Why Illumina if PacBio provides longer and better reads?












5












$begingroup$


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?










share|improve this question











$endgroup$








  • 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
















5












$begingroup$


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?










share|improve this question











$endgroup$








  • 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














5












5








5


1



$begingroup$


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?










share|improve this question











$endgroup$




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






share|improve this question















share|improve this question













share|improve this question




share|improve this question








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














  • 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










3 Answers
3






active

oldest

votes


















6












$begingroup$

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






share|improve this answer











$endgroup$





















    3












    $begingroup$

    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.






    share|improve this answer









    $endgroup$





















      3












      $begingroup$

      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.






      share|improve this answer









      $endgroup$













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        3 Answers
        3






        active

        oldest

        votes








        3 Answers
        3






        active

        oldest

        votes









        active

        oldest

        votes






        active

        oldest

        votes









        6












        $begingroup$

        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






        share|improve this answer











        $endgroup$


















          6












          $begingroup$

          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






          share|improve this answer











          $endgroup$
















            6












            6








            6





            $begingroup$

            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






            share|improve this answer











            $endgroup$



            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







            share|improve this answer














            share|improve this answer



            share|improve this answer








            edited Feb 5 at 8:26

























            answered Jan 31 at 16:12









            Kamil S JaronKamil S Jaron

            2,736639




            2,736639























                3












                $begingroup$

                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.






                share|improve this answer









                $endgroup$


















                  3












                  $begingroup$

                  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.






                  share|improve this answer









                  $endgroup$
















                    3












                    3








                    3





                    $begingroup$

                    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.






                    share|improve this answer









                    $endgroup$



                    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.







                    share|improve this answer












                    share|improve this answer



                    share|improve this answer










                    answered Jan 31 at 11:33









                    Michael G.Michael G.

                    3951213




                    3951213























                        3












                        $begingroup$

                        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.






                        share|improve this answer









                        $endgroup$


















                          3












                          $begingroup$

                          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.






                          share|improve this answer









                          $endgroup$
















                            3












                            3








                            3





                            $begingroup$

                            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.






                            share|improve this answer









                            $endgroup$



                            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.







                            share|improve this answer












                            share|improve this answer



                            share|improve this answer










                            answered Jan 31 at 12:37









                            Ian SudberyIan Sudbery

                            2,411217




                            2,411217






























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