Settling the Biological Virus Debate

[Scott]

I think the important thing is that it is the -largest- contig and is associated with a whopping 1,407,705 sequences, which in turn is a around 5% of the 26,108,482 remaining sequences, as mentioned by the mathematician. The fact that it has a 98.5% match with a human RNA sequence strongly suggests that this alleged "Cov 2" virus is just mislabelled human RNA.

It is NOT the largest contig.

I think that depends on whether you're looking at the original report from the authors of the alleged discovery of Cov 2, or what the mathematician was able to find while trying reproduce their results.

I don't think you even know what a contig is at this point.

I think the following definitions of reads, sequences and contigs gives a good description of contig as well as the other 2 terms:

**
My understanding of those three words as follows:

sequence is a generic name describing order of biological letters (DNA/RNA or amino acids). Both contigs and reads are DNA/RNA or aa sequences

reads are just a short hand for sequenced reads. Usually sequenced reads refer to somewhat digital information obtained from the sequencing machine (for example Illumina MySeq) and stored in the fastq file with quality scores per base. Reads are usually short. However "short" changes rapidly. Right now MySeq produces reads anywhere between 50-150 base pairs long (bp). From a single run (it will really depends on the run) you can get millions of reads, where each read will be set bp size e.g 100bp long. All reads are stored in a single fastq file per replicate, where all reads in that file are usually of uniform size e.g all 5 million reads are 100bp long.

As a bioinformatician your first job is to identify where about those reads come from. Depending on the experimental goal and on what sort of sequencing you were doing e.g DNA-seq or RNA-seq you may or may not encounter contigs.

contigs are simply reads that have been assembled together. For example if you are doing de novo transcriptomics. Then you would:

purify your transcript from a tissue and send it off for sequencing
get your fastq files with sequenced reads, that are all short reads (e.g 100 bp)
assemble those 100bp reads into a longer contig that hopefully will resemble your individual transcript
**

Source:
https://biology.stackexchange.com/q...equence-reads-and-contigs-of-genetic-material

 

[Scott]

LOL. The mathematician is saying he has no clue as to why they were marked N.

Not sure how you arrived at that conclusion. The mathematician makes it clear why the authors of the original paper claiming the discovery of the alleged Cov 2 virus marked more than half of the reads. Quoting the relevant portion from his paper once more:
**
A large proportion of the sequences, presumably a majority of those of human origin were overwritten by the authors with "N" for unknown and therefore filtered out by fastp.
**

Do you need the word presumably defined for you?

No, but I think it would probably be good to introduce a definition of it here for the purposes of debate:

**
Presume

to believe something to be true because it is very likely, although you are not certain
**

Source:
https://dictionary.cambridge.org/dictionary/english/presuming

The mathematician that refuses to put his name on his work is presuming something he doesn't know.

As I pointed out above, presume literally means to believe something is true even though one isn't completely certain. As to the mathematician not wanting to put his name on his work, it stands to reason given the harsh repercussions that tend follow professionals who go against the mainstream narrative on Covid.

 

[Poor Richard Saunders]

1 divided by 28,459 is 0.00003514, or 0.0035% of the total number of contigs. Certainly a very small fraction of the total. But as I've mentioned before, this contig is not your average contig. It's one of the biggest, if not the biggest contig they found. Another point I made in a previous post that you seem to have forgotten:

**
The point is that this remaining 5% of the sequences, comprising a total of 1,407,705 sequences, all belongs to a single contig, with the identification of k141_27232. It strongly suggests that this contig, far from being viral in nature, was actually -human- in nature. The mathematician even goes so far as to name the specific human component that it has such a high match with:
**
"Homo sapiens RNA, 45S pre- ribosomal N4 (RNA45SN4), ribosomal RNA" (GenBank: NR_146117.1, dated 04/07/2020).
**
**

Source:
Settling the Biological Virus Debate , Post #747

ROFLMAO..
Ok.. so let's see.
First you try to claim that .0035% is statistically meaningful. It isn't under any actual math.
Second you claim that the contig is one of the biggest. - this is after you falsely claimed it was the biggest.
Third - your argument is based on not even knowing what a contig is.
You have no point since the point you make is ridiculous because you completely ignore what a contig actually is in order to try to make your silly point. How many sequences were used to assemble k141_27232? I'll bet you don't know because the author doesn't tell us. Then you don't seem to understand that the contig is NOT found. It is assembled by a "computer game" according to your other silly arguments.

You can't have it both ways. You can't argue that the assembled contigs are invalid at the same time you try to argue they are valid. The way the virus genome and any gemone is found is by using hundreds of thousands of sequence reads many of which are duplicates and overlaps and assembling in different possible ways and then finding the one assembly that is the most statistically likely. The process is such that there will be some that are not statistically relevant. Trying to use those that are outliers is either stupidity or out right falsification. Are you stupid or are you intentionally lying?

 

[Poor Richard Saunders]

I think that depends on whether you're looking at the original report from the authors of the alleged discovery of Cov 2, or what the mathematician was able to find while trying reproduce their results.



I think the following definitions of reads, sequences and contigs gives a good description of contig as well as the other 2 terms:

**
My understanding of those three words as follows:

sequence is a generic name describing order of biological letters (DNA/RNA or amino acids). Both contigs and reads are DNA/RNA or aa sequences

reads are just a short hand for sequenced reads. Usually sequenced reads refer to somewhat digital information obtained from the sequencing machine (for example Illumina MySeq) and stored in the fastq file with quality scores per base. Reads are usually short. However "short" changes rapidly. Right now MySeq produces reads anywhere between 50-150 base pairs long (bp). From a single run (it will really depends on the run) you can get millions of reads, where each read will be set bp size e.g 100bp long. All reads are stored in a single fastq file per replicate, where all reads in that file are usually of uniform size e.g all 5 million reads are 100bp long.

As a bioinformatician your first job is to identify where about those reads come from. Depending on the experimental goal and on what sort of sequencing you were doing e.g DNA-seq or RNA-seq you may or may not encounter contigs.

contigs are simply reads that have been assembled together. For example if you are doing de novo transcriptomics. Then you would:

purify your transcript from a tissue and send it off for sequencing
get your fastq files with sequenced reads, that are all short reads (e.g 100 bp)
assemble those 100bp reads into a longer contig that hopefully will resemble your individual transcript
**

Source:
https://biology.stackexchange.com/q...equence-reads-and-contigs-of-genetic-material

Now do you understand why your use of the word contig is not accurate?

I think it's telling that possibly largest contiguous bit of RNA they found had a very high match to human RNA.

They didn't find a contiguous bit of RNA that matches human RNA.
They have hundreds of thousands of reads. Each read contains contiguous bits of RNA. They then try to assemble those hundreds of thousands of read of which there are duplicates and overlaps into possible combinations based on the overlaps. This is a simple statistical model. You look for the contigs that are the same or very similar. With 28,000 possible contigs, you may have 20,000 that are almost identical and then you have one that is nothing like them. Which one is statistically more likely to be the correct assembly?

By the way, it is disingenuous of you to argue that we can't believe the contigs that are assembled and then argue that one contig proves that the virus could be human. You are doing nothing but spreading bullshit to make such an argument.

 

[Poor Richard Saunders]

No, but I think it would probably be good to introduce a definition of it here for the purposes of debate:

**
Presume

to believe something to be true because it is very likely, although you are not certain
**

Source:
https://dictionary.cambridge.org/dictionary/english/presuming



As I pointed out above, presume literally means to believe something is true even though one isn't completely certain. As to the mathematician not wanting to put his name on his work, it stands to reason given the harsh repercussions that tend follow professionals who go against the mainstream narrative on Covid.

LOL. I guess we can just ignore logic and believe your bullshit.

 

[Scott]

Each contig can use reads that were used in other contigs. All they are doing is assembling the reads in different ways.
That contig in question used only 5% of the total reads he had after he filtered out 55% of the reads so that particular contig used less than 2% of the reads. Because each contig can reuse reads used in other contigs, the number of reads in a specific contig is meaningless when it comes to finding the actual sequence of the virus.

What is important is how many contigs result in similar or identical results. If a contig is completely different from all the other ones then that is an outlier and not likely to be the sequence of the virus.
The anonymous mathematician, who for some reason doesn't want to put his name to this groundbreaking science, had 1 contig out of 28,459 contigs that could considered similar to human RNA.
That would mean that .0035% of the contigs from the mathematician had a possible match to a human RNA sequence. No reasonable mathematician would accept this as statistically significant.

I suspect that you're mistaken here somewhere, but I admit that this bit of text is beyond me. I decided to ask over at Dr. Sam Bailey's substack about your statement above to see if someone there can help me out.

You suspect. That seems to be all you can do.

I've done a whole ot more than that, but I think it's good to admit when one isn't sure of something. I've rarely seen you do so despite the fact that it seems clear to me that there have been many such occassions. Anyway, as I've mentioned elsewhere, I strongly suspect that the fact that the largest contig is apparently human RNA, not part of the the alleged Cov 2 virus, is rather important.

You haven't done more than that.

Yet another unsubstantiated assertion. I think my posts make this clear to anyone who is looking at them from an informed point of view.

You have not responded to any of my math or statements about what constitute a contig.

I hadn't yet responded to those posts. I have now.

Instead you only suspect based on your complete misunderstanding of how a contig is constructed.

I actually defined what a contig means in a subsequent post, I'll let that speak for itself.

Where is your evidence that that particular contig is the largest contig?

I think there is actually some nuance here. First, I'll quote some text from the mathematician's report:


**
A comparison of our results (Tables and Figures: Table 1) with those from [1, Supplementary Table 1. The top 50 abundant assembled contigs generated using the Megahit program.] show remarkable differences. In the following, the contig IDs from [1] are preceded by "1_" to better distinguish them from our contig IDs. In general, it can be stated that our query hits regarding the accession numbers do not exactly match those from [1]. With respect to the subject descriptions, we observed a good match for the most part. Further, with the exception of the longest contig (1_k141_275316), our contigs were found to have greater length and tended to have greater richness of coverage.
**

From the paper...

With respect to the subject descriptions, we observed a good
match for the most part. Further, with the exception of the longest contig
(1_k141_275316),

[snip]
At this point, the contig with the identification k141_27232, with which 1,407,705
sequences are associated, a

Contig K141_27232 is the one you keep referencing. It is clearly not the longest contig.

Certainly not for the authors of the nature paper that claimed they had found the Cov 2 virus. -However-, I suspect it's the longest contig that the mathematician could find when he redid the work of the original authors.

I suspect you are an idiot at this point since you can't tell the difference between k141_27232 and 1_k141_275316

There you go again, ruining a good post with an ad hominem attack -.-

 

[Poor Richard Saunders]

Yet another unsubstantiated assertion. I think my posts make this clear to anyone who is looking at them from an informed point of view.

Anyone that is informed sees that your posts are filled with suspicions that are backed up by no evidence. In some cases your suspicions are refuted by clear and convincing evidence.

I hadn't yet responded to those posts. I have now.



I actually defined what a contig means in a subsequent post, I'll let that speak for itself.

When it speaks, it says your continued use of the word is incorrect.

contigs are simply reads that have been assembled together.

Contigs are not "found." Contigs doesn't mean "contiguous rna."

I think there is actually some nuance here. First, I'll quote some text from the mathematician's report:


**
A comparison of our results (Tables and Figures: Table 1) with those from [1, Supplementary Table 1. The top 50 abundant assembled contigs generated using the Megahit program.] show remarkable differences. In the following, the contig IDs from [1] are preceded by "1_" to better distinguish them from our contig IDs. In general, it can be stated that our query hits regarding the accession numbers do not exactly match those from [1]. With respect to the subject descriptions, we observed a good match for the most part. Further, with the exception of the longest contig (1_k141_275316), our contigs were found to have greater length and tended to have greater richness of coverage.
**





Certainly not for the authors of the nature paper that claimed they had found the Cov 2 virus. -However-, I suspect it's the longest contig that the mathematician could find when he redid the work of the original authors.

Let's see what the author of the paper you keep referencing says.....

Our longest contig showed
a perfect match with the MN908947.3 sequence at a length of 29,801 nt

Hmmmm.. It would seem that you could only suspect that k141_27232 is the longest the mathematician could find if you completely ignore what the mathematician actually said. Clear and convincing evidence that your suspicions are wrong.
The mathematician, who refused to put his name on the paper, never gives us the length of k141_27232 but it certainly is not the longest since he names the longest and it is NOT k141_27232. Your suspicions are based on nothing and are clearly false based on your own source.

There you go again, ruining a good post with an ad hominem attack -.-

There you go again, trying to avoid answering for your bullshit.



Meanwhile we have the following evidence that you refuse to address at all.
Viruses have been isolated and grown in tissue cultures.
Viruses grown in tissue cultures have infected people.


https://pubmed.ncbi.nlm.nih.gov/17469121/
Until you can prove that the virus wasn't grown in a tissue culture and the Nobel committee were fooled any claim that viruses can't be grown in culture are nothing but bullshit from you.


Since we now have evidence of a virus being grown in a culture and you can not refute it with any evidence, let's move on to the next step that proves that viruses grown in a culture can infect people after the virus is grown.
In 1955, Cutter grew the virus in culture and used it to make vaccine. They failed to adequately kill the virus and the virus grown in a culture was used to infect over 40,000 people.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1383764/

 

[Scott]

You don't understand. It was the original authors of the nature paper that claimed to have discovered the Cov 2 virus that eliminated 55% of the reads. The mathematician specifically stated that this was problematic. Below I'll requote the relevant part from the paper published by the mathematician, with the help of Dr. Stefan Lanka. Note where he refers to "the authors". He's referring to the authors of the paper published in Nature that claimed that the alleged Cov 2 virus had been discovered:

**

Renewed de novo assembly of published sequence data

To repeat the de novo assembly, we downloaded the original sequence data (SRR10971381) from 27/01/2020 on 11/30/2021 using the SRA tools [19] from the Internet. To prepare the paired-end reads for the actual assembly step with Megahit (v.1.2.9) [20], we used the FASTQ preprocessor fastp (v.0.23.1) [21]. After filtering the paired-end reads, 26,108,482 of the original total of 56,565,928 reads remained, with a length of about 150 bp. A large proportion of the sequences, presumably a majority of those of human origin were overwritten by the authors with "N" for unknown and therefore filtered out by fastp. This is to be regarded as problematic in the sense of scientificity, since not all steps can be retraced or reproduced. For the elaborate contig generation from the remaining short sequence reads, we used Megahit (v.1.2.9) using the default setting.
**

Source:
https://brandfolder.com/s/3z266k74ppmnwkvfrxs6jjc

I understand perfectly who eliminated the reads. What you don't seem to understand is you don't know why they were eliminated.

While I can't claim to read the minds of the authors of the nature paper, they labelled over half of the reads as "N" for unknown and then eliminated them.

Claiming they were eliminated because they were presumed to be of human in origin has as much evidence as claiming they were eliminated because they were presumed to be a 1957 chevy.

Neither I or the mathematician's paper claimed that the authors of the nature paper eliminated them because they were presumed to be of human origin. I have never claimed to read minds. The authors of the nature paper labelled them as "N" for Unknown. All the mathematician said is that the majority of those sequences were presumably of human origin.

The mathematician also marked reads as "N" and it had nothing to do with them being of human origin.

We set all bases with a quality lower than 20 to "N" (unknown). A quality of 20 means an error rate of 1% per
nucleotide, which can be considered sufficient in the context of our analyses.

[Source: https://brandfolder.com/s/3z266k74ppmnwkvfrxs6jjc ]

I -think- we can agree that "N" stands for unknown. I suspect that the mathematician presumed that the majority of the N sequences he eliminated were human, but that's not why he eliminated them. He eliminated them because he believed that they had a quality lower than 20.

Setting them to "N" had nothing to do with them being of human origin. It has to do with the quality of the read and the error associated with it. Perhaps we should presume the mathematician did this in order to make sure his results would not be the same.

I think the issue may be that the mathematician made it clear that he would eliminate reads with a quality lower than 20. I'm guessing that the authors of the original nature paper didn't specify the criteria they used to eliminate reads. As I've pointed out before, the mathematician found something the authors of the nature paper did to be problematic. Quoting from his paper:

**

Renewed de novo assembly of published sequence data

To repeat the de novo assembly, we downloaded the original sequence data (SRR10971381) from 27/01/2020 on 11/30/2021 using the SRA tools [19] from the Internet. To prepare the paired-end reads for the actual assembly step with Megahit (v.1.2.9) [20], we used the FASTQ preprocessor fastp (v.0.23.1) [21]. After filtering the paired-end reads, 26,108,482 of the original total of 56,565,928 reads remained, with a length of about 150 bp. A large proportion of the sequences, presumably a majority of those of human origin were overwritten by the authors with "N" for unknown and therefore filtered out by fastp. This is to be regarded as problematic in the sense of scientificity, since not all steps can be retraced or reproduced.
**

What I'd like to know is, what did the mathematician think should have been done with the Ns from the authors of the nature paper?

 

[Scott]

Already addressed your statement in my last post, but I'm writing this one because I got a response to your statement, not from Dr. Sam Bailey's substack, but from a facebook group that a substack respondent pointed me towards. I simply quoted what you said above and there was some confusion as to who had said it, but I think the respondent's points were good. She gave me permission to quote what she said:

**
I can't tell what you wrote vs. what someone else wrote, but all the talk about reads and contigs is irrelevant when the source of those reads and contigs can be anything in the original substance that was used in this "sequence the genome" computer game. What substance did those reads and contigs come from? If they're calling it a "virus," then by what means was it confirmed to be a particle containing RNA or DNA, capable of replicating inside a human cell and thereby causing human illness? (or have they changed the definition like they changed the definition of "isolate"?)

Without answering those questions, it makes no difference how those reads and contigs were assembled by the computer, nor how many "match" bits and pieces of human DNA/RNA or DNA/RNA from any other organism.
**

I got another response that I thought was quite good from someone named Patrik, but I only just asked him if I could quote him, no response yet. If you'd like to see his response, it's here:
https://www.facebook.com/groups/1816658931849533/posts/2535763723272380/

Easy to respond to:
https://pubmed.ncbi.nlm.nih.gov/17469121/

Responding is certainly easy, but responding with a strong counter argument is another matter entirely.

Until you can prove that the virus wasn't grown in a tissue culture and the Nobel committee were fooled any claim that viruses can't be grown in culture are nothing but bullshit from you.

As I've told you time and time again, proving -anything- is hard. I focus on evidence. As to the claim that the polio virus was allegedly grown in tissue culture, if I find an article refuting it, I'll let you know. In the meantime, I believe the claim is false due to the fact that the group of doctors have been saying for a while that no virus has ever been isolated, which would mean that there could be no solid evidence that any virus has ever been grown.

 

[Scott]

1 divided by 28,459 is 0.00003514, or 0.0035% of the total number of contigs. Certainly a very small fraction of the total. But as I've mentioned before, this contig is not your average contig. It's one of the biggest, if not the biggest contig they found. Another point I made in a previous post that you seem to have forgotten:

**
The point is that this remaining 5% of the sequences, comprising a total of 1,407,705 sequences, all belongs to a single contig, with the identification of k141_27232. It strongly suggests that this contig, far from being viral in nature, was actually -human- in nature. The mathematician even goes so far as to name the specific human component that it has such a high match with:
**
"Homo sapiens RNA, 45S pre- ribosomal N4 (RNA45SN4), ribosomal RNA" (GenBank: NR_146117.1, dated 04/07/2020).
**
**

Source:
Settling the Biological Virus Debate , Post #747

ROFLMAO..
Ok.. so let's see.
First you try to claim that .0035% is statistically meaningful. It isn't under any actual math.

Again, I think your problem is you seem to think that all contigs should have equal weight. It seems clear to me that the mathematician believes otherwise, and I believe he's right.

Second you claim that the contig is one of the biggest. - this is after you falsely claimed it was the biggest.

It may well be the longest contig that the mathematician claimed to find. It was not the longest contig that the authors of the nature paper claimed to find.

Third - your argument is based on not even knowing what a contig is.

I get into the definition of contigs in post #801.

 

[Scott]

I don't think you even know what a contig is at this point.

I think the following definitions of reads, sequences and contigs gives a good description of contig as well as the other 2 terms:

**
My understanding of those three words as follows:

sequence is a generic name describing order of biological letters (DNA/RNA or amino acids). Both contigs and reads are DNA/RNA or aa sequences

reads are just a short hand for sequenced reads. Usually sequenced reads refer to somewhat digital information obtained from the sequencing machine (for example Illumina MySeq) and stored in the fastq file with quality scores per base. Reads are usually short. However "short" changes rapidly. Right now MySeq produces reads anywhere between 50-150 base pairs long (bp). From a single run (it will really depends on the run) you can get millions of reads, where each read will be set bp size e.g 100bp long. All reads are stored in a single fastq file per replicate, where all reads in that file are usually of uniform size e.g all 5 million reads are 100bp long.

As a bioinformatician your first job is to identify where about those reads come from. Depending on the experimental goal and on what sort of sequencing you were doing e.g DNA-seq or RNA-seq you may or may not encounter contigs.

contigs are simply reads that have been assembled together. For example if you are doing de novo transcriptomics. Then you would:

purify your transcript from a tissue and send it off for sequencing
get your fastq files with sequenced reads, that are all short reads (e.g 100 bp)
assemble those 100bp reads into a longer contig that hopefully will resemble your individual transcript
**

Source:
https://biology.stackexchange.com/q...equence-reads-and-contigs-of-genetic-material

Now do you understand why your use of the word contig is not accurate?

How about you just tell me why you think my use of the word is innacurate?

 

[Poor Richard Saunders]

While I can't claim to read the minds of the authors of the nature paper, they labelled over half of the reads as "N" for unknown and then eliminated them.

Since you can't read minds, perhaps you shouldn't suspect things you have no idea as to whether your suspicions are even close to being true. All we see from you is circular reasoning and other fallacious bullshit.

Neither I or the mathematician's paper claimed that the authors of the nature paper eliminated them because they were presumed to be of human origin. I have never claimed to read minds. The authors of the nature paper labelled them as "N" for Unknown. All the mathematician said is that the majority of those sequences were presumably of human origin.

Are you saying what you suspect is not supported by facts? I would agree. You do suspect a lot of things that turn out to be not true.

I -think- we can agree that "N" stands for unknown. I suspect that the mathematician presumed that the majority of the N sequences he eliminated were human, but that's not why he eliminated them. He eliminated them because he believed that they had a quality lower than 20.

Since N stands for unknown, that would be evidence that you don't know why they were eliminated. But you seem to keep claiming you know something that you clearly don't know.

I think the issue may be that the mathematician made it clear that he would eliminate reads with a quality lower than 20. I'm guessing that the authors of the original nature paper didn't specify the criteria they used to eliminate reads. As I've pointed out before, the mathematician found something the authors of the nature paper did to be problematic. Quoting from his paper:

**

Renewed de novo assembly of published sequence data

To repeat the de novo assembly, we downloaded the original sequence data (SRR10971381) from 27/01/2020 on 11/30/2021 using the SRA tools [19] from the Internet. To prepare the paired-end reads for the actual assembly step with Megahit (v.1.2.9) [20], we used the FASTQ preprocessor fastp (v.0.23.1) [21]. After filtering the paired-end reads, 26,108,482 of the original total of 56,565,928 reads remained, with a length of about 150 bp. A large proportion of the sequences, presumably a majority of those of human origin were overwritten by the authors with "N" for unknown and therefore filtered out by fastp. This is to be regarded as problematic in the sense of scientificity, since not all steps can be retraced or reproduced.
**

What I'd like to know is, what did the mathematician think should have been done with the Ns from the authors of the nature paper?

What I would like to know is why the mathematician and you haven't considered the other times that Covid-2 was assembled de-novo not using the Wuhan paper and they came up with the same genetic sequence.
https://www.liebertpub.com/doi/10.1089/omi.2022.0042
Overall, three assemblers, that is, SPAdes, IDBA, and ABySS, performed consistently well, including for genome assembly of SARS-CoV-2

https://pubmed.ncbi.nlm.nih.gov/33822878/
We performed 6648 de novo assemblies of 416 SARS-CoV-2 samples using eight different assemblers with different k-mer lengths.

https://www.semanticscholar.org/pap...uyen/f5b89ebbaa8b493f053ae398dbf3d5589b148d06
The sequencing was successfully completed and de novo assembled in less than 30 hours, resulting in one contig with no gap and a length of 29,766 bp


Who should we believe? Your mathematician that did one de novo assembly or others that have done over 6,0000 de novo assemblies from multiple samples?

 

[Poor Richard Saunders]

How about you just tell me why you think my use of the word is innacurate?

It would seem that your ability to read and understand is limited. You get many things wrong from the papers you quote and you can't understand when I have told you why your use of contig is wrong.


contigs are simply reads that have been assembled together.
Each assembly has the same chance of being correct. When you do 28,000 assemblies each assembly has a .0035% chance of being correct. Picking out one outlier and claiming it has some relevance shows you don't know what contig means. Statistically, you look for contigs that are similar to find the rna sequence of a genome. Each contig uses some combination of reads that is different from the reads used other contigs. A contig may use 99% of the same reads as another contig or it could use 0% of the reads used by that other contig.


Meanwhile we have the following evidence that you refuse to address at all.
Viruses have been isolated and grown in tissue cultures.
Viruses grown in tissue cultures have infected people.


https://pubmed.ncbi.nlm.nih.gov/17469121/
Until you can prove that the virus wasn't grown in a tissue culture and the Nobel committee were fooled any claim that viruses can't be grown in culture are nothing but bullshit from you.


Since we now have evidence of a virus being grown in a culture and you can not refute it with any evidence, let's move on to the next step that proves that viruses grown in a culture can infect people after the virus is grown.
In 1955, Cutter grew the virus in culture and used it to make vaccine. They failed to adequately kill the virus and the virus grown in a culture was used to infect over 40,000 people.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1383764/

 

[Poor Richard Saunders]

Again, I think your problem is you seem to think that all contigs should have equal weight. It seems clear to me that the mathematician believes otherwise, and I believe he's right.

Where does the mathematician state that one contig should have more weight than another? Claiming that it should would be a violation of mathematical principles.
What is clear to you seems to be things that don't exist. Or in the case of viruses what is clear to you things that do exist don't exist.

It may well be the longest contig that the mathematician claimed to find. It was not the longest contig that the authors of the nature paper claimed to find.

It may not well be the longest contig the mathematician found since the mathematician states the longest one he found and it is NOT the one you keep referring to as the longest.
Your refusal to accept facts in front of your face is ridiculous at this point. Get medical help for your condition.
This is from the paper -
Our longest contig showed
a perfect match with the MN908947.3 sequence at a length of 29,801 nt

Just so you know, (GenBank: MN908947.3) is the genome for Sars-Covid-2 that is recorded in GenBank.

The longest contig the mathematician assembled is a perfect match for the Sars-Covid-2 virus.

Let me repeat that so that every time you say something about the longest contig found, I can repeat it..

The longest contig the mathematician assembled is a perfect match for the Sars-Covid-2 virus.

I get into the definition of contigs in post #801.

Then tell is in your own words what a contig is. My bet is you will not use the correct terminology.

 

[Poor Richard Saunders]

Responding is certainly easy, but responding with a strong counter argument is another matter entirely.



As I've told you time and time again, proving -anything- is hard. I focus on evidence. As to the claim that the polio virus was allegedly grown in tissue culture, if I find an article refuting it, I'll let you know. In the meantime, I believe the claim is false due to the fact that the group of doctors have been saying for a while that no virus has ever been isolated, which would mean that there could be no solid evidence that any virus has ever been grown.

I notice you are the one with no counter argument.

I presented evidence of a particle capable of replicating inside a human cell and thereby causing human illness. Do you have evidence that the Nobel committee was wrong when they awarded the prize for growing a particle capable of replicating inside a human cell and thereby causing human illness.

Not only have I presented a counter argument. I have provided strong evidence in support of my counter argument. You on the other hand have no Nobel winning scientists but only some anonymous person on Facebook.

I am calling it a virus because of the following:
The particle has been grown in tissue.
The particle has infected other people after being grown in tissue.
The particle has been isolated enough to take electron microscope pictures of with nothing else visible in the picture.
The particle has been sequenced to show it's genome.

The questions clearly have been answered. Your claim I don't have a strong counter argument is nonsense.


What evidence do you have that the polio virus can't be grown in tissue?
What evidence do you have that 40,000 people weren't infected with that virus grown in tissue when Cutter failed to properly kill it?
What evidence do you have that something other than a polio virus is in the multiple electron microscope pictures I have provided?

 

[Scott]

I think it's telling that possibly largest contiguous bit of RNA they found had a very high match to human RNA. To be fair to the authors of the alleged discovery of the Cov 2 virus, however, that part of RNA had not yet been known when they published their findings. It is now though, and people have to have a more serious look at this alleged Cov 2 virus given this new evidence.

They didn't find a contiguous bit of RNA that matches human RNA.

The evidence that the alleged Cov 2 virus is in fact composed of a substantial chunk of human RNA is strong. I strongly opposed your dismissal of this contig being human RNA way back in post #766:

**
A "similarity"? We're talking about a 98.5% match with "Homo sapiens RNA, 45S pre- ribosomal N4 (RNA45SN4), ribosomal RNA" (GenBank: NR_146117.1, dated 04/07/2020)", as I just quoted above. That is far more than a simple "similarity". And let's not forget that this isn't some small contig we're talking about either. Again, I think you haven't grasped just how important this contig is. The mathematician certainly made it quite clear. Quoting from him once more:
**
At this point, the contig with the identification k141_27232, with which 1,407,705 sequences are associated, and thus about 5% of the remaining 26,108,482 sequences, should be discussed in detail.
**

Source:
https://brandfolder.com/s/3z266k74ppmnwkvfrxs6jjc
**

They have hundreds of thousands of reads.

True, and a whopping 1,407,705 sequences/reads, constituting around 5% of the remaining 26,108,482 reads, are associated with k141_27232.

 

[Scott]

I actually defined what a contig means in a subsequent post, I'll let that speak for itself.

When it speaks, it says your continued use of the word is incorrect.

contigs are simply reads that have been assembled together.

Contigs are not "found." Contigs doesn't mean "contiguous rna."

Contig is short for contiguous. The fact that they are assembled doesn't change the fact that once assembled, they form a contiguous length of RNA.

Certainly not for the authors of the nature paper that claimed they had found the Cov 2 virus. -However-, I suspect it's the longest contig that the mathematician could find when he redid the work of the original authors.

Let's see what the author of the paper you keep referencing says.....

Our longest contig showed a perfect match with the MN908947.3 sequence at a length of 29,801 nt

Hmmmm.. It would seem that you could only suspect that k141_27232 is the longest the mathematician could find if you completely ignore what the mathematician actually said.

You mistake ignore with simply not remembering everything he said. So, congratulations, you've shown that k141_27232 was not, in fact, the longest contig that the mathematician found. That doesn't change the fact that the mathematician found k141_27232 very interesting. Furthermore, there are other points that I think are quite interesting. Many of them are made in the very paragraph from which you got your sentence. Quoting the complete paragraph:

**
We obtained 28,459 (200 nt - 29,802 nt) contigs, significantly less than described in [1]. Deviating from the representations in [1], the longest contig we assembled comprised only 29,802 nt, 672 nt less than the longest contig with 30,474 nt, which according to [1] comprised almost the entire viral genome. Our longest contig showed a perfect match with the MN908947.3 sequence at a length of 29,801 nt (Tables and Figures, Tables 1, 2). Thus, we could not reproduce the longest contig of 30,474 nt, which is so important for scientific verification. Consequently, the published sequence data cannot be the original reads used for assembly.
**

Aren't you at least curious as to why the published sequence data can't be the original reads used for assembly?

Surely the fact that the mathematician and doctor Stefan Lanka couldn't even reproduce the longest sequence allegedly found by the authors of the alleged Cov 2 virus, which "comprised almost the entire viral genome" should be a blazing red flag, don't you think?

The mathematician, who refused to put his name on the paper, never gives us the length of k141_27232

As mentioned elsewhere, there are very good reasons why the mathematician wouldn't want to put his name to the paper. It's hardly news that any professional who disagrees with the official covid narrative is bound to have serious repercussions. I think the treatment of doctors like Dr. Sam Bailey provides ample evidence for this.

In any case, you do seem to be right concerning the fact that the mathematician and Dr. Stefan Lanka never mentions the length of k141_27232 contig, at least in the analysis paper. I suspect that it may be in the tables document. I may look at that later to see if it's there.

 

[Scott]

Neither I or the mathematician's paper claimed that the authors of the nature paper eliminated them because they were presumed to be of human origin. I have never claimed to read minds. The authors of the nature paper labelled them as "N" for Unknown. All the mathematician said is that the majority of those sequences were presumably of human origin.

Are you saying what you suspect is not supported by facts?

No. Not sure how you would come to that conclusion from what I wrote above either.

I -think- we can agree that "N" stands for unknown. I suspect that the mathematician presumed that the majority of the N sequences he eliminated were human, but that's not why he eliminated them. He eliminated them because he believed that they had a quality lower than 20.

Since N stands for unknown, that would be evidence that you don't know why they were eliminated.

No, why they were eliminated seems perfectly clear. The mathematician and Dr. Stefan Lanka labelled all sequences with a quality lower than 20 with "N" and eliminated them.

I think the issue may be that the mathematician made it clear that he would eliminate reads with a quality lower than 20. I'm guessing that the authors of the original nature paper didn't specify the criteria they used to eliminate reads. As I've pointed out before, the mathematician found something the authors of the nature paper did to be problematic. Quoting from his paper:

**

Renewed de novo assembly of published sequence data

To repeat the de novo assembly, we downloaded the original sequence data (SRR10971381) from 27/01/2020 on 11/30/2021 using the SRA tools [19] from the Internet. To prepare the paired-end reads for the actual assembly step with Megahit (v.1.2.9) [20], we used the FASTQ preprocessor fastp (v.0.23.1) [21]. After filtering the paired-end reads, 26,108,482 of the original total of 56,565,928 reads remained, with a length of about 150 bp. A large proportion of the sequences, presumably a majority of those of human origin were overwritten by the authors with "N" for unknown and therefore filtered out by fastp. This is to be regarded as problematic in the sense of scientificity, since not all steps can be retraced or reproduced.
**

What I'd like to know is, what did the mathematician think should have been done with the Ns from the authors of the nature paper?

What I would like to know is why the mathematician and you haven't considered the other times that Covid-2 was assembled de-novo not using the Wuhan paper and they came up with the same genetic sequence.
https://www.liebertpub.com/doi/10.1089/omi.2022.0042
Overall, three assemblers, that is, SPAdes, IDBA, and ABySS, performed consistently well, including for genome assembly of SARS-CoV-2

https://pubmed.ncbi.nlm.nih.gov/33822878/
We performed 6648 de novo assemblies of 416 SARS-CoV-2 samples using eight different assemblers with different k-mer lengths.

https://www.semanticscholar.org/pap...uyen/f5b89ebbaa8b493f053ae398dbf3d5589b148d06
The sequencing was successfully completed and de novo assembled in less than 30 hours, resulting in one contig with no gap and a length of 29,766 bp

Who should we believe? Your mathematician that did one de novo assembly or others that have done over 6,0000 de novo assemblies from multiple samples?

My understanding is that -all- alleged findings of the alleged Cov 2 virus and its alleged variants are based on the Wuhan authors of the nature paper.

 

[Scott]

How about you just tell me why you think my use of the word is innacurate?

It would seem that your ability to read and understand is limited. You get many things wrong from the papers you quote and you can't understand when I have told you why your use of contig is wrong.

contigs are simply reads that have been assembled together.

I hope you've noted that I quoted that definition of contigs before you did.

Each assembly has the same chance of being correct. When you do 28,000 assemblies each assembly has a .0035% chance of being correct.

I strongly suspect that you're getting that percentage chance from a calculation I did, and it had nothing to do with the chances of a contig being correct. So, where exactly did you get that percentage chance?

 

[Poor Richard Saunders]

The evidence that the alleged Cov 2 virus is in fact composed of a substantial chunk of human RNA is strong. I strongly opposed your dismissal of this contig being human RNA way back in post #766:

**
A "similarity"? We're talking about a 98.5% match with "Homo sapiens RNA, 45S pre- ribosomal N4 (RNA45SN4), ribosomal RNA" (GenBank: NR_146117.1, dated 04/07/2020)", as I just quoted above. That is far more than a simple "similarity". And let's not forget that this isn't some small contig we're talking about either. Again, I think you haven't grasped just how important this contig is. The mathematician certainly made it quite clear. Quoting from him once more:
**
At this point, the contig with the identification k141_27232, with which 1,407,705 sequences are associated, and thus about 5% of the remaining 26,108,482 sequences, should be discussed in detail.
**

Source:
https://brandfolder.com/s/3z266k74ppmnwkvfrxs6jjc
**



True, and a whopping 1,407,705 sequences/reads, constituting around 5% of the remaining 26,108,482 reads, are associated with k141_27232.

Statistically insignificant. .0035% of the contigs is not a strong probability of being correct.
The evidence is not strong since something that is statistically insignificant can't be considered strong by any stretch of the imagination.
Since our mathematician that refuses to sign his name to his paper also refused to release the contig, we have no way of checking his work.

If it is a 98% match to GenBank: NR_146117.1 then it isn't a long contig at all which only goes to show again that you don't know what you are talking about when you claim it was the longest and now changed to one of the longest.
GenBank: NR_146117.1 is less than 1/2 the size of the Covid genome.
All you are arguing is that this sequence would have been filtered out if GenBank: NR_146117.1 had existed in the database.