Science method

Metagenomics - Science method

The genomic analysis of assemblages of organisms.
Questions related to Metagenomics
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Hi,
I'm new to shotgun metagenomics and just realized that there are multitudes of databases available to analyze the data, however no clear way to differentiate which one is better suited for which environment..
Which one to use for human gut shallow shotgun metagenomics data? (not looking to do de novo genomes, just to map to existing curated genomes..)
Looking at taxonomy databases for now, like GTDB, Web of Life, UHGG catalog....
Thank you for any advice!
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Thanks!
It seems that HUMAnN3.0 / MetaPhlAn uses the Chocophlan database. I'll try that out :)
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Dear researchers
In my subject, I work on the characterization of the Moroccan marine microbiota by metagenomics under the discipline of microbial ecology.
During the sampling, we could not have all the in situ measurements of the Physico-chemical parameters of the studied microbiome. That's why we had recourse to the extraction of spatial data from the NASA website to complete.
my question is: do we have the right to combine our own data with those of a database to analyze them? ethical and copyright aspects. since these data are submitted to the public with open access.
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If it is open access I see no reason not to use it. It is however essential that you should properly cite them.
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I am planning to run16S metagenomic sequencing on libraries prepared from colon content of C57BL/6 mice to understand the gut microbiota diversity of control group and DSS induced colitis group. I am having problem of very low library concertation of some samples from DSS groups after quantifying by qPCR. However, the qubit showed considerable amount of library concentration. I have repeated the library preparation on same samples by increasing DNA input and cycle numbers for PCR. But the result is still same. Can I diluted the libraries based on qubit concertation for further sequencing? Can I use fecal samples instead of colon samples for those samples for preparing libraries? Any information would be greatly appreciated. I have used following kits for library preparation and quantification.
16S Library preparation kit : Ion 16S™ Metagenomics Kit, A26216
Library quantification kit : Ion Universal Library Quantitation Kit, A26217
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Man Kit Cheung is probably right. In any case, I think this article might answer your second question.
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Dear researchers
In my subject, I work on the characterization of the Moroccan marine microbiota by metagenomics under the discipline of microbial ecology.
During the sampling, we could not have all the in situ measurements of the Physico-chemical parameters of the studied microbiome. That's why we had recourse to the extraction of spatial data from the NASA website to complete.
my question is: do we have the right to combine our own data with those of a database to analyze them? ethical and copyright aspects. since these data are submitted to the public with open access.
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Samir Ranjan Panda , Man Kit Cheung , Phil Geis thank you very muche for your answers :)
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Basically, the circular plasmid is more specific to identify its completeness. However, when we gain the metagenomic sequencing result from bacterial community or whole-genome sequencing result from bacterial isolates, after assembly of contigs, it is not clearly to confirm the completeness of linear plasmid.
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Unless you have overlapping contigs at either end of the plasmid it is impossible to tell in silico and would require experimental verification. It is possible to design primers near the ends of your plasmid assembly that would amplify across the remainder of the plasmid. This amplicon can then be sequenced to identify the remainder.
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I am trying to analyze the diversity of the bacteriome at different taxonomic levels
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Rocio Parra Laca A heatmap is a graphical approach to visualizing visitor activity data as hot and cold patches using a warm-to-cool color scheme. Warm colors represent areas with the greatest visitor engagement, red areas with the most interaction, and cold colors show areas with the least contact.
Also, have a look at this:
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Hi,
I have biological replicates: they come from the same raw sample (tube of sediment) but from different DNA extraction & sequencing experiments. These are metagenomes and I used whole genome sequencing.
If I treat them separately, the abundances are consistent, some of them cluster together on a PCoA but not so well on hclust.
Question:
1) Should I concatenate the raw fastq files together beforehand?
2) Or should I treat them separately until after the alignment to a db step and then sum the counts of each replicates together?
What is the best procedure?
Thanks
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Biological replicates of environmental samples will have some variations. Additionally, the quality/quantity of the DNA, as well as the library construction method will also interfere with the sequencing outcome.
I'm assuming you extracted DNA from the biological sample using the same method and at the same time. In addition, both were sequenced using the same library preparation techniques.
The final choice to merge or not will depend on the aim of the experiment. For comparative analysis, you can merge the samples to get a single assembly and then get the gene/contig counts from non-merged biological replicate reads.
If the comparative analysis is not your aim, you can merge the biological replicates and then use the merged reads to get the gene/contig counts.
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It's about RNA viruses metagenome.
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Thank you very much, Daniel Carrera Lopez!
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I am looking for packages to predict functional profiles from metagenomic 16S rRNA data in R language, as an alternative to PICRUst in Python. I found the Tax4Fun, but there are only a few examples of how to apply it. Does anyone know other similar and well documented packages?
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Hi Franciele Camargo, did you find sommething? iam trying to do the same thing but i don't find any thing actually
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I would bé gratful if you could send me a protocol to extracted metagenomic Dna from soil. The aime of work is shotgun metagenomics sequencing,so i'm looking for a good yield ans concentration. I already try with the power max kit of quiagen comptant and the concentration is very low.
Thanks
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Yes,metagenomics extraction of DNA is the best. But when you are experiencing low level of DNA,then check humus content,it may be a hindrance! Also,try changing the extraction kit. Use bioline product, it will help in getting more concentration of DNA.
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What are the best webserver/online tools for Downstream Analysis of 16S amplicon Metagenomic dataset besides Microbiomeanalyst ??
Thanks in advance...
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Hi,
EZbiocloud offers simple processing for 16S amplicon sequencing analysis, although, if I recall correctly, not much of control/information over the analysis pipeline.
dada2 + phyloseq or Qiiime2 are surely the better options if 16S sequencing analysis is a reoccuring task for you.
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as we submit genomic DNA sequences in various repositories (ex. NCBI). so is there any specific repository to submit metagenomic analysis results of 16s rDNA sequencing.
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Several platform you can prefer to submit your metagenome sequence data to NCBI-SRA(Sequence Read Archive), MG-RAST and ENA(European Nucleotide Archive)
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I have completed taxonomy assignment of the assembled contig from raw data but I cannot get the relative abundance of the species present. Is there any tool that can do that?
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Hello Ishtiaque,
I have found that Kaiju (taxonomy based on sequence homology) and Metagenomic Intra-species Diversity Analysis System (MIDAS; taxonomy based on curated phylogenetic trees) work terrifically for analyzing relative abundances of taxa with WGS data. These two tools complement each other as well.
Ryan
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Hello,
I want to determine the gut microbiome composition from my mice feces by using DNA metabarcoding sequencing of V3-V4 region from 16S rRNA.
I have contacted Novogene for doing it, and they offer 150.000 reads/sample and 30K Raw Tag.
Do you have any experience in using Novogene services?
Do you think this numer of reads for sample and Raw Tag is enough for species level discrimination?
Thanks in advance
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The species level discrimination not depends of the number or reads, depends of the technical approach, and V3-V4 is risky to go to species level, but good to go to genus level.
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I have a set of metagenomic sequence data from aquatic eDNA samples, and have been able to analyze the the bacterial/16S aspects of the samples but the program I use cannot analyze eukaryotic data. Does anyone have recommendations for programs that can be used to analyze eukaryotic metagenomic data?
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As an option you can do it manually by BLASTing your reads against 18s sets like SILVA ones. Next counting the relative presence of the species by assessing number of reads (and/or proportion of reads) aligned to a specific organism.
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Hi everyone! I'm trying to figure out how to process metagenomic data (obtained using qiime2 and picrust2 for qiime) to do some network analysis using igraph or similar (do you have any recommendations?).
Now, unfortunately I can't find a good tutorial about this passage, so do any of you have something which could help me?
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David Rosado-Porto yeah, but at the moment i'm struggling with the qza_to_phyloseq command, which somehow doesen't like my metadata file at all. Tried tsv, csv, excel formats, but nothing worked. I will update you!
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which extraction kit could be used for studies on metagenomics in bees?
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Excelente information Jeferson thanks!
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Hello.
I am trying to find differentially abundant microbes between two conditions. I have the relative abundance data but not the absolute read counts.
Is there any method that considers relative abundance data as input?
or any way to transform this data before use?
Regards,
Pratyay
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ANCOM-BC (ANCOM with Bias Control). You can run it easily in R using your relative abundance data without having to transform it. Here is some documentation you may find helpful:
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I have metagenomic data of gut bacteria of tribal population of Himachal Pradesh, can anyone help me regarding analysis of same for writing a research article. we will share authorship for the same.
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Many statistical analyses can be done on metagenomic data. Adding some details to your question will help narrow down the type of analysis you can do based on your research question.
  • What is your research question?
  • What type of samples did your study use? I guess stool samples?
  • What sequencing technology was used, and what was the library prep. protocol?
You can send a private message if it's easier to chat.
Best,
Hamza
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I am currently analysing Illumina sequences for a metabarcoding project. The primers used in the process have NOT been removed from the raw data. But after exploring the data, I found that ~5% of my raw data has no primers.
What could explain this 5% ? Should I discard these primerless sequences?
PS: The data was prepared according to the following protocole : 16 Metagenomic Sequencing Library Preparation Part #15044223 Rev. B (copy paste on internet to find it)
Thank
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If you are using trimming program, use parameter which discard the sequence which will be untrimmed because it doesn't have a primer sequence.
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I work on investigating the microbiome of the grapevines Rhizosphere using Shotgun-metagenome sequencing-Illumina. DNA was extracted using PowerSoil® DNA Isolation Kit - QIAGEN and further purified by Sodium acetate. Metagenomic DNA libraries (50 ng input) were prepared using NEBNext® Ultra™ II Prep Kit for Illumina®. The readouts of Bioanalyzer, Qubit™ dsDNA HS, or 16s PCR look perfect. However, the sequencing run gets always underclustered in case of my samples. Nevertheless, it disrupts the clustering of the other samples, too.
I look forward to any help!!
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Hi Islam M. Khattab
It's hard to cluster when the diversity is very high. Here's another reference that might help you:
Deconvolute individual genomes from metagenome sequences through short read clustering
doi: 10.7717/peerj.8966
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I have done both full-length 16S metagenomic microbiome and cultured microbiome identified with sanger sequencing. The results turned out greatly different from the metagenomics and cultured one, which should be usual. However, many microbes I cultured do not have the corresponding OTUs/ASVs in the metagenomic microbiomes. Regardless of the possibility of contamination, is there any other possible factor affecting the results?
Thanks in advance!
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I wouldn't expect that the difference is because of rarity of isolates, if the samples are not novel, because people have done a lot of isolation work for various environements. One possibiliy is that Enterobacteriaceae could be super low in abudance compared to others e.g. Clostridium, and thus it can be rarely detected by amplicon sequencing. This happened to samples e.g. sewage sludge or animal manure. In contrast, under a certain culturing conditions you provided for the bacterial community, Enterobacteriacease may happen to gain competence to grow. In that case, you could obtain the Enterobacteriacease, which you don't see in amplicon sequencing.
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The key difference in data (structure and function), effectiveness for which analysis, and which one gives more clarity for gene identification.
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Genomics explores the complete genetic information of a single organism be it a microbe, plant or animal, whereas metagenomics explores a mixture of DNA or RNA from multiple organisms and organs, and environmental samples
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Good morning,
Please I have an issue with my run and I need some help.
We did a metagenomic 96 sample run on Minion Mk1B (short-read 16S 400bp amplicons). The run lasted for 72 hours. Output was 9.7 gigabases (FAST5 files are 241GB). After this base-calling was initiated.
After 24 hours, the base calling was only 17% at which we aborted the base calling to do it on our server.
After 4 days now and only less than 20% is done. Why is it taking so long? We are using guppy v5.
What is the expected output size for such runs?
Does analysis usually take this long?
Is there a time limit by which we should stop the runs?
Thank you in advance.
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In my experience, yes, it takes many days to do base-calling with the guppy base-caller. However, it depends on what guppy version you used; if you use the guppy CPU version it will be much slower compared with the GPU version. The number of threads you used also affects the base-calling process.
I think no time limit for this. You just need to wait until 100% to get all your data converted to FASTQ by the program, or, you may need to adjust the base-calling parameters or change the program version and re-run the guppy base-caller to make it faster.
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Hello, I am trying to get a metagenomic analysis and found Novogene whose prices are pretty cheap (almost 1/3 of our university core). Does anyone have any experience with this company? about the data quality or reliability?
Please let me know,
Thank you,
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Hi Alba.
I had experience with Novogene, both for whole-genome and metagenomics.
The sequencing is very good, and I had no problems at all in terms of quality.
I don´t recommend to subscribe for their bioinformatic analysis, since the analyses performed are pretty basic and can be done easily by the researcher, and many times you need more complex analysis that are not included in the price.
Let me know if you need more information.
Ricardo
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For 16s rRNA profiling/ metagenomic analysis.
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DADA2 is widely used due to its accuracy and ease of use for marker gene-based community profiling https://benjjneb.github.io/dada2/index.html
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Please suggest a tool that can provide alpha diversity and beta diversity of microbes from shotgun metagenomic data either from raw sequences or assembled contigs.
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Hi Ishtiaque Ahammad, MG-Rast (https://www.mg-rast.org/) is a good tool for analyzing metagenomics data. After submitting your data it is possible to obtain a dissimilarity matrix for beta diversity analysis. With the generated abundance table you can also calculate diversity by other programs, such as R (as mentioned in the previous answer), or PAST (if you have difficulties in using software that demands greater programming skills).
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I need to extract DNA from the vaginal flora of cows for metagenomic studies. Does anyone know any extraction technique?
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Genetic and functional analysis of the bovine uterine ...
https://www.sciencedirect.com › science › article › p
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Hi,
Has someone experience in building a custom db using Kraken2?
I have downloaded the fasta files for some taxa and build the new db but it produced an unmapped.txt file with a long list of accession numbers.
What does this file mean? How can I deal with it? Can I overcome this issue?
How can I found out which taxa have been successfully included in the db that I have created?
Thanks
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Hi thanks, do you know if Centrifuge is better than Kaiju?
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Any body working on metagenomic DNA analysis in my connections? I need some help as regards the said analysis.
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16s amplicon, ITS, shotgun which one?
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I extract environmental DNA from a soil sample and sequenced using Illumina's next-generation sequencing technology.
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DEAR Amsale Melkamu
Genovo: De Novo Assembly For Metagenomes, Journal of Computational Biology: a Journal of Computational Molecular Cell Biology 18(3):429DOI:10.1089/CMB.2010.0244.
Meta-IDBA: A de Novo assembler for metagenomic data,DOI:10.1093/bioinformatics/btr216
GOOD LUCK
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Hi,
This may not be the forum to ask this question, but we are looking for someone to analyse the raw metagenomic data. That person can become a part of the publication/s we aim to produce. All analysis will be done remotely.
I can give more specific details if anyone is interested.
Thank you.
Thilini
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Thank you for the offer. If you think me a suitable collaborator I may be involved in the analysis of your whole metagenome data. Please go through my RG profile and publications. I am available @ nazmul90@bsmrau.edu.bd
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I am planning to go for metagenomics microbiome analysis. I have selected 4 primers for the same which are:
520F: 5'- AYT GGG YDT AAA GNG -3'
802R: 5'- TAC NVG GGT ATC TAA TCC -3'
338F:  5'-CCTACGGGNGGCWGCAG-3'
806R: 5′-GACTACHVGGGTATCTAATCC-3′
However there are some ambiguous sequences like, N,H,W,V,Y in my primers. Even though I know the coding standards like N stands for any of the 4 nucleotides(A,C,T or G) but i am confused which nucleotides should i put in to replace ambiguous letter. If anybody has any information. Please help
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1. You are using 16S and that is not a metagenomics analysis
2. Not clear what do you want to do by replacing the degenerate bases in your primers, and I am not sure if you know why they are used in primers
3. No analysis require the degeneracy of bases removed from primers, and that is why the question "why do you want to do that".
4. Interpreting the question and your reply above, it appears that there is a lack of understanding the basics of molecular microbiology and I would recommend to clear the basics before moving forward.
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I am working on sequence based metagenomics analysis, and I am having difficulty choosing which tool to use for binning of the contigs.
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There is no set rules in choosing binning tool unless you are doing supervised binning or binning from long reads. For shotgun metagenomics, there are many binning tools, of which MAXBIN, METABAT2, CONCOCT and BINSANITY are widely used. Whats importent is rather than relying on one tool (unless your study goal needs) it is better to use multiple tools and then use any BIN refiner ( DASTool, Binning-refiner and MetaWRAP refinement module) to select quality bins.
Workflows/pipelines such as ANVIO, MetaWRAP,SqueezeMeta, ATLAS can do the automatic binning using multiple binners and extrecting quality bins via bin refiners. Personally, i assemble my contig via metaspades then use metawrap binning ( MAXBIN, METABAT2, CONCOCT) refinement module and later import these bins in ANVIO for manual refining and other analysiss.
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I know that Shi et al 2016 inferred hosts for novel RNA virus genomes by searching their genes across cellular genome databases, so linking them with endogenous virus elements (EVEs).
Are you aware of other methods infer hosts for RNA virus contigs?
Thank you,
Guillermo
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The answer is found in the results of this study:
Nat Commun. 2017; 8: 16054.
Published online 2017 Jun 28. doi: 10.1038/ncomms16054
PMCID: PMC5493757
PMID: 28656958
Virus-host relationships of marine single-celled eukaryotes resolved from metatranscriptomics
Mohammad Moniruzzaman,1 Louie L. Wurch,2 Harriet Alexander,3 Sonya T. Dyhrman,3 Christopher J. Gobler,4 and Steven W. Wilhelm
we examined metatranscriptomes from two highly productive sites on the east coast of USA—Quantuck Bay, New York, and Narragansett Bay, Rhode Island. Quantuck Bay experiences recurring ecosystem disruptive brown tide blooms caused by the pelagophyte A. anophagefferens16, which are shaped by a giant virus (AaV)7,17. Narragansett Bay is a highly productive system with seasonal diatom blooms, but a poorly described eukaryotic virus community. By employing selection for polyadenylation before sequencing, we were able to focus on active virus infections within eukaryotes. Using time-series data, we captured emergent relationships of putative virus–host pairings and their ecological dynamics. This approach also allowed us to characterize viruses with diverse nucleic acid genomes actively infecting eukaryotes. The results show that this approach could both confirm known virus–host infections (including the infection of Aureococcus by AaV) as well as identify novel virus–host interactions. These observations demonstrate that the depth of virus–host interaction in the global oceans is likely much deeper than previously anticipated, with viruses containing all forms of genetic material potentially infecting single-celled eukaryotes.
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16s rRNA gene sequencing/metagenomics.
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As you said in your question "16S rRNA sequencing uses PCR to amplify a specific region of DNA", that is the main difference. 16S rRNA amplicon sequencing will sequence only the 16s gene in the provided DNA sample. Whereas, metagenomic will sequence all or most of the genes within a provided DNA sample. So, with 16s sequencing, one can get only the taxonomic information (from which bacteria does the 16s sequence came) while from metagenomics, both taxonomy and functional potential of the sample can be determined.
Note: There are some algorithms like PICRUSt which can PREDICT functional genes from 16s sequencing. But this can be used only for prediction and not conformation of a particular functional gene.
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Hi everyone
I'm processing some leaf samples collected in different rivers for shotgun metagenomic sequencing (Illumina NovaSeq 6000).
The company that will sequence my DNA samples (Novogene in UK) requires a 260/280 ratio =1.8-2.0 (no degradation or RNA contamination).
(Novogene webpage:
But I've sent samples in the past (to the same company but for amplicon sequencing) with 260/280 = 1.7-1.8 and they passed the quality control and went full analysis.
Regarding the 260/230 ratio, they do not refer any requirement but my 260/230 ratios are even lower (the lowest is 0.6).
I'm using the DNeasy PowerSoil kit (Quiagen).
So my question is, how low can these ratios be for shotgun metagenomic sequencing?
What's the limit?
I know that I will probably have to clean some samples but I just want to have an idea to help me select the ones I definitely have to clean.
Thanks a lot!!!
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First you have plants sample is Wash carefully and after that extract prepared and then filter the method for the concentration of, removal and enumeration of bacteria in liquid and air to avoid contamination of microorganisms for example fungi and then used other filtration method Sach as centrifugation.
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Previously, I colllected the oral swab samples in Zymo DNA/RNA sheild solution. I would like to perform the saponin based host depletion before doing the shotgun metagenomic sequencing.
I have concerned that DNA/RNA sheild could break the bacterial cell prior to host depletion. I have no idea about the component of this reagent. Do anyone have suggestion about this concern?
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It will not break but please do not leave it long time otherwise you will lost some.
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How can I best analyze the 16s amplicon sequencing data obtained from multiple runs? Do I have to run all the sequencing files in Qiime again? Are there any tutorials available?
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The best and most correct way to proceed would be reprocessing all the raw-data from different sequencing run with same parameters and together. The OTUs will surely change. With merging two separate runs, you would be forcing the two datasets to appear similar. Reanalysis would take only a few hours anyway.
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I am performing a metagenomics based experiment, where I need to send the sample to an external facility for NGS. The transit is of approximately 7 days. What can be the extraction and transfer protocol that can be followed?
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Hi,
To get a productive amount of DNA from your environmental samples, you can use Qiagen DNeasy Powersoil Kit to extract the metagenomes. I did use this kit and got a brilliant result after sending it to my external NGS facility.
If your concerned samples are soil or sediment or any other naturally-governed origin, then you must use specific kit to remove pollutants or strong organic matters hindering the DNA isolation process. Using any simple DNA isolation kit might not gives you all the extractable DNA confined to those natural media.
For transportation, you can certainly use dry-ice in a tightly sealed container and that will roughly give you a 3-4 days of time (as in my case, it was 4 days and samples were fine in it).
Best,
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Hello all Professors
What are the kits used in 16S rRNA Metagenomic sequencing (MiSeq Illumina) after the DNA extraction from human tissues (biopsy)?
Thank you in advance
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I think you are asking about library preparation. You should use TruSeq DNA PCR-Free sample preparation kit (Illumina Inc., San Diego, USA) for library preparation.
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I have microbiome sequencing data and I have analysed it to determine which taxa are up or down-regulated with my treatment, however, this doesn't really tell me much about the metabolic changes.
Is there anything I can use that is similar to the Qiagen IPA where I can place my metagenomics data and it can tell me if there are any changes in metabolic pathways?
Any links and tutorials would be greatly appreciated!
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I was wondering which databases would be best for a scoping review on how drugs effect the microbiome. Not sure if this falls into pharmacology, microbiology or metagenomics, but I would probably want to search a database that contains all of them!
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Thank you for nice question. There are many tools to predict both microbiomes and resistomes. However, the drugs interact with microbiomes is really challenging. You can use MASI: microbiota—active substance interactions database (https://doi.org/10.1093/nar/gkaa924).
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I am interested in doing microbial diversity analysis associated with a plant. I was looking for PNA clamps suppliers who can provide me mitochondrial PNA and plastid PNAs. Let me know if anyone has used it in their experiments or if someone can provide me as a courtesy.
Thanks in advance.
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I have been using them many times when working with grapevine-associated microbiome. As a rule of thumb I would check before-hand if they match the specific target you want to prevent and then they should work quite well. Only recently I had problems with wheat mitochondrial DNA and so far I have not had any luck using mPNA
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Hello,
I made index from my reference file and run command to align my metagenomic data by bowtie2. command is
bowtie2 -x <index_referance> -1 <paired_end_read_path_1.fastq> -2 <paired_end_read_path_2.fastq> -s <outputname.sam> and i got this result on screen without getting sam file in output folder.
16190304 reads; of these: 16190304 (100.00%) were paired; of these: 16189692 (100.00%) aligned concordantly 0 times 612 (0.00%) aligned concordantly exactly 1 time
0 (0.00%) aligned concordantly >1 times ---- 16189692 pairs aligned concordantly 0 times; of these: 59 (0.00%) aligned discordantly 1 time ---- 16189633 pairs aligned 0 times concordantly or discordantly; of these: 32379266 mates make up the pairs; of these: 32379200 (100.00%) aligned 0 times 66 (0.00%) aligned exactly 1 time 0 (0.00%) aligned >1 times
0.00% overall alignment rate
Can anybody tell me what are these results and what's wrong with this??
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For your purpose i.e. to know whether a given organism or closely related representatives are present in your metagenome or not , BBMap (https://sourceforge.net/projects/bbmap/) would be very convenient. This tool requires no installation and the command-line would be something like- bbmap.sh ref=fecal_indicator_genome.fasta in1=paired_end_read_path_1.fastq in2=paired_end_read_path_2.fastq outm1=fecal_genome_mapped_1.fastq outm2=fecal_genome_mapped_2.fastq minidentity=0.95
The above command-line will output only mapped reads that are somewhat closely related to your genome of interest (you may lower the minidentity values but the number of spurious mappings may increase and the overall mapping stringency with respect to your reference may go down; use minidentity=0.98 or 1 if you want very stringent mapping). You may further re-assemble these mapped reads on Spades and then analyze if this new metagenome-assembled-genome is actually represents your ref genome or if it is closely related
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I'm working on ARGs analysis from shotgun metagenomic data sets. I want to learn how to analyze mobile genetic elements by using ACLAME database. Is there any guidelines ?
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You may visit this site http://aclame.ulb.ac.be/. I hope that it will help your endeavor.
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I am looking to use the Illumina DNA prep kit 96 well edition for metagenomics on stool extractions. I've heard that you can get many more samples then just 96 out of a single kit, how many can you actually get out based on the amount of buffers, beads, etc? Looking to see if anyone has empirical experience with this. Obviously the indexes will have to be on a second plate if there are more than 96. Thank you!
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Thank you for the answers! It sounds like I will just use the prescribed amount then.
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We are collecting human samples and thinking to use some storage buffer to ensure optimal preservation of RNA and DNA, among other molecules.
We saw several papers, and authors mentioned Allprotect Tissue Reagent (QIAGEN) as storage buffer, but we did not find anything about its composition. Then, I decide to ask if anyone knows whether Allprotect Tissue Reagent (QIAGEN) was a buffered salt solution such as RNAlater (Life technologies) is, since we we need to take this into account for the subsequent treatment of the samples.
Thank you so much.
Nerea
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Yes I am also checking the ingredients of this Qiagen Allprotect reagent too. Qiagen should not just cover it this information as a business secret because we need to know for risk assessment. Some researchers bring this reagent to operation theratre for collection of human tissue samples and this maybe accidently contaminate with patient especially in operartion site etc.
If any one knows about the ingredients of allprotect (Qiagen), pls share too. Thanks.
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For my metagenomic shotgun analysis, I extracted total DNA from my food sample. I checked the concentration through nanodrop; there I got the good concentration of my samples but while running the gel, I did not receive any prominent band. I used 1 microliter of 6X loading dye and 3 microliter of my sample. what could be the possible reasons?
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How much elution buffer/TE buffer/nuclease free water you used to elute the extracted DNA? If you used more than 25 micro litre of elution buffer/TE buffer/nuclease free water to elute the DNA, then you may need to reduce the volume by drying the sample at 56 degree celcius temperature to make the final volume of 20-30 micro litre. Then, use 0.5 microliter of 6X loading dye and 2.5 microliter of extracted DNA for gel electrophoresis and run the DNA for 45 minutes at 50V in 1% agarose gel. I think you can see the DNA band (Photo attached).
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Hello,
I am interested in ordering universal hybridisation capture probes that can bind and identify as much animals species as possible. And same for plants and fish.
Later this captured (enriched) region can be sequenced on Illumina platform.
Since DNA barcoding for animals is done via COI region, is there a universal probe that can capture and purify this region for sequencing later?
Thanks
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Dear Farhan,
Brian gave to you some good ideas. For more details, I can recommend using DNA barcoding DB, BOLD where you can find a lot of certain info on animals and other organisms COI and other molecular markers. Also, there you may get info on primers from the special library.
YK
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There are several protocols available to perform sampling for metagenomics, such as Splash freezing, freezing, EDTA etc. Each method has its own pros and cons. Which sampling and sample preservation protocol is the best to reduce biasnesss as well as the taxonomy consistent?
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Use random sampling, correct sample size, proper controls, consistent methodology, and true replication to avoid post-sampling bias :)
How to Avoid Sampling Bias in Research | Alchemer
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We are doing a Metagenomics study to find a possible link between gut microbiomes (with different diets) and activation of immune response. Considering that the DNA amount in faecal samples might be low, I'll need an expert advice on choosing the right DNA extraction kit which someone has used during their Metagenomics research. Thanks!!
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Hi Leila!
In my research, "I used AccuPrep® Stool DNA Extraction Kit". I hope this can help you.
Best,
Romina.
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Hi All,
I'm currently working on identifying lignin-degrading enzymes from metagenomic sequence data. I have come across several papers and articles where the FOLy (Fungal Oxidative Lignin enzymes) database has been mentioned and described but I have not been able to find a link or address where I can access this database.
Can anyone with useful information help me out, please!
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Dear Jessica, thank you for posting this interesting technical question. uUseful information about this and related databases can be found right here on RG. For example, please have a look the the following article:
Lignin Database for Diversity of Lignin Degrading Microbial Enzymes (LD2L)
Deleted research item The research item mentioned here has been deleted
This paper has been posted by the authors as public full text on RG. Thus you can freely download it as pdf file.
Moreover, please see the following relevant reference:
FOLy: an integrated database for the classification and functional annotation of fungal oxidoreductases potentially involved in the degradation of lignin and related aromatic compounds
Unfortunately this very interesting paper is not yet available as public full text on RG. However, most of the authors have RG profiles. Thus there is a good chance that you can request the full text directly from on of the authors via RG.
I hope this helps. Good luck with your research and best wishes, Frank Edelmann
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I am soon starting a project, in which I aim at isolating bacteria from the muccus of Aiptasia ( a model organism for corals). I do not have a lot of experience in this field and I hope to get some technical tips and tricks. I will have three different strains of Aiptasia and try to obtain bacterial isolates from all of the three. The obtained colonies will be subjected to whole genome sequencing in order to determine the exact strain that was isolated (16S rRNA sequencing would not be enough for that). Is there a robust control, to exclude that the bacteria originated from the surrounding water and not from the muccus of Aiptasia? Thank you in advance.
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I have carried bacterial metagenomic analysis between multiple groups (five in total). The groups represent daywise changes in metagenomic contribution. To compare the data taking into account the sequencing depth and also gene length, the nearest normalization method I came across is TPM (Transcripts per million).
Is it ok to use TPM values to compare metagenomic groups and percent TPM contribution (by calculating the percentage of TPM values) of each gene/function?
Similarly, is there any better statistical method (other than TPM conversion) to compare gene abundance change by normalizing the data (Not include DE analysis)?
Thanks:)
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Thanks. I had a look at the QIITA workflow. seems like it is similar to what I did with my data except for DGE, which I am skeptical to use with metagenomic data. Sounds like TPM will be the best suit for my analysis. Thanks.
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I am currently carrying out the analysis of effluent samples from agricultural processing factory, and among others, I will be needing a lab where I can carry out the metagenomic analysis to reveal the bacteria, fungi and archaea present. Kindly send me a mail on kolafasina@com or leave a message here for me. Thanks
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You can as well contact Inqaba Technology Limited in South Africa. They provide quality services. info@inqababiotec.co.za
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Hi,
I have been trying to isolate metagenomic DNA using the conventional method of DNA extraction by using SDS for cell lysis and Isopropanol for precipitating the DNA followed by 70% ethanol wash. The resultant DNA contained humic acid contamination.
To avoid such contamination I was suggested to use PEG 6000, because of the non-availability of PEG 6000 can I use PEG 4000. If so how can I compensate PEG 6000 with PEG 4000?
Kindly help me in this regard.
Thank you in advance for your answers.
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I think it's worth trying. Generally, PEG 8000 is considered effective for DNA precipitation in case of humic acid contamination, but PEG 6000 and 4000 can also be used. They all can show DNA precipitating properties, but have differences in their molecular weights and efficiency. You may increase the concentration of PEG 4000 to compensate for its molecular weight.
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Hello, research community,
I am looking for some open problems in bioinformatics specifically in the area of, but not limited to, proteomics, and genomics. Since I am new to this area, any useful suggestions, a discussion on open problems and relevant resources are welcome.
Thanks.
Rahul
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examples:
Protein structure prediction
single cell RNA/DNA unsupervised learning/clustering
correlation of gene expression & variation with clinical outcomes
many more open problems tbh
e.g. see DeepVariant by google research
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I have assembled "bins" from metagenomic samples. But is there any tool that can tell me which species do these bins/putative genomes belong to?
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Sourmash or GTDB-tk for instance.
You can get the taxonomic classification of a bin, but if you are thinking you will get the same taxonomy to each and every scaffold, then that is practically not possible.
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After metagenomically assembling bins, how do I check their quality? is there any tool to improve their quality? Are there any tool to validate the genomes?
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First, use CheckM for quality of metagenome assemble genome
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Dear Colleagues,
Is it possible/feasible to assign Gram-positive and Gram-negative bacteria in a sample purely based on 16S or metagenomic sequences without gram staining?
Thank you very much.
Regards,
Nathanael
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Yes. It is possible. All you need is the appropriate database and software for analysis depending on the type of 16S (Illumina or PacBio)
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This is my first time of collecting water samples from marine environment. Could somebody please tell me the technique? I mean what kind of equipments (I usually used plankton net for freshwater) and procedures, in terms of collecting samples for metagenomic analyses. I could read from articles (and I did) but I need more practical quidance. Thanks a lot!
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Younes Boundir thank, but I can't read French
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I want to extract bacteria DNA present in blood. Could somebody recommend me a protocol.
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thank you
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Any certificate course or institution where I can learn the basics and advanced level of metabolomics and metagenomics data analysis?
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I am working on a urine metagenomics project, and I was wondering if there is a manual urine microbial DNA extraction protocol that provides DNA from gram positive and gram negative bacteria along with fungal DNA too, so I can run a pretty general, inclusive metagenomics test on urine?
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Hello, easy simple and reliable method for DNA extraction is benzyl chloride method.
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I am working on developing metagenomics as a tool for diagnostics, but I am stuck at providing a significant value or amount corresponding to the number of reads obtained from sequencing.
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Metagenomics is compositional. You can compare compositions but you will not have absolute values of concentration of bacteria. What you can do is to use a normalization factor. For example, you can quantify the number of reads mapped to a universal gene (better if a single copy, for example, recA). But still, always keep in mind that you are dealing with a composition.
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Which DNA extraction kit or protocol would you recommend for studying the fish gut microbiome (16S and metagenomics)? I noticed that not every well-established protocol for human stool samples works well for fish-feces too.
Thanks for sharing your thoughts!
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Hello Stephanie Celine, I am also trying to come out with a better protocol for DNA extraction in the trout gut for 16s. did you find a better one. Please help me if you did.
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I am looking for ideal configuration details for a workstation to perform a metagenomic, transcriptomic and whole genomic analysis.
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You may see the image attached herewith. I hope this resolves your query.
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STAMP(Statistical analysis of metagenomic profile) can create a stamp file from MG-RAST profile. The present version of MG_RAST is providing TSV file or TSV detailed file. So, I am unable to create a stamp file from the MG-RAST web server data. Can someone help me in creating the stamp file from the present version of the MG-RAST web server data output.
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Hi. I hppe the following website could help you:
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I have used eztaxon database (http://eztaxon-e.ezbiocloud.net) to find the taxonomic classification 16S rRNA sequences. This tool analyzes only for one sequence at once. There are thousands of sequences in metagenomics data. So I want to analyze for multiple sequences.
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Hi Sanchita! Thank you very much for the important question. For species level identification, you have limited database options, and includes only PathoScope (https://doi.org/10.1186/2049-2618-2-33) and IDSeq (https://idseq.net/).
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Hello, I have a few hundred trimmed 16S metagenomic sequences from the Human Microbiome Project online database that I would like to search for the presence of several strains of bacteria via pairwise sequence similarity. Does anyone have any recommendations for software that can achieve this?
I am not a bioinformatician by any means, so something that has a user-friendly UI and can run on Windows would be much appreciated (although I can make my way around a command-line interface if need-be)!
As an aside, can I make a reasonable claim for species-level identity solely using 16S sequence identity? If so, is the >97% threshold generally accepted or is there another metric (e.g., score-based) that is more reliable?
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Hi Abhijeet!Thank you very much for the important question. Very difficult question to answer. You know metagenomic data can be of two different types i.e. Targeted/amplicon (16S rRNA) metagenomic data and shotgun whole metagenome sequencing (WMS) data. For the first one, you can analyse your data using QIIME, MOTHUR, MetaMLST, PanPhlAn, IDSeq, Pathoscope and MG-RAST (http://www.metagenomics.wiki/tools/pathogen-screening).
For WMS, you have limited database options, and includes only PathoScope (https://doi.org/10.1186/2049-2618-2-33) and IDSeq (https://idseq.net/) and MG-RAST (https://www.mg-rast.org/) (see our latest articles: https://doi.org/10.1038/s41598-019-49468-4; https://doi.org/10.1016/j.ygeno.2020.09.039).@
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I am preparing a metagenomics experiment from the soil sample. I will use Oxford Nanopore technology, which has only limited throughput (approx. 8 GB), so I need to discard all eukaryotic cells before the sequencing (because their genomes are really large, and would saturate the device quickly). So I am interested in the simple and reliable method, how to obtain only the prokaryotic and viral species. Is it a good idea to use some syringe filters? E.g. with the pore size 1 micron? So the eukaryotic cells will be stuck on the filter surface, and bacteria, archaea, and viruses will go through?
Thanks for all suggestions,
Martin
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For details of the possible methods to use, the article suggested hereunder refers.
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I've successfully uploaded my metadata file and assembled, shotgun metagenomic dataet to my MG-RAST inbox. The metadata passed the QC-like step, my sequwnce data uploaded just fine and I could happily move on to the submission step. Everything works beautifully until I get to the tab where I submit my sequence data, which is there but in red text and I can't select it.
Has anyone else had this issue and knows what the problem is?
I have deleted and re-uploaded both the sequence and metadata files but with no success. Any help/advice would be hugely appreciated!!
Thanks in advance.
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Hi and good day! I have been finding the answer to this too, and found it myself in the end. I thought it would be good to share the information. The sequence files will be in red font and unselectable if the total bp is less than 1,000,000 bp, which is the minimum threshold.
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Hi
I am extracting genomic DNA from dust samples and the 260/280 ratio is 1.4 whereas 260/230 is 1.35. I need to perform the metagenomic sequencing and for the same, the recommended 260/280 ratio should be greater than 1.8. Can anyone help me with how can I improve this. I have tried ethanol precipitation but it causes a significant reduction in the yield. As these are environmental samples the yield of genomic DNA is already low.
Thanks
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Your observation that you cannot visualize DNA on an agarose gel is a hint that you might have very low "true" DNA concentrations in your sample. UV-Vis measurements - and this includes Nanodrop - are sensitive to contaminations in your DNA extract. Therefore, my recommendation is to check the DNA concentration with a more sensitive and more specific assay such as SyBrGreen. Also, you could spike your DNA extract with a known amount of a pure DNA (e.g., DNA ladder for sizing on gels), to see whether your instrument works well.
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I am working on some soil samples acquired from 16S RNA sequencing. In order to see which environmental factors influence community composition, I am using RDA(because dca() axis length <3.0).
I am confused on how to interpret the result from RDA and the subsequent anova.cca().
Q1: after running ·mod <- rda(otu_data ~ pH + T + N, env_factor)·, we get constrained eigenvalues of ·RDA1 RDA2 RDA2·, so is RDA1 means pH ?? If not, what does RDA1 represent?
Q2. using · anova(mod, by='term')·, we get a permutation test result like
` pH p-value=0.001; T p-value=0.03, N p-value=0.002 `. p-value of environmental factor pH is significant for what? It means pH is significantly responsible for community difference? This anova() function permute what(otu_data or env_factor) to refit the model?
In Jari Oksanen's vegan tutorial, ·“The test is sequential, and the order of terms will influence the results“, does that mean pH will have smaller p-values in 'pH + T + N' than it in 'N + T + pH'?
Q3. Do we need to process environmental factor of different range. factor1 may in range 1~ 10, while factor 2 may in range -50 ~ 50. z-score not work, because it raise error in rda.
Thanks to you all in advance.
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Q1 The axes model the variation of the dependent matrix and the eigenvalues are a measure of how much of the variance is explained by a certain axis*. One axis is not a certain independent variable, but a linear combination of all of them (RDA1 means x*pH + y*N + z*T; so usually, none of the axis directly represents a variable).
*since the calculated R² is biased, it has to be corrected and so have the eigenvalues
I can recommend the Numerical Ecology with R book (ISBN 978-3-319-71404-2) for explanations and examples (the binding of the paperback version is not as high quality as the content, though).
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Hi, does anyone know of a method to remove, as possible, plant DNA by conserving as much fungal and protozoan DNA as possible, for metagenomic analysis?
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Next year I will start teaching metagenomics to master students (mainly focused on bioinformatics). Can anyone recommend a text book related to this topic? I am also interested in other related material such as video seminars. Thanks
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I am at the second year of teaching the metagenomic course to the master degree in molecular biology and bioinformatics. At the end, I decided to collect many presentations reported in youtube and in other online resources and I used them to design the course. Still, I did not find a very good book for metagenomics but some presentations (for example those from Dan Knight) are very useful!
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I am trying to work with my first data set of metagenomic analysis. I have a data set of gene abundance (normalized) organized in two categories. first categorie is more general: Aceton metabolism, Aminoacids and Derivatives, Carbohidrates, ....And a second categorie with more specific groups: Acetone carboxylase subunits 2, Alanine biosynthesis, ....
I only have numerical values , corresponding to normalized relative abundance. The other information I have is not numerical, but categories of genes ( like I explain above) How I can calculate a functional diversity index with this type of data? Can someone give me any hint or tell me some paper where I can get information? thanks marta
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Functional diversity metrics are calculated by associating species-by-site matrices, such as presence-absence or abundance of species, to the species' functional traits; i.e. morphological or behavioural traits that are related to the role the species may perform in the ecosystem. Functional diversity is a type of alpha or Simpson diversity and the link below will show you how to calculate it.
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Dear Friends and Colleagues,
To date very few journals are available to accept video articles for submission/publication in our field, although these types of articles are of paramount importance in microbial ecology in order to share new techniques and approaches.
For this reason, I decided to open a Collection titled “Multi-targeted approaches to evaluate microbial interactions and ecosystem assemblages in diverse environments” on the Journal of Visualized Experiments (JoVE): https://www.jove.com/methods-collections/919.
The purpose of the Collection is to offer a comprehensive overview of wet- and dry-labs perspectives in the field of microbial ecology.
The most recent Impact Factor for JoVE (ISSN 1940-087X) is 1.163, according to the 2019 Journal Citation Reports released by Clarivate Analytics in 2020, and the Journal is currently indexed in the major databases, including PubMed, EMBASE, Scopus and Web of Science.
After submission, each manuscript will be editorially and peer reviewed, which is typically a 1-2 month process. Once a text article passes review, a script will be generated. Generally, a filming date will be scheduled within 4-8 weeks after acceptance. A videographer will be sent to the authors’ site to film the procedure.
If you are interested, either message me or submit an abstract here:(https://www.jove.com/methods-collections/submit-an-abstract?collection_id=919).
Best Regards,
Prof. Elaine CP De Martinis, Ph.D – Full Professor, University of São Paulo, Brazil
Otávio GG Almeida, B.Sc. – Ph.D. candidate, University of São Paulo, Brazil
Guest editors.
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Thanks for sharing!
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I am currently in the phase a deep analysis of metagenomic data present in a water sample. There are multiple micro organisms that are only presented with one read in the data. Does that indicate that it is present in the sample, or are they just traces of the pathogen ?