Why Illumina if PacBio provides longer and better reads?
$begingroup$
PacBio provides longer read length than Illumina's short-length reads. Longer reads offer better opportunity for genome assembly, structural variant calling. It is not worse than short reads for calling SNP/indels, quantifying transcripts. Sounds like PacBio can do whatever Illumina platform can offer.
Would that be any reason for going with Illumina if PacBio's long reads can do everything and more?
long-reads
$endgroup$
|
show 9 more comments
$begingroup$
PacBio provides longer read length than Illumina's short-length reads. Longer reads offer better opportunity for genome assembly, structural variant calling. It is not worse than short reads for calling SNP/indels, quantifying transcripts. Sounds like PacBio can do whatever Illumina platform can offer.
Would that be any reason for going with Illumina if PacBio's long reads can do everything and more?
long-reads
$endgroup$
2
$begingroup$
PacBio used to have high error rates and the expensive libraries with low throughput. In terms of transcriptome, its not quantitative, needs to generate several libraries with different fragment lengths, again not quantitative, captures only abundant transcripts, misses LncRNAs.
$endgroup$
– geek_y
Jan 31 at 6:29
1
$begingroup$
@geek_y Can you please elaborate in details, and if possible with reference? Your answer will be useful for our users, not just myself!
$endgroup$
– SmallChess
Jan 31 at 6:32
2
$begingroup$
IMHO not all NGS questions are about bioinformatics, @gringer, and not all bioinformatics has to do with NGS. So I kindly disagree with your statement about "Bioinformatics includes NGS". This question is about the specs of different platforms, and could be asked on a forum such as SEQanswers.
$endgroup$
– benn
Jan 31 at 9:53
2
$begingroup$
@benn Analyzing NGS data is very much a part of bioinformatics. By extension, the generation of NGS data is also on topic here since it is very relevant to the job of the bioinformatician who will analyze them. I don't understand why you would consider this off topic. We've even had a meta discussion about this sort of thing and the consensus was clear: biological questions are on topic when they are relevant to bioinformatics.
$endgroup$
– terdon♦
Jan 31 at 10:08
2
$begingroup$
The close votes claim that this question is opinion-based, but there are some very objective answers to the question of which sequencing platform to choose. I think the question itself could be re-worded a bit, but it's definitely an on-topic discussion.
$endgroup$
– Daniel Standage
Jan 31 at 14:09
|
show 9 more comments
$begingroup$
PacBio provides longer read length than Illumina's short-length reads. Longer reads offer better opportunity for genome assembly, structural variant calling. It is not worse than short reads for calling SNP/indels, quantifying transcripts. Sounds like PacBio can do whatever Illumina platform can offer.
Would that be any reason for going with Illumina if PacBio's long reads can do everything and more?
long-reads
$endgroup$
PacBio provides longer read length than Illumina's short-length reads. Longer reads offer better opportunity for genome assembly, structural variant calling. It is not worse than short reads for calling SNP/indels, quantifying transcripts. Sounds like PacBio can do whatever Illumina platform can offer.
Would that be any reason for going with Illumina if PacBio's long reads can do everything and more?
long-reads
long-reads
edited Jan 31 at 6:31
SmallChess
asked Jan 31 at 5:39
SmallChessSmallChess
1,338622
1,338622
2
$begingroup$
PacBio used to have high error rates and the expensive libraries with low throughput. In terms of transcriptome, its not quantitative, needs to generate several libraries with different fragment lengths, again not quantitative, captures only abundant transcripts, misses LncRNAs.
$endgroup$
– geek_y
Jan 31 at 6:29
1
$begingroup$
@geek_y Can you please elaborate in details, and if possible with reference? Your answer will be useful for our users, not just myself!
$endgroup$
– SmallChess
Jan 31 at 6:32
2
$begingroup$
IMHO not all NGS questions are about bioinformatics, @gringer, and not all bioinformatics has to do with NGS. So I kindly disagree with your statement about "Bioinformatics includes NGS". This question is about the specs of different platforms, and could be asked on a forum such as SEQanswers.
$endgroup$
– benn
Jan 31 at 9:53
2
$begingroup$
@benn Analyzing NGS data is very much a part of bioinformatics. By extension, the generation of NGS data is also on topic here since it is very relevant to the job of the bioinformatician who will analyze them. I don't understand why you would consider this off topic. We've even had a meta discussion about this sort of thing and the consensus was clear: biological questions are on topic when they are relevant to bioinformatics.
$endgroup$
– terdon♦
Jan 31 at 10:08
2
$begingroup$
The close votes claim that this question is opinion-based, but there are some very objective answers to the question of which sequencing platform to choose. I think the question itself could be re-worded a bit, but it's definitely an on-topic discussion.
$endgroup$
– Daniel Standage
Jan 31 at 14:09
|
show 9 more comments
2
$begingroup$
PacBio used to have high error rates and the expensive libraries with low throughput. In terms of transcriptome, its not quantitative, needs to generate several libraries with different fragment lengths, again not quantitative, captures only abundant transcripts, misses LncRNAs.
$endgroup$
– geek_y
Jan 31 at 6:29
1
$begingroup$
@geek_y Can you please elaborate in details, and if possible with reference? Your answer will be useful for our users, not just myself!
$endgroup$
– SmallChess
Jan 31 at 6:32
2
$begingroup$
IMHO not all NGS questions are about bioinformatics, @gringer, and not all bioinformatics has to do with NGS. So I kindly disagree with your statement about "Bioinformatics includes NGS". This question is about the specs of different platforms, and could be asked on a forum such as SEQanswers.
$endgroup$
– benn
Jan 31 at 9:53
2
$begingroup$
@benn Analyzing NGS data is very much a part of bioinformatics. By extension, the generation of NGS data is also on topic here since it is very relevant to the job of the bioinformatician who will analyze them. I don't understand why you would consider this off topic. We've even had a meta discussion about this sort of thing and the consensus was clear: biological questions are on topic when they are relevant to bioinformatics.
$endgroup$
– terdon♦
Jan 31 at 10:08
2
$begingroup$
The close votes claim that this question is opinion-based, but there are some very objective answers to the question of which sequencing platform to choose. I think the question itself could be re-worded a bit, but it's definitely an on-topic discussion.
$endgroup$
– Daniel Standage
Jan 31 at 14:09
2
2
$begingroup$
PacBio used to have high error rates and the expensive libraries with low throughput. In terms of transcriptome, its not quantitative, needs to generate several libraries with different fragment lengths, again not quantitative, captures only abundant transcripts, misses LncRNAs.
$endgroup$
– geek_y
Jan 31 at 6:29
$begingroup$
PacBio used to have high error rates and the expensive libraries with low throughput. In terms of transcriptome, its not quantitative, needs to generate several libraries with different fragment lengths, again not quantitative, captures only abundant transcripts, misses LncRNAs.
$endgroup$
– geek_y
Jan 31 at 6:29
1
1
$begingroup$
@geek_y Can you please elaborate in details, and if possible with reference? Your answer will be useful for our users, not just myself!
$endgroup$
– SmallChess
Jan 31 at 6:32
$begingroup$
@geek_y Can you please elaborate in details, and if possible with reference? Your answer will be useful for our users, not just myself!
$endgroup$
– SmallChess
Jan 31 at 6:32
2
2
$begingroup$
IMHO not all NGS questions are about bioinformatics, @gringer, and not all bioinformatics has to do with NGS. So I kindly disagree with your statement about "Bioinformatics includes NGS". This question is about the specs of different platforms, and could be asked on a forum such as SEQanswers.
$endgroup$
– benn
Jan 31 at 9:53
$begingroup$
IMHO not all NGS questions are about bioinformatics, @gringer, and not all bioinformatics has to do with NGS. So I kindly disagree with your statement about "Bioinformatics includes NGS". This question is about the specs of different platforms, and could be asked on a forum such as SEQanswers.
$endgroup$
– benn
Jan 31 at 9:53
2
2
$begingroup$
@benn Analyzing NGS data is very much a part of bioinformatics. By extension, the generation of NGS data is also on topic here since it is very relevant to the job of the bioinformatician who will analyze them. I don't understand why you would consider this off topic. We've even had a meta discussion about this sort of thing and the consensus was clear: biological questions are on topic when they are relevant to bioinformatics.
$endgroup$
– terdon♦
Jan 31 at 10:08
$begingroup$
@benn Analyzing NGS data is very much a part of bioinformatics. By extension, the generation of NGS data is also on topic here since it is very relevant to the job of the bioinformatician who will analyze them. I don't understand why you would consider this off topic. We've even had a meta discussion about this sort of thing and the consensus was clear: biological questions are on topic when they are relevant to bioinformatics.
$endgroup$
– terdon♦
Jan 31 at 10:08
2
2
$begingroup$
The close votes claim that this question is opinion-based, but there are some very objective answers to the question of which sequencing platform to choose. I think the question itself could be re-worded a bit, but it's definitely an on-topic discussion.
$endgroup$
– Daniel Standage
Jan 31 at 14:09
$begingroup$
The close votes claim that this question is opinion-based, but there are some very objective answers to the question of which sequencing platform to choose. I think the question itself could be re-worded a bit, but it's definitely an on-topic discussion.
$endgroup$
– Daniel Standage
Jan 31 at 14:09
|
show 9 more comments
3 Answers
3
active
oldest
votes
$begingroup$
There are so many reasons why one might want to prefer Illumina over PacBio (also note that it's a false dichotomy, at least Oxford Nanopore is a competitive sequencing platform):
- The first (IMHO and the most common reason) is still the cost of both sequencing and the instruments. Illumina can sequence a Gbp of data for $7 - $93. PacBio sequencing is according the same webpage $115 per Gbp, however at our sequencing center it's ~$200. Though ONT might have already a cheaper solution. Edit, I just found a google sheat with prices that seems to be frequently updated, seems that the ratio still holds Illumina short reads ~10x cheaper than PacBio.
- RNA-seq (i.e. analysis of a gene expression) is not possible with PacBio due to preferential sequencing of smaller fragments; shorter genes would always be shown to be more expressed. To be clear, it's possible to sequence RNA with PacBio (the keyword is iso-seq), but the analysis of gene expression is problematic.
- It's way easier to extract fragmented DNA (concerns small non-model organisms; although recently a single mosquito was sequenced, so we can expect a further improvement)
- other sequencing techniques as RAD-seq that allow genotyping with very little effort and cost, I have never seen anybody even considering using long reads for such genotyping
Genome profiling (assembly-less genome evaluation) based on kmer spectra analysis is not possible with PacBio data due to higher error rates. Conflict of interest: I am a developer of one of the tools for genome profiling (smudgeplot)- I bet there will be a plenty other applications I am not aware of
$endgroup$
add a comment |
$begingroup$
Three reasons for Illumina:
* Much better for a large number of samples (easily handle 96 samples).
* SNP calling is much better - much greater depth
* Hardware costs, an Illumina MiSeq machine is cheap
PacBio SNP calling has been improved towards the standard of Illumina by DNA modification to the inputs to be sequenced but it depends on the application.
$endgroup$
add a comment |
$begingroup$
Many analyses performed on Illumina machines these days require large numbers of reads. For example, most analyses in ChIP-seq, RNA-seq, ATAC-seq etc, need 10s or even 100s of millions of reads for the statistics to work out properly.
But this isn't limited to just sequencing as an assay experiments. High depths are important for things like somatic variant calling as well. Or simply sequencing of medical gene pannels, where you might only have 20 amplicons of a 500bp each, but need to do it on 100s of patients as cheaply as possible.
$endgroup$
add a comment |
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3 Answers
3
active
oldest
votes
3 Answers
3
active
oldest
votes
active
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votes
active
oldest
votes
$begingroup$
There are so many reasons why one might want to prefer Illumina over PacBio (also note that it's a false dichotomy, at least Oxford Nanopore is a competitive sequencing platform):
- The first (IMHO and the most common reason) is still the cost of both sequencing and the instruments. Illumina can sequence a Gbp of data for $7 - $93. PacBio sequencing is according the same webpage $115 per Gbp, however at our sequencing center it's ~$200. Though ONT might have already a cheaper solution. Edit, I just found a google sheat with prices that seems to be frequently updated, seems that the ratio still holds Illumina short reads ~10x cheaper than PacBio.
- RNA-seq (i.e. analysis of a gene expression) is not possible with PacBio due to preferential sequencing of smaller fragments; shorter genes would always be shown to be more expressed. To be clear, it's possible to sequence RNA with PacBio (the keyword is iso-seq), but the analysis of gene expression is problematic.
- It's way easier to extract fragmented DNA (concerns small non-model organisms; although recently a single mosquito was sequenced, so we can expect a further improvement)
- other sequencing techniques as RAD-seq that allow genotyping with very little effort and cost, I have never seen anybody even considering using long reads for such genotyping
Genome profiling (assembly-less genome evaluation) based on kmer spectra analysis is not possible with PacBio data due to higher error rates. Conflict of interest: I am a developer of one of the tools for genome profiling (smudgeplot)- I bet there will be a plenty other applications I am not aware of
$endgroup$
add a comment |
$begingroup$
There are so many reasons why one might want to prefer Illumina over PacBio (also note that it's a false dichotomy, at least Oxford Nanopore is a competitive sequencing platform):
- The first (IMHO and the most common reason) is still the cost of both sequencing and the instruments. Illumina can sequence a Gbp of data for $7 - $93. PacBio sequencing is according the same webpage $115 per Gbp, however at our sequencing center it's ~$200. Though ONT might have already a cheaper solution. Edit, I just found a google sheat with prices that seems to be frequently updated, seems that the ratio still holds Illumina short reads ~10x cheaper than PacBio.
- RNA-seq (i.e. analysis of a gene expression) is not possible with PacBio due to preferential sequencing of smaller fragments; shorter genes would always be shown to be more expressed. To be clear, it's possible to sequence RNA with PacBio (the keyword is iso-seq), but the analysis of gene expression is problematic.
- It's way easier to extract fragmented DNA (concerns small non-model organisms; although recently a single mosquito was sequenced, so we can expect a further improvement)
- other sequencing techniques as RAD-seq that allow genotyping with very little effort and cost, I have never seen anybody even considering using long reads for such genotyping
Genome profiling (assembly-less genome evaluation) based on kmer spectra analysis is not possible with PacBio data due to higher error rates. Conflict of interest: I am a developer of one of the tools for genome profiling (smudgeplot)- I bet there will be a plenty other applications I am not aware of
$endgroup$
add a comment |
$begingroup$
There are so many reasons why one might want to prefer Illumina over PacBio (also note that it's a false dichotomy, at least Oxford Nanopore is a competitive sequencing platform):
- The first (IMHO and the most common reason) is still the cost of both sequencing and the instruments. Illumina can sequence a Gbp of data for $7 - $93. PacBio sequencing is according the same webpage $115 per Gbp, however at our sequencing center it's ~$200. Though ONT might have already a cheaper solution. Edit, I just found a google sheat with prices that seems to be frequently updated, seems that the ratio still holds Illumina short reads ~10x cheaper than PacBio.
- RNA-seq (i.e. analysis of a gene expression) is not possible with PacBio due to preferential sequencing of smaller fragments; shorter genes would always be shown to be more expressed. To be clear, it's possible to sequence RNA with PacBio (the keyword is iso-seq), but the analysis of gene expression is problematic.
- It's way easier to extract fragmented DNA (concerns small non-model organisms; although recently a single mosquito was sequenced, so we can expect a further improvement)
- other sequencing techniques as RAD-seq that allow genotyping with very little effort and cost, I have never seen anybody even considering using long reads for such genotyping
Genome profiling (assembly-less genome evaluation) based on kmer spectra analysis is not possible with PacBio data due to higher error rates. Conflict of interest: I am a developer of one of the tools for genome profiling (smudgeplot)- I bet there will be a plenty other applications I am not aware of
$endgroup$
There are so many reasons why one might want to prefer Illumina over PacBio (also note that it's a false dichotomy, at least Oxford Nanopore is a competitive sequencing platform):
- The first (IMHO and the most common reason) is still the cost of both sequencing and the instruments. Illumina can sequence a Gbp of data for $7 - $93. PacBio sequencing is according the same webpage $115 per Gbp, however at our sequencing center it's ~$200. Though ONT might have already a cheaper solution. Edit, I just found a google sheat with prices that seems to be frequently updated, seems that the ratio still holds Illumina short reads ~10x cheaper than PacBio.
- RNA-seq (i.e. analysis of a gene expression) is not possible with PacBio due to preferential sequencing of smaller fragments; shorter genes would always be shown to be more expressed. To be clear, it's possible to sequence RNA with PacBio (the keyword is iso-seq), but the analysis of gene expression is problematic.
- It's way easier to extract fragmented DNA (concerns small non-model organisms; although recently a single mosquito was sequenced, so we can expect a further improvement)
- other sequencing techniques as RAD-seq that allow genotyping with very little effort and cost, I have never seen anybody even considering using long reads for such genotyping
Genome profiling (assembly-less genome evaluation) based on kmer spectra analysis is not possible with PacBio data due to higher error rates. Conflict of interest: I am a developer of one of the tools for genome profiling (smudgeplot)- I bet there will be a plenty other applications I am not aware of
edited Feb 5 at 8:26
answered Jan 31 at 16:12
Kamil S JaronKamil S Jaron
2,736639
2,736639
add a comment |
add a comment |
$begingroup$
Three reasons for Illumina:
* Much better for a large number of samples (easily handle 96 samples).
* SNP calling is much better - much greater depth
* Hardware costs, an Illumina MiSeq machine is cheap
PacBio SNP calling has been improved towards the standard of Illumina by DNA modification to the inputs to be sequenced but it depends on the application.
$endgroup$
add a comment |
$begingroup$
Three reasons for Illumina:
* Much better for a large number of samples (easily handle 96 samples).
* SNP calling is much better - much greater depth
* Hardware costs, an Illumina MiSeq machine is cheap
PacBio SNP calling has been improved towards the standard of Illumina by DNA modification to the inputs to be sequenced but it depends on the application.
$endgroup$
add a comment |
$begingroup$
Three reasons for Illumina:
* Much better for a large number of samples (easily handle 96 samples).
* SNP calling is much better - much greater depth
* Hardware costs, an Illumina MiSeq machine is cheap
PacBio SNP calling has been improved towards the standard of Illumina by DNA modification to the inputs to be sequenced but it depends on the application.
$endgroup$
Three reasons for Illumina:
* Much better for a large number of samples (easily handle 96 samples).
* SNP calling is much better - much greater depth
* Hardware costs, an Illumina MiSeq machine is cheap
PacBio SNP calling has been improved towards the standard of Illumina by DNA modification to the inputs to be sequenced but it depends on the application.
answered Jan 31 at 11:33
Michael G.Michael G.
3951213
3951213
add a comment |
add a comment |
$begingroup$
Many analyses performed on Illumina machines these days require large numbers of reads. For example, most analyses in ChIP-seq, RNA-seq, ATAC-seq etc, need 10s or even 100s of millions of reads for the statistics to work out properly.
But this isn't limited to just sequencing as an assay experiments. High depths are important for things like somatic variant calling as well. Or simply sequencing of medical gene pannels, where you might only have 20 amplicons of a 500bp each, but need to do it on 100s of patients as cheaply as possible.
$endgroup$
add a comment |
$begingroup$
Many analyses performed on Illumina machines these days require large numbers of reads. For example, most analyses in ChIP-seq, RNA-seq, ATAC-seq etc, need 10s or even 100s of millions of reads for the statistics to work out properly.
But this isn't limited to just sequencing as an assay experiments. High depths are important for things like somatic variant calling as well. Or simply sequencing of medical gene pannels, where you might only have 20 amplicons of a 500bp each, but need to do it on 100s of patients as cheaply as possible.
$endgroup$
add a comment |
$begingroup$
Many analyses performed on Illumina machines these days require large numbers of reads. For example, most analyses in ChIP-seq, RNA-seq, ATAC-seq etc, need 10s or even 100s of millions of reads for the statistics to work out properly.
But this isn't limited to just sequencing as an assay experiments. High depths are important for things like somatic variant calling as well. Or simply sequencing of medical gene pannels, where you might only have 20 amplicons of a 500bp each, but need to do it on 100s of patients as cheaply as possible.
$endgroup$
Many analyses performed on Illumina machines these days require large numbers of reads. For example, most analyses in ChIP-seq, RNA-seq, ATAC-seq etc, need 10s or even 100s of millions of reads for the statistics to work out properly.
But this isn't limited to just sequencing as an assay experiments. High depths are important for things like somatic variant calling as well. Or simply sequencing of medical gene pannels, where you might only have 20 amplicons of a 500bp each, but need to do it on 100s of patients as cheaply as possible.
answered Jan 31 at 12:37
Ian SudberyIan Sudbery
2,411217
2,411217
add a comment |
add a comment |
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$begingroup$
PacBio used to have high error rates and the expensive libraries with low throughput. In terms of transcriptome, its not quantitative, needs to generate several libraries with different fragment lengths, again not quantitative, captures only abundant transcripts, misses LncRNAs.
$endgroup$
– geek_y
Jan 31 at 6:29
1
$begingroup$
@geek_y Can you please elaborate in details, and if possible with reference? Your answer will be useful for our users, not just myself!
$endgroup$
– SmallChess
Jan 31 at 6:32
2
$begingroup$
IMHO not all NGS questions are about bioinformatics, @gringer, and not all bioinformatics has to do with NGS. So I kindly disagree with your statement about "Bioinformatics includes NGS". This question is about the specs of different platforms, and could be asked on a forum such as SEQanswers.
$endgroup$
– benn
Jan 31 at 9:53
2
$begingroup$
@benn Analyzing NGS data is very much a part of bioinformatics. By extension, the generation of NGS data is also on topic here since it is very relevant to the job of the bioinformatician who will analyze them. I don't understand why you would consider this off topic. We've even had a meta discussion about this sort of thing and the consensus was clear: biological questions are on topic when they are relevant to bioinformatics.
$endgroup$
– terdon♦
Jan 31 at 10:08
2
$begingroup$
The close votes claim that this question is opinion-based, but there are some very objective answers to the question of which sequencing platform to choose. I think the question itself could be re-worded a bit, but it's definitely an on-topic discussion.
$endgroup$
– Daniel Standage
Jan 31 at 14:09