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Next Generation Sequencing - Science method

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Hello everyone
Does anybody know a free accessible workshop on how to do and analyse the NGS result?
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Hi Vahid
You can find smth interesting for you here:
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I am searching for ready available kit or panel solution from any reputed manufacturer for diagnosis coagulation genes by NGS method. We have Genexus and S5 machine from thermo scientific and Novaseq 6000 from Illumina.
Expected gene covered : F10, F11, F12, F13A1, F13B, F2, F5, F7, F8, F9, FGA, FGB, FGG, GGCX, GP1BA, KLKB1, KNG1, LMAN1, MCFD2, PLG, SERPINE1, SERPINF2, VKORC1, VWF
Please suggest compatible panels if anyone is working or have information.
Thank you.
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Hi Jigarkumar
you can try AmpliSeq for Illumina Hematology Research Panel (394 genes)
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I have extracted DNA from human stool by using The QIAamp Power Fecal Pro DNA Kit.
However, I found that most of my purity reading A260/230 were very low. I plan to send my extracted DNA for NGS. Does anyone have any suggestion on how to improve the reading.
Thank you so much.
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Nurul
Did you use right blank/reference? Sorry for asking!
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Need a help! Basically if someone is focusing on liquid biopsy and next generation sequencing.
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Yes
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The sample was extracted by PAXgene kit, However, its measurements on nanodrop is very poor (report is attached). The current quality is not suitable to be applied for next generation sequencing. Are there possible means can be used to increase its quality?
Thanks in advance
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Hello, you can try to run clean up the sample by running through (new) column again, repeating the wash steps. This can potentially increase the purity, but you may lose yield.
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Hello, I got a question with the units of sequencing products. Most of the phylogenetic study that using ddRAD or other NGS method provided the data size of their analyzed dataset using the unit "loci" or "SNP". While for research using Sanger sequencing and PCR, they used "base pairs" or "nts". If I would like to compare the molecular data size between these researches, is there a transforming algorithms to do it? Or could I just simply use these number to compare (e.g. 1400 bps v.s. 7000 SNPs)? Thanks!
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Why do you want to "compare" the size of markers? I think the absolute size of bp is incomparable between a sequence and SNPs among genome, cause all nucleotides in a sequence are linked and not all of them are polymorphic; while SNPs are polymorphic loci scattered on different positions of a genome, which may be less linked to other SNPs. Also, sequence and SNP provide different aspects of evolutionary information, so I think comparing a single sequence to a RAD-seq data could not provide you some useful information
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Hi all,
I'm performing small RNA library for NGS illumina, and I wonder have you tired use SPRI beads to enrich for a small range of length of your library and how does that work?
My desired fragment size is between 175-185bp, I can chose to run a polyacrylamide gel and excise my desired length. But I'm curious, can I just use the SPRI beads to enrich for fragments of 175-185bp length?
Thanks!
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Hi,
We are considering purchasing a Bioanalyser to increase the accuracy of DNA quantification during library preparation for next generation sequencing. However I have heard that some laboratories now use a Tapestation instead.
Given that Tapestations are more expensive, I wondered if anybody had any advice regarding either of these machines and could offer their own recommendations.
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Both the Qubit and QPCR will give a valuable result. However, qPCR still remains the more reliable quantification result. Several kit works. For me..I used the illumina Infinium kit which is like a mastermind containing about 50 different gene. You can check the illumina website for the list of genes contained and if your gene of interest is among..bravo. Then your works goes faster. Used it o your QPCR Machine to check the QC of your sample. Then you wiĺl get a reliable quantification measurement
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Hello,
My group is attempting to decide whether NGS or RT-PCR would be the appropriate method for analysis.
We want to ensure expression of 5 genes is maintained in our two modified cell lines.
Both should express similarly, however one also produces a protein of choice (this is being confirmed via other testing)
We have 3 cells groups.
WT group
Modified 1 (no protein produced)
Modified 2 (protein produced)
Additionally, we don't necessarily want to quantify the level of expression just a confirmation that modified 1 and 2 express these 5 genes similarly and to a greater degree than WT.
Which method would be the most straightforward?
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RT-PCR would be my recommendation. 3 cell lines x 5 genes in triplicate is less than half a 96-well qRT-PCR plate. Preparing 3 libraries for NGS is most likely going to be more expensive, and would still require validation by RT-PCR.
I would only recommend using NGS if you are interested in looking at global changes in gene expression after your experimental manipulations.
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I am designing a custom NGS run and need to determine the sequence coverage. I am using the Illumina Sequence coverage calculator https://support.illumina.com/downloads/sequencing_coverage_calculator.html
How do I determine the genome/ region size?
Additional information:
Human gDNA will be used. I will have 4 amplicons about 250 bases each from 4 different genes.
Any help would be appreciated. Thanks, Nikhil.
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Thanks Luigi Marongiu but I still have not gotten my data yet. I should have worded better. I am just looking to determine the number of samples I will in my run, and for that I will need the genome size or region size.
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Hi everyone, does anyone here have experience extracting fungal DNA from mouse stool and sending it for next generation sequencing? I have continually run into a problem where I extract DNA from stool and submit it for fungal ITS1 sequencing and have gotten poor unusable data back (poor number of reads per sample). I use the qiagen powerfecal pro DNA kit to extract my DNA. Of note when I send the same samples for 16s bacterial sequencing the data looks fine. I ran a gel on my samples using an ITS1-2 primer including a positive control and do not get the expected ~300 bp band. Instead I get several larger bands (see attached). I have been told by our sequencing core that these larger bands would typically be ignored or not get through the flow cell which is why I never get any fungal sequences back. Has anyone run into a problem like this and how did you overcome it?
Thanks!
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HI,
you might try power fecal Pro kit as the extraction of fungal DNA works a lot better. In addition the amount of fungal DNA will be much lower than the amount of bacterial DNA. Further I would check the primer design, annealing temp and general reaction conditions again. Let me know (DM) if you need more background
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I would like to do next generation sequencing on cells sorted based on an intracellular stain. Is there a best practice for how to fix the cells such that my sequencing run is not compromise?
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Did you ever get this to work? I have the same problem and was looking for an answer. I need to fix my cells for FACS but then need to extract the genomic DNA after for a PCR. Thanks!
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I'm looking for primers that target all (or the majority of) viruses and nothing else for PCR. I believe there are primers for some virus families but I haven't found any that would be called universal viral primers. Thanks.
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Hi Ali,
That is impossible because every virus has its own genome.
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I will sequence the micro RNA isolated from Arabidopsis and want to detect the presence (if any) of small RNA which are nor originated from Arabidopsis genome. Please provide me your valuable suggestions for this study. Thanks
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If your are using STAR to align your miRNA you can use the --outSAMunmapped or --outReadsunmapped options to get unmapped reads
Here's the manual for further information:
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Does anyone know a good way of predicting E. coli K-antigen identity from NGS data? It seems like there are lots of options for O and H antigens (e.g. the excellent ECTyper) but none for the K antigen. I'm hoping to type some strains to better understand the host ranges of a phage collection. Any help gratefully received!
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If you have assembled genomes, this should be easily done. The most simple way I could think of right now is similarity based analysis, for example, BLAST.
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Hello,
I am looking for a lab that can process insect DNA samples for me. More precisely, I would like to do hyRAD on my samples (they are not good enough for ddRAD). I am struggling to find one.
Thank you!
Sophie
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Tyler Chafin thank you very much !
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What NGS analysis approaches do you use? Do you use bioinformations? Do you have software solution to do your own analysis? What do you do?
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I recommend to ask question which is logical or make some sense.
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I am doing targeted sequencing on colitis-associated cancer sample, and found some mutations. So I need to validate 3 synonymous mutation with additional samples. Unfortunately, samples are limited and out of 6 samples, I only found the mutation in 1 sample. Is it strong enough? Or do i need to do further validation with sanger? I am also planning to do functional study of that mutation via in vitro.
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If you only have the empty dna sample tube left of your original sample then whole genome amplification will generate large amounts of dna from the small amount coating the bottom of the tube and then you can amplify and sequence. If that is too expensive then just add 10ul of water to the sample that you have left and pcr amplify but add 4 more cycles than usual and you should get enough amplimer to sequence or restriction digest or whatever method that you want to try next
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Hey guys, I was just wondering whether there are any public clusters for evaluation of NGS data like ? Thanks in advance for your comments!
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I have the best experience with the Galaxy cluster of bioinformatics tools https://usegalaxy.eu/ (it has a cutting-edge workflow for nearly all types of sequencing (DNA, RNA, long reads/short reads, metagenomics, epigenomics,...)
Hope this helps
Martin
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Has anyone had luck with NGS library prep for DNA/RNA samples that had low A260/230 ratio due to guanidine thiocyanate? Our samples are made using the AllPrep Qiagen kit without Trizol (used other lysis buffer) and phenol precipitation does not help much. NB, phenol is not the issue.
Thanks.
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If your A260/230 values are 0.8-1.7, do a 1.8X cleanup with RNAXp beads to remove salts. Do a Nanodrop after and your A260/230 value should now be higher. Start with minimum 1000ng RNA -post cleanup RNA will be about 55%-70% (i.e. 550ng-700ng) depending on how much salt contamination is present in starting sample. Resulting RNA can be used for NGS prep.
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NGS has become an integral part of biomedical research, and with the ever-increasing quantity of sequencing data, as cancer biology researchers, it has become increasingly important for us to analyze this data and determine critical gene signatures. However, given the novelty and the overwhelming expansion of resources and online tools in this field, as beginners, it becomes challenging to find suitable resources to learn how to analyze this data. Can anyone with expertise in this field, kindly guide me on this and help me find the right materials, to begin with?
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Before moving on to NGS data analysis, first try to understand what NGS and its different types are.
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I am analyzing my small RNA seq data on Galaxy, I need to remove all rRNA reads from my data. I downloaded a rRNA reference genome for mice and tried mapping with Bowtie2, but it kept failing. Apparently my rRNA reference file had multiple duplicate names. Where can I get a rRNA reference genome from?
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Hi Sanat Bhadsavle , you can download the entire SILVA LSU/SSU rRNA Database (LSU= large subunit rRNA, SSU= small subunit rRNA). For practical reasons, just merge both LSU/SSU FASTA files. Now you can (additionally) isolate all entries that belong to mice. The SILVA entries contain the whole taxonomy in the name.
The next step, map your RNA-Seq data against our SILVA database, I would recommend hisat2 over bowtie2. The resulting SAM or BAM (mapping) file can be filtered to extract all entries that do not map to your reference.
samtools view -f 4 mapping.bam > unmapped.sam
will store all unmapped reads in the unnmapped.sam file
Cheers
Roman
See here for more information:
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Hello!
I isolated some T-cells with some very interesting TCRs from primary cultures. I sent them to Genewiz to get chromium single cell TCR sequencing done, however the sample viability was super low. I sent them 8 more vials so that they could do a dead cell removal and then isolate the live population and perform single cell sequencing on the remaining cells. The sequencing results show that whatever is left over after DCR is most likely another contaminant cell type, not a TCR. I now only have one vial left, so whatever I choose to do next is very critical and essentially has to work the first try.
At this point I dont care about chain pairing, I can piece that back together afterwards by trial and error, I just want to get some data from these cells. I was wondering if anyone knows if I can thaw my cells directly into RNA later and then do either normal NGS or another single cell sequencing method to get any info on the TCR sequences? Should I just amplify the TCR regions on thawing with some kind of primer pool and then send that for NGS? In general, what's the most robust process for getting out TCR information from low viability samples?
Some other notes:
1. I didnt personally do the T cell isolation but my thinking is they were pretty much exhausted at the time of freezing which is why we have viability issues on thawing
2. They were frozen in 10% glycerol + 10% FBS in a Mr Frosty at -80C and then maintained in LN2 and shipped on dry ice.
3. Observed viability is ~30% on thawing however this could just be the contaminant cell population....
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Definitely a fair assessment, Ive made other samples that have similar properties as this, but none of the other samples Ive generated have responded with as much vigor as this sample.
Definitely will invest in generating another panel of T-cells but from what I can tell so far, this sample had a particularly rare phenotype that i may or may not see again in a relatively limited panel size. every once in a while I remember I have this last vial and wonder if I can do anything with it, in the end its always for the birds...
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Hello, I have done WGS of my bacterial strains and got some preprocessed Illumina sequencing files in .fna format. It has a format like this
>1 length=400016 depth=0.86x the sequence
>2 length=323455 depth=1.00x and so on to >102
I want to know how to deal with this .fna file and which analysis to run on it.
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Abhijeet Singh with a big position and seat comes big responsibilities. It would have been great if you provide some guidance rather than demeaning others.
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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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- There was no measures taken before storing
- Precious samples; repeating sample acquisition won't be available
- Later NGS application
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Freezing whole blood samples is not recommended as it causes cell damage. One freeze-thaw cycle could be tolerated, if you thaw the samples at 15-30 degree C. Freeze-thaw cycles generally render blood samples unusable for molecular studies as freeze-thaw can lyse cells and these lysed cells could release nucleases. It would have been better if you would have isolated PBMCs from blood within 6-8 hours after blood withdrawal and frozen the cells instead of freezing whole blood.
PBMCs are isolated by density gradient centrifugation, as different components of blood have different densities and can be separated accordingly. The density gradient medium most used is Ficoll or Ficoll-Paque.
To preserve PBMCs at ultra-low temperatures in liquid nitrogen, PBMCs at 5-10 x 10^6 cells/mL are resuspended in freezing medium containing 10% DMSO + 10%FBS + 80%RPMI medium, and are placed inside a freezing container (i.e. Mr. Frosty) at -80°C overnight to allow gradual and even cooling. The following day, samples can be moved to a liquid nitrogen tank for long-term storage. You could later thaw these cells at 37 degree C for further analysis.
Best.
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I read several papers where researchers use several strains of the same species for analysis of recombination or selection pressure however there are few papers in which researchers use the multiple species belonging to one 'Genus', not the multiple strains that belong to one 'Species'. What difference is expected in the result and how it can be interpreted.
I want to know how my pathogenic organism 'Xyz abcde' is evolved (recombination and selection pressure). 5 different strains of 'Xyz abcde' is sequenced while 9 organisms in Genus 'Xyz' is sequenced.
Which dataset I should use to proceed and why? How it will make difference in the analysis?
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The answer is found in this study:
J Virol. 2006 Nov; 80(22): 11124–11140.
Published online 2006 Sep 6. doi: 10.1128/JVI.01076-06
PMCID: PMC1642140
PMID: 16956935
Recombination and Selection in the Evolution of Picornaviruses and Other Mammalian Positive-Stranded RNA Viruses
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A splice site mutation in human RNA at a VAF of ~50% using NGS was detected. When I use the same aliquot of RNA (for contaminating genomic DNA) in Sanger sequencing using primers that amplify this intronic and exon region, the mutation is undetectable. It has been confirmed that there has been no mix-up on the source of RNA and it has been repeated NGS which confirmed this mutation again and Sanger analysis on cDNA has not produced different results. Looking for suggestions for what might be occurring thanks.
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One possibility when Sanger sequencing gives different results is that the change detected is on the same chromosome as a polymorphism which lies under the 3' end of either the pcr primer or the sequencing primer. This means that only one chromosome is being amplified so the pcr is hemizygous and the chromosome that has the change has not amplified or sequenced. One solution is to move the pcr and sequencing primers to different positions not including the original primer positions. If this is human then check snpdb but even if it is not in the database it is worth moving the primers in case you have found a rare polymorphism that is interfering with amplification or sequencing
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Dear all, I am carrying out a project related to the identification of the pathogens (parasites, fungi, bacteria, virus). I have a very large dataset obtained after doing Shotgun Metagenomic Sequencing on multiple faecal samples of animals. All bioinformatic analyses were performed by a company. For identifiation, they blasted all predicted protein sequences with more than 30 amino acids against the reference proteome of UniProt. Then, they only removed those hits with homology below 30% and the final set of UniProt hits and their relative information (including gene name, protein name, GO annotation, pathway, and taxonomic lineage) was sent to us.
After checking the results for the taxonomic annotation, many innacurate species have appeared, so the company suggested to apply filters on the % identity (70%), query coverage (70%) and subject coverage (40%). Nevertheless, they said there are no references to justify these values, and that it is up to us to decide. Based on our previous knowledge on building phylogenetic trees after PCR + Sanger sequencing, we consider that 95% identity would be better, but we do not really know if that applies to this type of research too. Could somebody please enlighten us on which would be the right balance between identity, query coverage, and subject coverage? We do know that it is a trade-off and that many reads will be lost after the filtering, so we want to maximise what we keep whilst still being able to say that what appears on the obtained dataset is true. Thank you very much in advance for your help.
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  • % identity (70%), query coverage (70%) and subject coverage (40%).
>> This is good enough
But I wonder, if you have metagenomics sequence data, you can assemble and bin the data. In this way, you you don't need to use blast or any other analysis manually. The taxonomy will depend on the completeness and contamination on your MAGs/Bins.
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Hello all,
I´m trying to isolate DNA from streptomyces isolate using Kit (GenElute Bacterial Genomic DNA Kit), but I always get sheared/ smeared DNA (see attached figure - 1% agarose gel, 80V, 45min, fresh TAE buffer, 6µl of DNA on gel).
I isolated carefully without vortexing, from fresh culture. For elution I used sterile water.
I need good quality DNA for NGS.
Do you have any suggestion for protocol improvement or recommendation for some other kit please?
Thank you for answers.
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  1. Using DNA direct for gel without any PCR or anything will always give you smear, unless you are using long/high-MW DNA extraction protocol. Thus, the gel above does not make much logic.
  2. DNA shear depends on the cell lysis step and if your protocol incorporate physical and vigorous lysis, the smear is unavoidable.
  3. NGS does not make any sense if not used in appropriate context. And mostly all PCR based and shot-gun sequencing method might work on most DNA extracts unless the quality (bioanalyser/tapestation) is very bad.
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Commercial tools are also fine.
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Before answering the question, I would like to ask you few questions related to the topic
  1. Do you have knowledge and understanding of NGS and how it is literally translated to type/platform in a practical sense
  2. Do you know what an antibody is based on its structural composition?
  3. Do you have knowledge and understanding of what assembly and annotations are and their purpose?
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We are trying to look into mutational landscape of ctdna in serum/plasma on NGS . Any recommendations on kit for isolation. Does isolation kits have any impact on ctdna mutation detection?
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Thank you @ Yangyi Chen. The kits compares the urine cfDNA. We are using serum for cfDNA mutation. Is there will be difference in fragmentation of DNA and quantity in serum samples as compared to Urine? In our scenario 4.0 ml serum collection is not feasible from cancer patients, as the reference study used 4.0 ml of urine as starting material. Increasing the input amount will definitely increases the DNA yield.
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I have treated some of my plasmid samples with RNase A to get rid of their RNA contamination.
I'm going to send the samples for sequencing afterward.
Is it necessary to clean up my samples after RNase treatment?
Does RNase A make any problem in the DNA sequencing process?
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Yes, you should remove the RNase from your sample.
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Hi. Has anyone had any experience with Nextera Flex/Illumina DNA prep with enrichment on FFPE samples?
I'm having some difficulties in obtaining a reasonable quality of sequencing using this protocol.
The problem is obviously related to the degraded input material I'm working with. I spoke with some colleagues who perform enrichment-based sequencing on FFPE extracted DNA, however, none of them was using DNA prep/Nextera flex library preparation pathway.
This library preparation method is extremely convenient, but I'm having doubts if it's optimal for every type of source DNA.
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Muhammad Shakeel - thanks for the suggestion, I didn't think about reducing the tagmentation time. I thought that this parameter was significant with first version of Nextera, and that in Flex/DNA prep it did not matter.
I'm afraid that I might be forced to look for end-repair method instead of nextera, which is so convenient. But the quality of input material is something that I have no control of.
I also considered the FFPE repair kits - is it worth a shot? There were publications proving that it greatly improves the results of microarray analyses. I'm not sure if it will do the job in case of NGS.
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I have done WGS of my three patients samples. And I have done detailed bioinformatics too. So can I publish these data as an individual paper in a good journal?
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This will depend on the question you are trying to answer. For NGS data, it is important that the results are statistically sound. If you are looking for differences in the genome or gene expression between your patients and control group, that should have good statistical support. f you are doing differential expression analysis of genes, make sure you have done so using established differential expression analysis tools, for example.
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The RNA sample will be used in NGS and I am basically searching for protocol that doesn't involve column purification.
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You can use heat inactivation of DNase. Heat your samples for 5-15 min at 75°C.
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I need the information about the companies in India offering services of environmental DNA for any organism. Please add website links.
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Hi Dinakarsami, I'd be happy to help you with metagenomics and metabarcoding analysis. Pl. drop your message.
Thiru
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I extracted DNA from ffpe tissue, measuring OD by nanodrop, I find bad DNA quality: 260/230 ratio is about 0,3 and 260/280 ration is about 1,3.
Is it suitabale for NGS or i should repeat the extraction
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Hello,
The quality of DNA for NGS is important. Sequencing low-quality nucleic acid will result in impaired performance and failed run.
The DNA should be intact and non-sheared without any large smears which you should check on agarose gel. There should be no RNA contamination as it can artificially inflate the amount of DNA present in the sample.
The purity of DNA is also important. You need to check the purity using Nano Drop spectrophotometer. The ratio
A260/280= 1.8 implies that the sample has high amount of DNA. This ratio is most appropriate for NGS analysis.
A260/280 = 2.0 implies that the sample has high amount of RNA.
A260/280 lower than 1.8 indicate protein contamination.
The ratio A260/230 should be greater than 2.0. This indicates very few contaminants like phenol, EDTA, salts and carbohydrates are present in the sample. This would be most suitable for NGS.
A260/230 less than 1.5 indicates large amounts of contaminants which can negatively affect many kinds of enzymatic reactions that are part of the NGS workflow.
Next, the DNA should be of high concentration. For this, it is always better to use fluorometric methods to quantify DNA like the Qubit or Pico green method as these methods only allow for DNA to be quantified.
So, your DNA is not suitable for NGS and you need to repeat the extraction.
Good Luck.
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My background is Biotechnology and for my PhD research Bioinformatics (NGS Analysis) which is necessary not easy task.
now days I am learning Linux Kernel (Operating system), which is hard to understand.
as I have MacBook Air, now the question is that can I do All the NGS analysis using MacBook as Mac have Terminal command.
rather learning Linux kernel, because for Linux I need to buy another Machine/ time to learn all the necessary commands.
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Ubuntu
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Hello...
I want to do NGS for my samples. I sent the samples to the company - they passed the bioanalyzer QC (which means the RNA conc. is enough) but they didnt pass the library QC. what could become the main issue during the process? Thankyou...
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hello Dr. Muhammad Shakeel and Frederic Lepretre . thankyou for the explanation. Actually I don't know the exact protocol that the company is using. My RIN was not that good, but the other sample with the same RIN were pass the library QC. that's why i'm just wondering what could made the difference :)
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Dear All,
In my lab, we have performed whole-exome sequencing of 10 patients to see if we found any germline variations associated with prostate cancer.
I am new to projects that use sequencing and am a little lost on how to analyze these results.
Can anyone suggest to me an app, approach, or pipeline to analyze these results?
I have my data in fastq files and understand a little bit of R.
Thanks a lot
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Thank you all,
I will use the tips you have given me and try to analyze my data!
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Kindly share your suggestions please.
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As I'm in Iran I could not suggest you a laptop with specific model number but here is my opinion on how to choose a workstation laptop for bioinformatics:
- first, everything is about your CPU, choose best one. As I now Intel core-i7 is essential, do not go for AMD. In case of core-i7 please choose 10 or 11 generation and also do not go for U models (they are low voltage and could not provide enough speed), H models are best options for NGS and bioinformatics. My suggestion is intel i7-11800H, it provides you 8 cores and 16 threads.
- Do not spend extra money for GPU if you do not have a plan for machine learning and deep learning. There are few programs which could use potential of GPU.
- If you can go for 32 or 64 gb ram. some programs need minimum 32 gb ram. But in most cases 16 gb is enough.
- In case of Storage, I think you need both HDD and SSD. HDD is good option for storing large files like fastqs, but it could not provide you enough speed, also HDD are cheep and I think you could get 2TB for a laptop. 500 Gb SSD is enough for your primary partition, and also m2 SDD is better than sata SSD, if it is possible please choose m2 types.
- and final point, heat pipes and fans, buy a laptop with minimum 2 exhaust fans and more heat pips, you need to check some YouTube channels to get information about this part, search for disassembly of a laptop.
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We would like to perform some amplicon sequencing. Paired-end reads 2x300 or 2x250 bp on miseq system. We are looking for a reliable, reasonably priced and fast sequencing service. Our purpose is to get at least 100 k reads per amplicon.
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Eminent Biosciences. Email us your samples details and objective of your study anuraj@eminentbio.com
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Hello,
I have some cleaned degradome-seq files, FASTA format, provided by a company. I found out the length of reads in FASTA files are variable between 45-47nt. I assumed they might contain adapter remnants, so I used Trimmomatic "java -jar trimmomatic-0.39.jar SE -phred33 X1-clean.fq.gz outpute.fq.gz ILLUMINACLIP:TruSeq3-SE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:15". But, all reads were removed. Could the length of degradome-seq reads be more than 25nt? The attached image shows the quality of raw data.
Thank you.
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In degradome-seq experiments, the shorter fragment length (e.g., 20nt) poses difficulty in distinguishing between the members of the same target gene family, so, larger fragment length (25 nt or higher) is recommended.
For the removal of the adaptor, I presume that the company has provided data after adaptors removal. That's why you have variable reads length. Nevertheless, you should ask them to verify.
The quality of reads sounds pretty good. You got all the reads removed in the output after trimmomatic, might be change in parameters solve the issue. For example, in ILLUMINACLIP:TruSeq3-SE.fa:2:30:10, set the value 10 to 20 and make sure TruSeq3-SE.fa file exists there and contains the adaptors sequence. In SLIDINGWINDOW:4:15, set 15 to 10 etc.
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I want to run geneflow estimate through Migrate-n but I do not know how to convert the NGS data into the correct formation.
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What's the specific format of your data (Genpop, Arlequin, VCF, nexus, phylip)?
Or is it still "raw" (probably in fastq or fastq.gz)?
Have you done some reference-based or de-novo assembly and post-filtering?
If yes, a tool like PGDSpider surely will help you (http://www.cmpg.unibe.ch/software/PGDSpider/)
If not, the pipeline is a little bit longer. In a nutshell, something like quality filtering/adapter removal - assembly - loci filtering (HW, MAF, missing data, outliers...) - clustering. After that, you'll probably get a .vcf file, which can be used as input in PGDSpider to get the Migrate file.
Regards!
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I am working on cell culture medium, using Ultracentrifuge to collect EVs, and check for size and concentration with NTA.
Is there a concentration (particle/ml) for a miRNA NGS analysis?
There are few articles suggest, after Trizol and Nanodrop checking, some say they put 10ng RNA but some say they put 100ng RNA?
Does any one has an experience on this?
I would appreciate some insight, thanks so much.
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Of course, you can also directly choose the exosome high-throughput sequencing service. Creative Biostructure offers a complete exosome workflow solution to solve nucleic acids profile of exosomes, from fast and efficient RNA isolation to exosome RNA sequencing.
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I am working with a parasitic nematode. We performed a differential expression analysis based on a reference transcriptome and found some interesting genes. Now, I want to look at the alignment of these interesting genes. I think that should be stored in the BAM files that originated after the mapping. How to extract only the alignments (or mapping) for these genes?. I have searched for tools, but they suggest using an annotation file to look for the genes according to the coordinates. However, all I have is reference transcriptome in fasta format.
Thanks for any suggestion!!
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Dear all
Which NGS method would be most suitable to achieve the following objectives in plant sample
• Identifying all the genes associated with the biosynthesis of a particular metabolite.
• To locate the chromosome regions associated with the biosynthesis of the same metabolite.
Regards
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Maybe Illumina x64 or varieties.
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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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If the results of DNA sequencing via NGS panel through Ion torrent , are showing variant allele frequencies of the studied genes around 11-14 % on IGV in many patients of the studied cohort, instead of the expected 50% in a dominant disorder. Could we consider this variants to be real or this is probably an artifact ?
N.B Samples are tissue ( parafin sections ), so could this be a sampling issue ?
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Hello,
Assuming you are looking for germline variants, you would generally (hypothethically) expect heterozygote variants to be 40-60% VAF, with homizygote 90-100% VAF (though real life distributions of VAF may deviate from this especially with large panels / exome data). You said your tissue is parafin, this is n ot a somatic analysis right? Because with somatic analysis the autosomal context is different, in there a somatic gain-of-function variant might exist in 10-20% VAFs (i.e. EGFR variants).
You could get such low VAFs as you are stating with mosaism as per: https://www.nature.com/articles/gim2017114/tables/1
However you should be careful that large amount of false positive variants may also exist in these VAF ranges as per:
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is it possible to submit or it require other editing or software to get accession number give a suggestion or help me to submit the sequences.
Thanks and regards
Ashwini M
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Hi Ashwini,
You can submit raw fastq sequences without any processing or editing. You need to create an account and choose the type of sequence based on your study. If it is whole genome, then choose genome, if 16s metagenomics then choose SRA etc. The relevant page will open and you will be guided step by step towards submission. Follow this link: https://submit.ncbi.nlm.nih.gov/
I hope it is helpful
Good Luck
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Next Generation Sequencing is a quantitative specialized technology that allows the analysis of genes through parallel sequencing of thousands to millions of DNA molecules in relatively short period of time with high-throughput, higher speed, sensitivity, reduced cost, and permitting a discrete discrimination between homozygous, heterozygous and subclonal events based on the number of DNA molecules supporting each variant (allele burden).
We are searching for the most effective technique for analyse Human Leukocyte antigens types
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Next Generation sequencing is a method for Human leukocyte antigen (HLA) typing.
It is use to match patients and donors for bone marrow or cord blood transplants.
As a close match between a donor’s and a patient’s HLA markers is essential for a successful transplant outcome.
HLA typing or matching promotes the growth and development of new healthy blood cells (a process called engraftment) and reduces the risk of a post-transplant complication called graft-versus-host (GVHD) disease.
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I wanted to know what kind of studies like pipelines, R code, Python code, and software can be used to perform Next-generation sequencing (NGS) specifically for HLA typing. What kind of studies can be performed on HLA data?
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It is a very particular theme. I supose to look into R or python first
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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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I have installed the mixcr file in the Home PATH of the Ubuntu from the respective GitHub and tried to set the mixcr directory as an environment variable by using the "PATH=$Home/<directory name>:$PATH". Though the above command did not show any error but am unable to get the access of mixcr function and instead it's showing "Command 'mixcr' not found", so is there any other method to set environment variables?
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Thank you so much
David Farringdon Spencer
, I will try according to this ..
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Variant genomes may share quite similar sequences, when I make the denovo assembly, only a few contigs are generated (sometimes the variants should contain a large diversity, e.g. HIV). Normally people use SGA for this purpose, want to know how to achieve the same goal using NGS short reads, single genome sequencing such as nanopore should work.
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For species with very small genomes, eg. bacteria, virus, you can simply use TGS(both Pacbio and Nanopore sequencing) to solve this problems. It's not expensive. But, if you want to use NGS data, you need to choose the right assemblers. Most of the NGS data assemblers are based on debugin graph. Once your samples are complex, they might not work well. But referenced guided genome assembly is another thing. If you want to do genome assembly of species with finished genomes using NGS data, you can try this method.
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Is anyone using the same DNA extraction kit for faecal, cecal and oral mouse samples? Please share your experience about the yield, use in downstream analysis such as NGS etc.? I really appreciate any help you can provide.
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Different kits are more or less similar in there basics for the DNA extraction. Same kit have different efficiency/performance with even samples of same type.
Thus, same kit can be used for different sample types, however, there must be some sort of optimization needed based on the sample properties.
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Hello,
I recently performed a sequencing run with MiniSeq. The experiment involves editing via viral transduction, where the construct contains the CAs9 and guide RNA. When performing the NGS analysis, the total reads seem to be good enough (good enough depth). However, the number of reads with the indicator sequences in the given amplicon seems to be awfully low compared to the total reads. I bought new primer sequences for NGS prep and repeated the NGS run. No contamination or primer dimer in the library prep. Still I see the same low reads with indicator sequences in the given amplicon.
I think the transduction and random integration can be the reason for imperfect alignment of the amplicon, resulting in low number of reads with indicator sequences. Am I right? Could there be any other reason ?
The analysis was done via Rgen Cas9 analyzer website link http://www.rgenome.net/cas-analyzer/#!
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Thanks for the reply! I spiked enough PhiX , to get a good cluster density. However, I see your point on low numbers of perfectly matched sgRNAs.
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Our research group plans to buy a NGS sequencer . The obvious choice becomes Illumina MiSeq. However, the steep price tag at 1.5 crore is a hinderance. Can you suggest any alternative along with its price with a mention of the drawbacks when compared to MiSeq. Would really appreciate the help. Thank You in Advance.
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It all depends upon what are you going to primarily look out with sequencing.. Whether Targeted sequencing, whole exome, whole genome etc? For latter two you ideally need a high throughput sequencer and Miseq too would not be a choice there.. Ideally nextseq or novaseq. But these would be way beyond your budget coming at 5 criteria to-8 crore respectively. Low budget sequencer are primarily targeted sequencing with up-to 1-2 whole exomes that can be achieved per run per chip or flow cell. Sequencers in your price bracket would be IonTorrent S5 and Miseq (though a bit costlier) and newly launched illumina iseq. If u are an illumina fan iSeq should be best bet for targeted panel Based sequencing. We use Ion torrent S5 which is very good for targeted sequencing with error rate around 0.5-1%. With automated Ion Chef at additional cost of 40-50 Lakhvinder you can completely automate your work flow for ion torrent.
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Hi
I am looking to upgrade the GPU in our computer to run real-time basecalling with the MinION MK1C. The recommended GPU's are a little out of our price range so I was hoping to get some idea of what people are using.
Our computer specifications are currently:
ASUS X99-e WS motherboard with Intel Xeon E5.
64GB RAM
NVidia Quadro K2200.
I was thinking an Nvidia Quadro RTX 5000
Any advice would be appreciated.
Thanks!
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Miles Benton has become a leading figure in working out GPU solutions and recommendations for Nanopore sequencing. I’d consider giving the link above a read.
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I do not have programming knowledge.
Kindly share any manual calculation protocol.
How to determine the cut-off value for copy number gain or loss?
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Cassiane G. Santos, really thanks for your response. This would indeed be helpful.
But I do also want to identify deletion or duplication of particular genes (Copy Number Variation) from Targeted NGS data. For instance, loss or gain of DEK gene in our clinical samples.
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Dear all,
I am trying to sequence the genome of one protist. Apparently, it has some secrets in its RNA world:) In particular, I cannot remove RNA from gDNA extraction (phenol method or salt method). I tried RNase A (30 min to 4 hrs at 37C or OvN at RT, or combination of both). I also tried the mix of RNase A, Rnase H, and RNase T1 (all we had in the lab). Still, I end up with as much RNA as DNA in my sample.
I figured it might be because of some specific folding of this organisms' RNA species?
In this case, are there any other commercially available RNases I can try?
Or can there be another explanation?
It seems that this RNA contamination affects the downstream sequencing (nanopore), so I'm anxious about finding solution:)
Thank you in advance!
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Hi
Generally, RNases are very effective in removing RNA contamination. I will suggest to address the following concerns
1) Is your RNase working properly? Use some well purified RNA preparation and see the efficiency of degradation.
2) Your genomic DNA prep may have some residual phenol of salt, which may affect the activity of the enzyme.
3) For genomic DNA isolation, the pH of phenol should be close to 8. If lower RNA starts contaminating
see if these tips can help
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Hi,
I have sorted IgA coated bacterial cells by flow cytometry. The cells are in PBS and stored at -80. The total number of events is 50,000. Since it is a small cell numbers, is there any effective protocol to extract DNA from IgA coated bacteria to run 16S NGS? Originally the bacterial cells are extracted from Mice fecal sample.
Any help would be highly appriciated.
Thanks,
Samnhita
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Good question. I agreed with Abhijeet Singh.
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For RNA profiling of frozen tissues, researchers recommend to use single-nuclei RNA sequencing instead of single-cell. What is the reason for this?
Also, what is the best way to freeze cells for RNAseq at a later time?
Thank you very much for your help, be safe!
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If it is not feasible to process fresh tissue, fresh-frozen tissue samples can be used for Single Cell RNA sequencing. Before freezing, the tissue could be dissociated into a single-cell suspension. Cells can then be cryopreserved in a suitable freezing medium. When freezing cells, we recommend starting with at least 1 million total cells to recover sufficient numbers post-thaw since almost half may be lost in the freeze-thaw process and during the wash and centrifugation steps.
If the tissue is frozen whole, it is more challenging to isolate viable single cells after thawing. In this case, it is recommended to extract nuclei from the snap-frozen tissue. Please refer to this article: How do you isolate nuclei from snap-frozen tissue for 3’ gene expression profiling?
The choice of one method over the other(dissociating and then cryopreserving vs. snap-freezing whole tissue) would depend on the sample type. If a well-optimized tissue dissociation protocol is already available that yields >90% viable cells with no cell type bias, then dissociation followed by cryopreservation is preferred. However, if the tissue dissociation protocol is not optimized then it may be better to snap-freeze the tissue whole. It is recommended to try both approaches with a non-precious sample before the actual experiment to know which approach is giving better yields.
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Hello everyone,
What is the minimum DNA concentration (ng/ul), yield (ug), and purity (absorbance A260/A280 and A260/A230) accepted for Next-generation sequencing (Illumina and Ion Torrent)?
Thank you.
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NGS is okay to use in general but when one is talking about more practical stuff, it is good to use name of specific platform.
Concentration and purity and template type would significantly differ among different techniques. But if the concentration is measured with qubit, few nanograms could work. You are talking about ratios (absorbance A260/A280 and A260/A230) that means you are/will use (ing) nanodrop, with is not recommended.
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Hello all,
I have a question regarding gene prediction for long metagenomic reads (MinION nanopore).
I was trying to understand the process of gene prediction. In my attempt, I classified my metagenomic sequences using a reference database by following methods :
1. I did Prodigal to predict ORFs using -p meta option and then ran a diamond aligner using e= 0.002
Result: 689 queries aligned
2. I directly used diamond for alignment of metagenomic reads to the reference database using the same e score value (I did not give identity parameter)
Result: 7292 queries aligned
3. I converted my DNA fasta file to protein sequence using GOTRANSEQ, and did the same analysis with same parameter.
Result: 169 queries aligned.
There is a huge difference between 2 and 3 method? Confused...!!
Which approach is better for predicting protein gene sequence for long reads ?
Is e-value a sufficient parameter for diamond blastp analysis? Do I need to give any identity % in case of first approach?
In addition, I would also like to confirm, whether I can directly use the translated file from PRODIGAL analysis (-a output) for DIAMOND?
Please help
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  1. In my opinion, it would be wiser to assemble the reads before doing any kind of analysis
  2. No wonder different methods give different results. The tools you are using are principally different, thus the results. You can go through the manual of each to see what they are basically designed for. Prodigal on one hand is designed for gene prediction thus it searches protein coding genes (full-length). Diamond on the other hand is a faster version of blast which tries to locally align two sequences irrespective to their functional characteristics or length.
After this, I don't think specific details are important to be further discussed.
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Does anyone have experience with cfDNA NGS?
We would like to sequence some samples, but I'm currently struggling to find the correct NGS protocol.
We can choose from several readmodes:
- NextSeq550High (300-400million reads)
- NextSeq550Medium (110-130million reads)
-NextSeq2000P2 (300-400million reads)
- NovaSeqSP (650-800million reads per lane)
Which one should we choose?
Further, should it be paired-end or single read?
Last question: I have read that some kits (i.e. QIAamp circulating nucleic acid kit) contain carrier RNA complicating NGS library prep. Should we use a kit without carrier RNA (i.e. Norgen's cell-free DNA preservative tubes dx) just to be safe?
Thank you :)
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You can go through the following papers just for the basic idea.
Bennett CW, Berchem G, Kim YJ, El-Khoury V. Cell-free DNA and next-generation sequencing in the service of personalized medicine for lung cancer. Oncotarget. 2016 Oct 25;7(43):71013-71035. doi: 10.18632/oncotarget.11717. PMID: 27589834; PMCID: PMC5342606.
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I have received the annotated data for NGS WGS and we have done some analysis like sequence similarity distribution among species, score distribution of the biological process, etc using Omicsbox. Then we thought of comparing the complete sets of protein and gene (more than 5000 in Fasta format) with protein and gene sets from few other species. Is it possible and how it can be carried out.
I am new to bioinformatics, kindly guide me
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What do you mean by comparing?
There are different ways for the comparative analysis and you need to ask for something specific to get meaningful answers.
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Mutational Analysis.  Will any software help? Could someone help me sort this out?
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Python can be very useful in getting the result.
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Hi everyone,
Illumina provides a list of primers to amplify with high taxonomic coverage the ITS1 region for further fungal sequencing, but I cannot find the exact amount necessary of each primer. I understand then that have to mix them equimolarly, am I right? Has anyone used them?
Thx!
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I am trying to apply meachine learning approaches such as: support vector machines, random forests, artificial neural networks on a microRNA dataset (NGS) and also on a mRNA dataset (NGS).I have used sequencing data for training and to make classifications based on some features and then tested on an independent data set to see the prediction accuracy.
To calculate support vector machines (SVM) I used the R e1071 package but I am looking for other tools.
Any body can share/suggest an R/ Python code/Package?
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LIBSVM -- A Library for Support Vector Machines https://www.csie.ntu.edu.tw/~cjlin/libsvm/
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We collected faecal samples from various species that we want to analyse their microbial communities' DNA via Next-Generation Sequencing. The problem is that due to budgetary constraints, we will have to pool the isolated DNA from each sample to be able to analyse them all. We will of course keep each species separated from the other ones, and we are planning to pool the samples from individuals which share enclosure only. Nevertheless, we do not know if there is a maximum number of samples that can be pooled together for NGS.
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The number depends on the sample type, sequencing platforms and quantity of sequencing data per sample. If you want to study microbial communities samples, you can do 16s/18s/ITS amplicon sequencing, which is cheap and fast. Yun can also choose metagenome sequencing or meta-transcriptome sequencing, which need more data and the bioinformatics work are more complex. For amplion squencing, you can choose NGS or TGS. We now can pool more than 1500 samples per run at Novoseq 6000. For TGS, it's a little bit expensive, but you can get the full-length sequence of the amplificated area, which will gives you a resolution of species-level at diversity analysis.
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I am a research tech in a wildlife genetics group and my PI and I are trying to figure out how/where to put raw reads in a repository. We have capture-seq NGS from Rapid Genomics. The post-doc who was working on a project left our lab group and has not been in good communication to assist. I am new to working with NGS data, slowly trying to figure it out! Any input would be very appreciated!
Maggie
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Hi Magdalena,
If you have raw fastq reads you can simply upload your data on SRA (https://www.ncbi.nlm.nih.gov/sra), it's where ALL the NGS data is uploaded on NCBI.
I'm not sure you can upload on GEO because it accepts studies concerning differential gene expression and regulation, epigenetics, or other functional genomic studies. I'm not familiar with CaptureSeq but it is basically a targeted genome resequencing so you check genotypes, SNPs etc... right?
If that's the case you should create a BioProject for your experiment on SRA (the bioproject is basically a "folder" containing all the reads you produced for a specific experiment/project/manuscript) and then upload your reads in the bioproject, here is the guide: https://www.ncbi.nlm.nih.gov/sra/docs/submit/#submitting-via-sra-submission-po
It's pretty easy, the only complicated part may be the actual uplod of the file. I suggest you to use FileZilla to transfer the files by FTP. Anyway, you find the instrunctions on their websites.
If you have any doubt you can contact the SRA team, they're really nice and helpful!
Best
Umberto
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Hello everyone,
Do you recommend storing DNA and plasma aliquots (samples) at -20°C or -80°C for a period of 5 to 7 months knowing that subsequent analysis will be NGS?
Thank you.
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-80 is no doubt the best option
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Looking expert opinion...
I have collected marine sponge samples and were shadow dried for two weeks. Now the sponge samples are well dried and can be directly powdered by grinding. I would like to study the sponge associated actinobacterial populations (uncultured) from the dried sample rather than fresh sample.
Here comes my doubt,
If we grind and use the sponge powder for metagenomic DNA extraction, does the DNA be damaged/sheared ?
or
can directly use the dried sponge material (without grinding) for metagenomic DNA extraction?
Kindly, some one clarify my doubts.
Thanks in Advance,
Siva
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Hi Sivasankar Palaniappan ! How did the shadow drying method affect the DNA quality of your sponge sample?
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I would like to barcode fungal caps from the field for two main research goals (1) molecular iD of the fungal specimen and (2) to identify any invertebrate DNA within the cap using CO1 primers.
Does anyone have any experience with the versaility of Whatman FTA saver cards (i.e. use with fruiting fungi) and whether it would provide sufficient DNA for the amplification of metazoan communties using Illumina NGS technology?
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Bhaskar Ganguly thank you for your response!
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I need good quality and quantity of viral cDNA for NGS analysis. Please suggest how can I increase amount of cDNA obtained from viral RNA.
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