Science method

Metagenomics - Science method

The genomic analysis of assemblages of organisms.
Questions related to Metagenomics
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How can I effectively perform metagenomic assembly on large Illumina sequencing data from environmental samples, given that I have already completed quality control but encounter issues due to the data size?
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Several online resources you might try have limitations, so whether they work or not will depend on how much data you have. Most of them perform other analyses besides assembly, so you might consider what to do with the results and check if other tools available on the same site could also help.
You could try:
Bacterial and Viral Bioinformatics Resource Center (BV-BRC) https://www.bv-brc.org/
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Hello ResearchGate community,
I am looking for a statistician with experience in metagenomic data analysis to assist with a research project. The data involves genotypic diversity within microbial profiles, and we require statistical expertise to ensure accurate and robust analysis. Specifically, I am seeking someone who is skilled in handling large datasets and can provide insights through advanced statistical methods.
If you have expertise in this area or know someone who does, please feel free to reach out. I’d be happy to discuss further details regarding the project and potential collaboration.
Thank you in advance for your support and recommendations.
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Please contact me
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I have FASTQ files for metagenomic analysis of the 18S rRNA gene, and I began to analyze them using DADA2 in R, following the tutorial at DADA2 Tutorial(https://benjjneb.github.io/dada2/tutorial.html). However, I stopped at the taxonomy assignment step due to my laptop overheating, which means the device's performance is insufficient to complete the analysis.
My question is: Is there any way to complete the analysis and obtain the taxonomy results while using my laptop? Or is there an alternative to DADA2 that can yield similar results? I would appreciate your expert opinion.
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You can try run kaiju or kraken for taxonomic assignment. There are some online servers that can do it without the need to run it in your computer.
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There is growing interest in techniques like single-cell genomics and metagenomics to study microbes that are difficult to culture using traditional methods.
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There is no best method.
1) they are not cultivable
2) complex environments will have their own flora that will obscure the putative 1st time isolate
3) ypu'll have no ide what the novel growth will appear to be
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Dear All,
We are looking to buy a sequencer for NGS metagenomic analysis and whole genome sequencing. We would really like to get your feedback and user experience on which is better?
No doubt Illumina has been in the market for a long time hence has a bigger user database, but our budget is limited. The machine we can afford is from Illumina iSec100 or from Nanopore PS solo2 (promethion).
We are working in antibiotic resistance in wastewater and sewer system.
Any response would be very helpful for us.
Thanks in advance
Kanchan
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Unless you are sequencing something on regular basis, I don't think buying the above mentioned sequencers is specially helpful.
Illumina system you mentioned not only generate low amount of data, the read lengths are short. In any lab, there need to be specific someone to operate and maintain the seq platform, which will add additional cost for personal and space.
In case of Nanopore, if not used very frequent, the data generated is not cheaper and data quality is not relatively good as compared to Illumina.
Buying a seq service is a better option if the sequencing is not don't frequently or sample numbers are big.
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I'm making my research on metagenomics and I want to find the source of the command 'vsearch merge-pairs' that used to be 'vsearch join-pairs''
How can I cite that?
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You can find all the updated commands and information on the latest QIIME 2 environment directly on the QIIME 2 website (https://qiime2.org/). Additionally, you can join the QIIME 2 forum (https://forum.qiime2.org/) by registering yourself to receive the latest updates about QIIME 2.
I hope this information helps you.
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Hi there,
I have some 16S and metagenomic sequencing data from mice fecals and I want to upload them to NCBI Sequence Read Archive (SRA). I don't know what NCBI package is suitable for my animal fecal samples.
What packages should I choose to complete my submission?
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Dear Yuhang Wu,
You have already selected the correct package, as shown in the attached figure. Since you are working with 16S sequences, the packages you chose are appropriate.
For additional upload instructions, please follow the SRA submission guidelines. If you encounter any problems, feel free to reach out to me, and I will do my best to assist you.
Best regards,
Dr. Samrendra Singh Thakur
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I am doing a metagenomic data analysis.
Where from cell free DNA of AML patients who have sepsis.
It is a illumina NOVA Seq paired end data.
When I used various algorithms like minimap2, bowtie2 etc I got mapped reads of each TAXA.
What's the best way to predict Species abundance from its number of mapped reads ?
I have ref seq length of species also.
Some do say abundance = mapped reads/ ref seq length.
I wanted to know if there is any literature of how abundance could be predicted which is a more dynamic and robust quantitative value ?
happy to engage !
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have you had a peak into this publication-- maybe it can help? https://academic.oup.com/bioinformaticsadvances/article/3/1/vbad060/7156835
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Does anyone have any advice regarding 16s metagenomics and an appropriate sequencing depth and paired end reads. Expecting around 10-15 organisms within the samples.
Thank you :)
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Thanks for your reply :) I'm looking to find the low abundance organisms!
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I am a Nigerian researcher working on microbial diversity of an African fermented food product. I will appreciate it if l can get a location and price for shotgun metagenomic sequencing.
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Some well-known commercial labs that offer metagenomic sequencing services for food samples include:Novogene (United States, China, and other locations)Eurofins (Global network of labs)Microbiome Insights (Canada)DNA Genotek (Canada)
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Hi everyone! I hope you all are fine. I have tried many tutorials regarding the calculation of alpha and beta diversity, however, my RStudio is throwing up so many issues. Packages aren't getting installed due to some compatibility issues. That's another discussion. However, may I request you all to kindly guide me in calculating these diversity indices?
What R script should I follow to calculate the Alpha and Beta- diversity indices. People have told me to use vegan, but how to go about it?
P.S. My input taxonomic data comes from Kraken2, so I have sample_kraken_report.txt for all my samples.
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(https://rpubs.com/mrgambero/taxa_alpha_beta). You can solve this problem via the given link.
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full title: metagenomics and alternative approaches for the fundamental study and exploitation of telluric microflora
"alternative approaches" here means metaproteomic and metatranscriptomics ?
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Any omics study is NOT alternative to other, in your context.
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Hi all..
I am seeking advice on the preferred method for sequencing a bacterial 16S metagenome: Illumina platform or Nanopore method? Any insights or experiences would be appreciated. #sequencing #metagenomics #researchmethods
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Nanopore has an advantage when you want to use whole genome metagenome sequencing. The standard 16S metabarcoding is done by illumina, but nanopore can be used if you want to sequence the whole 16S gene.
the choice of which primers to use and the region to sequence also depends on the environment that you are testing. It is always advisable to do a PCR+Gel before you decide on the primers and send the DNA for sequencing, just to see that your choice is suitable for your data. In my experience not all primers work equally good in all environments.
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In a metagenomic library profile desired size is 450-550bp,getting unwanted fragments which is causing failure of the library or it is difficult to get the desired data after sequencing.
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Generally, column-based PCR cleanup protocols / or bead-based purification are not that efficient in removing short bases in the samples. I suggest doing a gel extraction of PCR product to select the desired size, before starting with library preparation. During library preparation, you can do bead-based purification as suggested by the manufacturer. However, starting material is very crucial in the NGS. We follow this in our lab, and we always get a good library with desired sequencing data. Regards
Venkat
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I have red poultry mite samples which have been stored in ethanol. Now I need to perform RNA and DNA extraction followed by shotgun metagenomic sequencing. I would like to know if there is a way to successfully extract the nucleic acids so that I have no inhibition or problems during the sequencing run. You opinion and experience is highly appreciated.
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Pretty much all RNA/DNA extraction kits (Qiagen, Zymo, or even homogenization followed by etoh precip) will remove inhibitors. You may worry more about the degradation of nucleic acid especially if it was stored in ethanol for an extended period of time - you can check that on a Bioanalyzer.
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I have been able to use the Kraken2 pipeline for analysing the nanopore reads and derive a KronaPlot for metagenomics. Since KronaPlot also gives a list of reads from a sample that is associated with the species identified, I am able to find those reads from my sample fasta file. Now, when I nucleotide BLAST those reads in NCBI, they don't identify the same species that the Kraken2 pipeline has output. Also, if I try to assemble the reads to the species identified by Kraken2, they don't align.
What am I doing wrong here, or did I miss identifying some important concept?
I am using Standard Kraken2db (All bacteria, fungal, viral and human) available here
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Thank you for the input. I found that redoing the analysis with confidence scores in Kraken and then further analysis with Bracken brought in some consensus and better confidence in the final output.
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What is the best way of metagenomic analysis using multiple rDNA amplicons (e.g. multiple 18S and ITS for each sample)? What methodology would you use to reliably normalize and integrate the data from individual amplicons, regarding variable amplicon length between the taxons and variable libraries sizes? Can we employ Kraken or Bracken classifiers? Thank you in advance for any advice.
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So far, I found one paper dealing with that:
Yet the algorithm used here results in selecting just one best-discriminating amplicon for each taxon, if I understand it well... Does anybody have experience with this MVRSION approach?
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During writing a review, usually published articles are collected from the popular data source like PubMed, google scholar, Scopus etc.
My questions are
1. how we can confirm that all the articles that are published in a certain period (e.g.,2000 to 2020) are collected and considered in the sorting process(excluding and including criteria)?
2. When the articles are not in open access, then how can we minimize the challenges to understand the data for the metanalysis?
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For the first question, using multiple databases as you suggest usually help to minimize the risk of missing relevant studies. The risk of missing studies by published year not usually an issue, since published year tend to be well documented and indexed.
However, missing studies due to a narrowed scope while searching for literature is always potential risk. If you have an reasonable knowledge of the field you are planning to review, you might have a range of publications already prior to the reviewing process. If you can find all of these publications during your scoping process then your scope is acceptable. If some of these are missing, you might need to extend the scope further.
Another issue that is difficult to account for is the inclusion of journals/publications that are not indexed in the big databases.
For the second question, one option is to contact authors of these subscription-only publications and request a copy. If some publications are essential yet no access can be granted, the last option is to purchase the publication.
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Hello,
I recently received metagenomic 16S rRNA gene sequence data from a company, which includes both raw reads, and clean data with barcodes removed. My goal is to analyze these sequences and obtain information on the taxonomic diversity and abundance of the species present in the sample.
Since I use a Windows system and cannot utilize Mac or Linux, I would greatly appreciate guidance on how to proceed with this analysis. Are there any web server-based applications available that can assist with this task?
Furthermore, if there are any researchers or experts interested in this project, I would be grateful to explore potential collaborations. Please feel free to reach out to me if you are interested or have any recommendations.
Thank you in advance for your assistance.
Best regards
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SilvaNGS - simple and win-based. https://ngs.arb-silva.de/silvangs/ It is probably less flexible than all nice approaches mentioned above but it is quite useful for first look or for someone who needs an established reliable pipeline
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We did surveillance of ARGs. After getting results of metagenomics, suggest the appropriate way to explore and compile results
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Prodigal is a frequently used tool to find genes from contigs by a lot of metagenomic pipeline to software. 'Gene comparison', do you mean that you want to know the function of genes? In this step, you need a proper reference database and then annotate your sequences against the database (for example CARD above mentioned), using tools like blastp, diamond, Hmmer, eggNog mapper.
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I'm planning to conduct Metagenomic analyses on DNA extracted from soil using the ITS and 16S primers. However, I'm getting bands at 2k or 3k on the gel, even though my ratios and DNA concentration are within the acceptable range.
The 260/280 ratios are approximately 1.9 and 260/230 ratios of approximately 2 and DNA concentration measures around 250-300ng/ul.
I was expecting a thicker band above 10k. I'm concerned about the quality. Should I proceed with the metagenomic analyses or should I extract the DNA again modifying my method? Do I have too much smears? I use Dneasy Pro kit for soil extraction.
Info:
Primers: Crude DNA extracted from soil with Dneasy Qiagen PRO kit
Gel %: 1% gel
Ladder full name: Lambda DNA/HindIII Marker and 1kb plus
Time and Voltage: 30 mins at 80v and 1h at 80v
Sample Volume and concentration: 1 ul of 6x DNA Loading Dye and 5ul of DNA, 1A 1:1:4
Ladder conc.: 1 ul of 6x DNA Loading Dye and 5ul of Ladder and 1:1:4. 1Kb is 1:5
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The gel picture of DNA extracts looks smearing. It is not very surprising if the sample was bead processed fiercely and a bit long. The spectral parameter looks good.
With this DNA material, you can go further for PCR to get 16S or ITS fragment. The PCR products will used for amplicon sequences. If you would like to do short-gun metagenomic sequences for the genomic DNA, you can send to sequencing company, they will check the quality and quantity of your DNA extracts with good instruments, and contact you whether the samples are good or not for sequencing.
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what's the difference between gene abundance in metagenomics and expression value in metatranscriptomics
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Metagenomics measures gene abundance, which represents the presence of specific genes within a microbial community. Metagenomic sequencing identifies and quantifies genetic material, including microbial organisms' genes. Gene abundance reflects the community's potential functional capabilities and suggests genes contributing to specific biological functions or metabolic pathways. Metatranscriptomics, on the other hand, measures gene expression value, which represents the level of transcribed genes within the community. Expression values provide insights into the community's functional activity and genes being utilized under specific conditions or environmental factors.
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How do scientists use metagenomics and high-throughput sequencing technologies to study microbial communities and uncover novel microbial species and functions?
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Hevar Neaz This forum is not ChatGPT. Try to figure out the basic information yourself and then ask any remaining specific questions, which only experts in the field may be able to answer.
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AS the title. The fecal samples were stored in the -80 ℃ refrigerator for several years. Want to know if it is suitable for 16sRNA or metagenomic sequencing to analyze the gut microbiota.
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* The Mice stool samples can be stored in -80°C for up to 2 years without significant loss of microbial diversity or composition.
References:
Thanks
Samir
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Please suggest a website, API, or other solutions to sequence similarity searches on many (all available) metagenomic libraries without downloading the metagenomic reads or assemblies.
Thank you
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You can use NCBI for that. Use project in SRA explorer.
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I have some soil samples from wheat rhizosphere. Which physical parameters may I check for a metagenomic analysis? Will approximately 20 grams of soil be enough for all tests?
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Hi Mirza, for metagenomics analysis the required edaphic properties may vary based on your specific research question as also mentioned by Pankaj Kumar Singh . Physical parameters such as soil pH, soil moisture or soil water content, bulk density, texture, porosity, water holding capacity, aggregate stability, electric conductivity etc. may be investigated. Further, Soil nutrients in terms of C (organic and inorganic carbon, dissolved organic carbon, total carbon, labile and recalcitrant carbon), N (organic and inorganic, total nitrogen), Phosphorus etc. may be determined. I also suggest to analyze soil microbial biomass carbon to understand the variabilities in the metagenomic data better.
If you want help on how to understand the correlations of these parameters with the metagenomic data please check the following article:
Thanks and all the best in exploring your research.
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which method should be more succeful and realabel in idetifing Microbiota
Metataxonomics or the shutgun ?
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Microtaxonomy is the study of classifying and identifying microorganisms based on their genetic and phenotypic characteristics, such as morphology, biochemistry, and physiology. On the other hand, metagenomics is a field that involves the study of the genetic material recovered directly from environmental samples, including the DNA of microbial communities.
In terms of identifying microbiota, both metataxonomics and shotgun metagenomics can be successful and reliable, depending on the research question and the samples being analyzed. Metataxonomics typically involves amplifying and sequencing a particular gene, such as the 16S rRNA gene, which is commonly used to identify and classify bacterial species. Shotgun metagenomics, on the other hand, involves sequencing all the DNA present in a sample, allowing for a more comprehensive analysis of the microbial community. The choice between metataxonomics and shotgun metagenomics will depend on the specific goals of the study, the complexity of the microbial community being analyzed, and the available resources. For example, metataxonomics may be preferred if the goal is to identify specific bacterial species in a relatively simple microbial community. However, shotgun metagenomics may be more appropriate if the microbial community is complex, and a more comprehensive analysis is required.
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I am working on metagenomics datasets...I have six disease datasets...i need to find disease-specific genes and proteins for comparative analysis. I would like to know that, can we find out disease-specific genes and proteins with metagenome rather than metatranscriptome...thank you in advance..
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Yes you can find gene families by using HUMAnN (https://github.com/biobakery/humann). And then you can perform differential analyses say LDA using LEfSe (https://huttenhower.sph.harvard.edu/lefse/) to identify markers.
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How abundance calculation is done for the genes which are annotated by any reference database like MegaRes, contig file generated after de novo gene assembly is aligned to the database using Blast. Is the abundance referred to the number of contigs annotated as a specific gene or is it some other way??
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The abundance calculation for genes annotated by a reference database such as MegaRes depends on the specific approach used for gene quantification. In general, the most common method involves mapping the sequencing reads to a reference database and then counting the number of reads that map to each gene.
In your case, it sounds like you are using a de novo gene assembly approach to generate contigs, which are then aligned to the MegaRes database using BLAST. To quantify the abundance of each gene, you could count the number of contigs that align to each gene in the database. However, it is important to keep in mind that the number of contigs is not necessarily directly proportional to the expression level of a gene, as different genes may have different lengths and levels of expression.
A more accurate approach to quantifying gene expression would be to use tools such as RSEM, Kallisto, or Salmon, which use a statistical model to estimate the expression level of each gene based on the mapping of the sequencing reads. These tools take into account the differences in gene length and the potential for reads to map to multiple genes, which can improve the accuracy of the abundance estimation.
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Hello to all,
I need to perform a standard curve for metagenomic analysis with qPCR, of Treponema Denticola and Pseudoramibacter Alactolyticous, using the 16S RNA copies of my DNA.
As well I must perform a standard of a monk microbial community purchased by the Zymobiomics.
Since it is the very first time that I come across this topic I am sicking for help so I asked help from another colleague and she has helped me a lot BUT, in her calculations of 16S RNA copies and bacterial population she has used the guide of applied biosystems where the Molecular wight of DNA is reported to be 660 g/mole and according her calculations the DNA mass is equal to 9,13*10^20 bp/ng.
I asked the technical team of Zymo and they replied that I should use the following formula 6,022 x 10^23/10^9/650 which equals to 9,26462E+11 bp/ng. At this point I am totally stuck and I can not proceed with my calculations.
According to your experience could you please help me?? Should I consider as the correct molecular weight of the double stranded DNA the 650 or the 660???
Why I obtain 9,26462E+11 and my colleague 9,13*10^20??
Thank you
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Thank you so much for your reply.
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I want to know if I want to apply the metagenomics test routinely to my soil throughout planting cycles to diagnose and predict harmful pathogens that might affect crop health and overall yield. How often should I take a soil sample?
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Hello, soil microbial communities are complex and susceptible to change this emphasizes the importance of establishing a baseline for the study. Controls are needed to provide such a baseline for determining whether a change in the soil microbial community is due to the treatment and use. The tests at least need to be performed before and after the metagenomic study.
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My colleague and I are planning to do a culture-independent study on identifying specific bacteria in a river system. We just have some questions before we undertake this study.
1. If we happen to sample pathogenic bacteria, do we need to work in a BSL-2 laboratory?
2. What is the general procedure for trying to identify specific bacteria? Do we need to perform DNA extraction, cultivation, etc.? We are planning to perform 16S rRNA metagenomic analysis and are scouting sequencing centers around our country.
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Ciara Maria Ines Palma Del Rosario Look at work of Gyraite G, Katarzyte M, Schernewski G. First findings of potentially human pathogenic bacteria Vibrio in the south-eastern Baltic Sea coastal and transitional bathing waters. Marine pollution bulletin. 2019 Dec 1;149:110546.
It has most of important methods regarding identification pathogenic bacteria in water
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How to analyze LEfSe and interpret the result of soil microbes obtained through metagenomic high throughput sequencing
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Thanks Mr. Milan, satisfied with your reply.
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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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Is there a minimal sequence depth or length of the sequence read (>xxx bp) required to use Tax4Fun2 and PICRUSt2?
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Hello, collegues,
I'm trying to estimate the distribution of a certain kind of microorganism (eg Methanobacterium) in a certain environment (permafrost) from metagenomic data presented on various online services (NCBI, MG-RAST, https://microbeatlas.org). Such an analysis can be done on MG-RAST, but data are scarce. The service https://microbeatlas.org gives good data, but they do not correspond to the entire genus, but only to selected reference genomes. The situation is complicated by the fact that my computer is not very powerful and I cannot download 10,000 metagenomes and analyze them myself. Can you please tell me if it is possible to carry out such an analysis online, at least partially, with post-processing on a computer?
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Hello Vladimir,
I agree with Dr. Abhijeet. Working with 10000 genomes requires a lot of planning and very powerful servers.
However for smaller and more modest projects you could try working with cyverse servers, or with usegalaxy servers.
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I asked a similar question before but I'm here again. I'm working on urine samples to perform shotgun metagenomics. The biggest problem is that my A260/A280 is below 1.8 (about a third of the samples are below 1.0). I cannot redo the entire procedure since I ran out of raw sample. Is there any way for me to improve A260/A280?
Someone recommended zymo kit but doesn't zymo kit require raw sample? If not which zymo kit should I use?
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Its better to ask help from someone experienced in your lab, otherwise it will be just waste of time and resources.
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I work in the cancer research field and human disorders by using the bioinformatics approach. These projects contain the analysis of transcriptomic data such as microarray, RNA-seq analysis, TCGA, systems biology analysis, survival analysis and etc. also, the metagenomic analysis in microbiome fired are conducted. Those interested in participating in analyses and writing articles are invited to send their CV to the email below.
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How does your institute financially support the applicants?
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What would you suggest as the most efficient method for virus concentration in DNA extraction from soil for shotgun metagenomics assay? In a situation where you have soil and shoot samples for DNA extraction, targeted for metagenomics.
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There are a number of methods that can be used to concentrate viruses from soil samples for DNA extraction and shotgun metagenomics analysis. Some of the most commonly used methods include:
  1. Physical separation: Physical separation techniques, such as filtration or centrifugation, can be used to separate viruses from other contaminants in the soil sample. Filters with a small pore size (e.g. 0.2-0.45 microns) can be used to capture viruses, while larger particles such as bacteria and soil debris are retained. Centrifugation can also be used to separate viruses based on their size and density.
  2. Chemical lysis: Chemical lysis techniques involve the use of detergents or enzymes to break down cell walls and release the viral DNA from the viral particles. This can be combined with physical separation techniques to increase the efficiency of virus recovery.
  3. Enrichment culture: Enrichment culture involves the growth of viruses in the presence of specific host cells, which can be used to selectively enrich for viruses in the soil sample. This method can be combined with DNA extraction and metagenomics techniques to identify and characterize the viral communities present in the sample.
  4. Tangential flow filtration can be a useful method for virus concentration in DNA extraction, as it allows for the efficient separation of viral particles from other contaminants in the sample. This can be particularly useful for soil samples, which can contain a wide range of contaminants that can interfere with downstream analysis. By concentrating the viral particles using tangential flow filtration, it may be possible to improve the sensitivity and accuracy of DNA extraction and metagenomics techniques.
Overall, the most efficient method for virus concentration in DNA extraction from soil will depend on the specific goals of your study and the resources available to you.
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I have done 16s metagenomic analysis (16S rRNA gene targeted amplicon data )for soil samples. I have also characterized my sample for its geochemical parameters. I want to study ordination between the two data but I don't know what or which value to input from the metagenomic sequence results. In papers, they have used OTU abundance (Picture attached and the article too).
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Input all the OTU. I used excel to calculated the Relative Read Abundance.
I think you need a file with all the OTU (columns) and samples (rows). You also need another file: first column with all the samples' name and a second column with the characterization of the geochemical parameters for each sample. The NMDS plot will show points (every sample) and a centroid (mean value), and there will be as many centroids as geochemical parameters were characterized.
I used TXT files for the process.
I hope I helped you!
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The results of metagenomic analysis are a large amount of data, please tell me what is the minimum percentage value that is significant (0.1%, 0.2%, 0.3%....) at the level of phylum, class, order, family, genus?
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Oksana Kisil You should look at dinamic changes of different taxons through the season (OK, permafrost is not a case) and on taxons differentiating locations or soil levels. Even low frequency taxons (0.1-0.2%) can be important for certain biological processes.
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I'm a grad student working on metagenomics and I ran into some issues with the samples. I collected urine samples and extracted DNA using DNeasy Blood & Tissue kit. I used NanoDrop to measure DNA concentration and ran into different issues. The problem is that the A260/280 level is too low (not to mention the contamination) and I don't know how to increase the purity level. I don't think I can collect the samples again, or at least it will take a while before I can do that again. Is there a way or a kit I can use to increase the purity level of my DNA extracts without significantly lowering DNA concentration?
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Péter Gyarmati I will try again with Qubit, but regardless of contaminations, most samples have purification level that does not meet the requirement. I may have to alter the sequencing method. Thank you for the recommendations.
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Hi all,
we would like to perform metagenomics on plant tissue as well as modern soil samples. We are not experienced with these analyses neither on plant material nor on modern soil. Has anyone recommendations for sequencing depths or tips how to choose the appropriate sequencing?
Thank you very much in advance!
Cheers,
Barbara
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I would highly recommend to discuss the topic with your sequencing facility. They will understand the aim and project and can suggest the best way. Or if what you are trying to do is the best way or not.
There are many things/information missing in your question missing without which no one can suggest any logical solution.
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I'm using Kraken2 to generate a custom database to run a shotgun metagenomics (microbiome) dataset against for associated host removal (the custom database is the host). The database builds fine, but the "--unclassifed-out" .fastq files have "x"s added to them (perhaps instead of Ns) and this is not readable in my downstream applications with qiita/qiime2. Why is this happening? I can't figure it out. Interestingly, I have done this procedure before and have not had this problem. Any thoughts as to what is going on? The output in my text editor looks like this (note the "x"s in the sequence):
FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF,,F:,::,,,:,FF,,:,,::FF,FF,FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF
@A00223:522:HW3NCDSXY:1:1101:8992:1000 1:N:0:GTGCACGA+GCCTATCA
AGTGCACCTCAACCCTATGTATTGTGGACCTATACCAGTCCTTATAGAATGGCAGACTGTACCTCACTCAAxCCTATGTACxGAGATCGGAAGAGCACACGTCTGAACTCCAGTCACGTGCACGAATCTCGxxTxxCxTCxTxTxxTTxxA
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This can help you
awk '/@/{ n=NR+1 } NR==n{ gsub(/x/, "N") }1' input.fq > output.fq
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Hi,
I got the shotgun sequencing data of my samples and I ran RGI for my samples to check the ARGs present in my samples using CARD database. Now I want to calculate the abundance of ARGs. May I request if I can get any help/guidance for doing the same?
Regards
Yasir
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Hi Dr. Connor!
I used RGI on assembled reads (min length of contigs was >200bp).
Awaiting your response.
Thanks and regards
Yasir
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I did DNA extraction using Power soil DNA extraction >> the yield was very low with high level of inhibitors.
I checked the publications and I found a recommendation to use one hour incubation in tissue lysis buffer and Proteinase K from Qiagen’s DNeasy Blood and Tissue kit then I complete with power soil kit however I don't know how to do this step and the amount of the enzyme I should use?
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Hello use membrane filtration method for your ground water.
Use 0.45 um filters to filtrate water if your water highly dirty first use paper filter or mechanical filter than perform membrane filtration than use pure sterile water add to filter to wash and remove all inhibitors. the amount of filtrated water depends from content of microorganisms in initial sample if it fro 10-to100 CFU/ml the 100ml is quite enough. if more you can reduce the volume. By this way you can have pure microorganisms without any inhibitors. Than you can use any method for extraction of DNA from microorganisms. For example the benzyl chloride method for DNA extraction highly recommended.
Good luck.
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I am having problem with 16S amplification on colon content DNA from DSS treated group. I have found that DSS is a polymerase inhibitors and tried to purify DNA with LICL and Glycogen-ethanol precipitation. I have also tried to dilute my stock DNA before PCR. However, there is no successful 16S amplification. I have attached a gel electrophoresis result ( tapestation report) on PCR product of my samples and E.coli as control for your reference. Only control showed 200bp band but all my samples showed no amplification. Any suggestion would be greatly appreciated.
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Hello all,
Thank you so much for your answer. Lately I have tried DNeasy PowerClean Pro Cleanup Kit for an additional clean up process of DNA samples and ran PCR. I think I saw some bands in the region of 200-300bp.
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Dear all,
I am looking for a user-friendly pipeline for metagenomics analysis using COI (Cytochrome oxidase I) as marker. I have tried some of them based on python and computed by docker but is not enough clear to be used with students. Could anyone recommend me any alternative?
Thank you in advance.
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The link posted above is useless and it does not relate what was asked in the question.
Try:
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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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You can contact me if you still need help with tax4fun2
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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 , Simon 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 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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"Comparative studies on the extraction of metagenomic DNA from various soil and sediment samples of Jammu and Kashmir region in prospect for novel biocatalysts" by R singh.
This is perhaps the best protocol that have yielded me excellent results.
The methods of Zhou et al. (1996), Volossiouk et al. (1995), Tsai and Olson (1991), Siddhapura et al. (2010), Verma and Satyanarayana (2011) are very helpful too.
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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 am looking for future collaborators in India working in the field of microbiome and metagenomics, with focus on antimicrobial resistance. Any suggestions?
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Interested in gut resistome study
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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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If your outputs are from qiime2, you can easily extract the feature table in .biom format and extract the taxonomic information and merge the two objects. From that point you can just create a phyloseq object and use it for the network.
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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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I am using STAMP software to analyze 16S metagenomic data. Basically I have two experimental replicates for six different experiments. The first three experiments were performed in a specific condition and the remaining three in a second condition. It is therefore a “two groups experiments”. I am checking differences in metagenomic composistion between the two conditions and I prepared a tab-separated file for stamp software. The software works correctly (both with sample files and with files containing only two columns of data) but do not recognize my “tab separated” file.
I have attached a small file with the first rows of data. Is there something wrong in this file? Is it possible to obtain a sample file for a “two groups” experiment?
Thank you
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Thanks a lot for your answer. It worked for me :)
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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?