle possible by using grep & sed. Here is an example showing three symbols around a match. zcat My_Hiseq_Data.fq.gz | \ grep -Eo '.{0,3}GATCGATC.*' | \ sed -En 's/.*/ \0/; s/.*(.{3}GATCGATC.{0,3}).*/\1/p' | \ grep --color=always GATCGATC Here are some ...


6

As asked as it is, the answer is probably no. Indeed, the highest expressed RPKM/FPKMs will be different from one condition (or tissue) to another one for example. Then, you may also have technical artefacts due to the wet-lab part or to the normalisation. For example, mitochondrial genes are often reported in the top expressed genes. Now, if you want to ...


5

Question 1: The additional sequences is needed because that is complimentary to the P5 sequence anchored to the flow cell. It is also the site for priming the Index 2 read on a MiSeq. The additional sequence is also needed for the read 1 primer in the cartridge to anneal to the correct place for the molecules. Question 2: The "GT" sequence you're referring ...


5

As has been said before, mappability to the 'human genome' depends on a number of factors, among these the reference version and type of reads, for which you are interested in GRCh38 and 2x150bp reads. Although I am not aware of numbers accounting for these particular reference and type of Illumina reads, the 1000 genomes project has provided the community ...


5

Mapping quality is determined by the repetitiveness of the genome, the sequencing error rate, insert size, the capability of the mapper and the nasty heuristics behind the mapper. MAPQ=0 to one mapper is not necessarily MAPQ=0 to another. That said, I get what you mean. You want to know the uniqueness/repetitiveness. It is still hard if you want to get a ...


5

The counts files for GSE89225 is the output of HTSeq-count as a large matrix. Unless you are developing a differential expression package yourself you should not attempt to directly use this. Rather, you should load it into R and use packages such as DESeq2, edgeR, or limma (those are the most popular ones). For convenience, in DESeq2 you would want the ...


5

As far as I'm aware, Illumina provide CSV annotation files for all their sequencing chips, which can be used when they can't be found in Bioconductor. You can find annotation information for the PorcineSNP60 here, in particular the Manifest file (CSV format). The format is Illumina's weird "we say it's a CSV because there are commas in it" format, so if ...


4

Yes, as a general rule of thumb mappability increases with insert size (up to a limit) and read length. Whether this will actually occur in a given case will depend more on how randomly the sequencing samples from the genome to begin with (i.e., if the library prep happens to select for/against high mappability regions then the insert size won't much matter)....


4

Disclaimer: I'm a developer for http://www.sequin.xyz. Sequin is a new set of spiked-in controls for next-generation sequencing, and that includes Illumina. We design controls for RNA-Seq, genome sequencing, metagenomics etc. Please study our papers if you want more details. Reference Standards For Next-Generation Sequencing by Hardwick should be a good ...


4

See here, in particular slide #10 from the tutorial: bwa mem -5SPM ref.fa read1.fq read2.fq > out.sam Here, -SP disables pairing. The Aiden lab and this paper also use a similar command line. Beware that there are many Hi-C pipelines, but not many are using bwa-mem.


4

You can have a look at cutadapt. It is capable of quality trimming for both ends as you can read here.


4

How are you evaluating sequencing error rate? My most recent re-calls of 2017 sequences are demonstrating median single-read accuracy over 96%. Before considering Illumina, it'd be worth it to do an initial correction using nanopore-only reads. This will make sure that the best results are obtained from the nanopore signal. First, make sure that the reads ...


3

Your initial guess is almost certainly correct. I don't know about the linked read libraries, but in the 10X single cell sequencing protocol, separating real barcodes from noise barcodes is an important and sensitive step in the analysis pipeline. The current analysis pipeline is to look at a plot, like the one you produced and find the "knees". The plot ...


3

I never spent too much time on choosing my trimming software, therefore I might have missed some jewels. I use trimmomatic when I need versatility and I am entirely sure that it trims reads on both ends. A more convenient option is skewer, they do perform quality filtering, but I could not find an explicit confirmation that it works on 5' too.


3

Here's a Python script (e.g., called map_entrez_to_ensembl.py that uses mygene.info to convert a list of Entrez IDs to Ensembl gene names: #!/usr/bin/env python import sys import mygene mg = mygene.MyGeneInfo() genes = ['3815', '3816', '2341'] results = mg.querymany(genes, scopes=['entrezgene'], fields=['ensembl'], species='human', ...


3

It is worth noting that the Illumina NovaSeq and NextSeq address all of the lanes of the flow cell from a single loading point (by default). So on those instruments, you end up with all libraries loaded across all lanes. Therefore for each index you will have L001, L002 (+ L003 and L004 if appropriate) FASTQ files (and R1/R2, again if appropriate). As @...


3

If you have used adapters containing barcode sequences (that identify each patient), you would presumably end up with one single tube with your libraries in it right? Correct, you have to prep each sample into a library. If so, you then "put" the contents of that tube along with DNA polymerase and nucleotides into one single lane of a flow cell? You ...


3

should we expect Illumina 2x150bp (or shorter, 2x75bp) reads to map relatively equally to all centromere sequences? No. It has long been established that different chromosomes are associated with different centromeric sequences. It is sometimes possible to tell which chr a read is originated from based on its sequence. The GRCh38 centromeres are trickier. ...


3

I doubt it, unless you are asking if mapping would be similarly bad for all centromeres. Here are some repetitive structures (probably not centromeric) that I've found in the nanopore reads for "human" sample NA12878, produced by the nanopore-WGS consortium: These structures are consistent in that they repeat lots of times, but the internal patterns can be ...


3

If you google AGTATGTACAAATACCTACAACTTGTGCT you'll find it's a primer sequence: https://artic.network/resources/ncov/ncov-amplicon-v3.pdf


2

Try LR_Gapcloser. I've used L_RNA_Scaffolder for trying to scaffold a genome (which turned out to be more complex than I had expected). It looks like LR_Gapcloser (written by the same people) is similar, but designed specifically for scaffolding using long-reads. That page also suggests PBJelly and GMCloser as competing tools.


2

The specifics will depend on the experimental setup and data, but a few general comments... 1) Metagenomic data is often large volume and high in microbial diversity but low and uneven in coverage; single genome assemblers may suffer particularly since abundant (or closely related) species/strains will tend to be interpreted as repeats within a genome ...


2

I wrote a Perl script to do this. Just like zgrep, it can search through as many files as you give it. You can use the -c switch to tell it how much context (how many characters) you want around the match. So -c10 will search for your target string and 10 characters on either side of it. If you don't use the -c, it will default to 155, which should include ...


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

I think you need to explain better what you have tried, including some code. You say that you were unsuccessful to download it, because of an outdated version of R. How did you do that? I am not sure what you have tried, but if you read the instructions for installation here, you need to type the following in R console: ## try http:// if https:// URLs are ...


2

It took me a while to figure out that the "index" is the same thing as the "barcode" that says which sample each sequence is from on a multiplexed run. If your data is not demultiplexed (single R1.fastq and R2.fastq files contain the information for multiple samples), then this I1.fastq file is what you use to assign each sequence to a sample (ie to "...


2

Out of all of the major trimming tools available and widely used (trimmomatic, cutadapt/trimGalore (trimGalore is built on top of cutadapt), fastp), I actually instead prefer bbduk which is part of the bbmap suite: https://github.com/BioInfoTools/BBMap https://github.com/BioInfoTools/BBMap/blob/master/sh/bbduk.sh It's much more "fine tuneable" than the ...


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