SEQanswers

Go Back   SEQanswers > Bioinformatics > Bioinformatics



Similar Threads
Thread Thread Starter Forum Replies Last Post
transcripts missing from cufflinks djm2007 RNA Sequencing 3 05-29-2013 11:39 PM
fetch transcripts assembled by cufflinks asling Bioinformatics 6 09-27-2012 09:46 PM
Cufflinks Annotated Transcripts magarolo RNA Sequencing 1 12-08-2011 01:34 AM
Visualizing novel transcripts through cufflinks adrian Bioinformatics 0 06-13-2011 08:07 AM
transcripts by cufflinks and cuffdiff mrfox Bioinformatics 1 11-22-2010 05:44 PM

Reply
 
Thread Tools
Old 09-03-2010, 12:19 PM   #1
IrisZhu
Member
 
Location: Maryland

Join Date: Jul 2010
Posts: 25
Default cufflinks generated >400,000 transcripts??

I've tried using tophat and cufflinks on 3 different sets of data, at least two of which I know are of very high quality. I was surprised by the output of cufflinks --- it generated > 400,000 transcripts!!

Could anybody tell me how many transcripts you got from tophat - cufflinks pipeline?

Thank you in advance!

Iris
IrisZhu is offline   Reply With Quote
Old 09-04-2010, 12:44 AM   #2
GKM
Member
 
Location: Pasadena, CA

Join Date: May 2009
Posts: 45
Default

Cufflinks will report anything it sees, it is your job to filter the garbage out after that. Use cuffcompare to compare against the annotation, this will tell you which ones are known transcripts, novel isoforms of known genes and novel intergenic transcripts, and also which are things that you probably don't want to deal with like intronic leftovers, polymerase post-3' run on fragments, etc.

Also, note that Cufflinks will produce three values for each transcript - it's best guess FPKM estimate, and 95% confidence values on each side. For a lot of transcripts those three values will be 0, a very small number, and another very small, although somewhat bigger number. You probably want those out too if you want to be stringent.

The above should bring down the number of transcripts significantly.
GKM is offline   Reply With Quote
Old 09-05-2010, 04:04 AM   #3
IrisZhu
Member
 
Location: Maryland

Join Date: Jul 2010
Posts: 25
Default

Quote:
Originally Posted by GKM View Post
Cufflinks will report anything it sees, it is your job to filter the garbage out after that. Use cuffcompare to compare against the annotation, this will tell you which ones are known transcripts, novel isoforms of known genes and novel intergenic transcripts, and also which are things that you probably don't want to deal with like intronic leftovers, polymerase post-3' run on fragments, etc.

Also, note that Cufflinks will produce three values for each transcript - it's best guess FPKM estimate, and 95% confidence values on each side. For a lot of transcripts those three values will be 0, a very small number, and another very small, although somewhat bigger number. You probably want those out too if you want to be stringent.

The above should bring down the number of transcripts significantly.
Thanks a lot for your reply . I did use cuffcompare to check the output against a reference genome: Homo_sapiens.GRCh37.59.gtf downloaded from Ensembl and only got ~7000-9000 (2% of the total output and <20% of the reference transcripts) transcripts matching with the reference:
this is from one dataset:
>>cut -f3 transcripts.tmap |sort|uniq -c
8646 =
56845 c
1 class_code
26512 e
230788 i
10697 j
8367 o
20707 p
212179 u
which makes me (actually not me, my boss) doubt if I use tophat/cufflinks properly or not. I would expect a much better recovery of the annotated transcripts since I got a very good coverage after mapping the same set of reads directly to the transcriptome with bowtie.

Last edited by IrisZhu; 09-05-2010 at 05:47 AM.
IrisZhu is offline   Reply With Quote
Old 09-09-2010, 10:16 AM   #4
chrisbala
Member
 
Location: North Carolina

Join Date: Jan 2010
Posts: 82
Default filtering cufflinks transcripts

I have a similar situation (and I guess this is common) to have a large number of predicted transcripts from cufflinks.

I'm trying to adjust the pre-mrna fraction (-j) to see if this helps at all (as it seems that some of my transcripts are might be from premrna. )

does anyone else have any suggestions about how to filter out the junk? Afterall its sort of hard to know what junk is?

Low coverage stuff makes some sense. But is there a way in cufflinks to require that a transcript be represented by some # of reads in advance?

Are there any other filters that come to mind? Many of my dubious transcripts are very short, and unspliced, would it be too risky to filter on such features? hmmm probably yes.
chrisbala is offline   Reply With Quote
Old 09-24-2010, 11:45 AM   #5
aulyanov
Junior Member
 
Location: Washington, DC

Join Date: Feb 2010
Posts: 1
Default

In my case it is even worse. I have a goal to discover alternative spliced genes using CuffLink. I took gene-by-gene approach and submitted only a fraction of the sam file that cover a region of the interest. So far I have got only 50% recovery of main RefSeq transcripts and lot of false-positive two-exon transcripts with score 1000. The only explanation I have is that I use bwa but not TopHat to align the reads.
aulyanov is offline   Reply With Quote
Old 03-02-2011, 03:28 PM   #6
frankyue50
Member
 
Location: CA

Join Date: Nov 2008
Posts: 34
Default

In some cases, I have seen cufflinks give more 1 million transcript. But I checked the authors original paper, they only predicted less 30000 transcript ...
frankyue50 is offline   Reply With Quote
Old 03-03-2011, 12:57 AM   #7
dnusol
Senior Member
 
Location: Spain

Join Date: Jul 2009
Posts: 133
Default

Hi,

I used cufflinks for my Arabidopsis data using the TAIR .gtf file and I only got

41590 =

in my transcripts.tmap file so I donīt know if there is no new isoform that can be found
dnusol is offline   Reply With Quote
Old 03-03-2011, 10:19 AM   #8
frankyue50
Member
 
Location: CA

Join Date: Nov 2008
Posts: 34
Default

But you provided a gtf file ... We were talking about the transcriptome assembly.

Quote:
Originally Posted by dnusol View Post
Hi,

I used cufflinks for my Arabidopsis data using the TAIR .gtf file and I only got

41590 =

in my transcripts.tmap file so I donīt know if there is no new isoform that can be found
frankyue50 is offline   Reply With Quote
Old 03-09-2011, 06:37 AM   #9
plabaj
Member
 
Location: Vienna

Join Date: Oct 2010
Posts: 85
Default

Hi,

If providing a reference GTF file (-G option) is not "permitted/welcome" in your study, you should think about playing with following parameters:
--min-frags-per-transfrag <int> - by default is 10, increasing should produce less transcripts
-A/--small-anchor-fraction <0.0-1.0> - by default is 0.12, decreasing will take into consideration more reads falling on splice junctions -> less one exon transcripts; should help without producing FP transcripts especially for longer reads (>75bp) and paired-end
__________________
Pawel Labaj
plabaj is offline   Reply With Quote
Old 03-09-2011, 06:43 AM   #10
dagarfield
Member
 
Location: Heidelberg, Germany

Join Date: Aug 2010
Posts: 39
Default

How much coverage do you have?
If you have low coverage, and you're predicting transcripts de novo, cufflinks is going to give you a lot of transcripts (because many of your reads don't overlap another one).

-DG
dagarfield is offline   Reply With Quote
Old 05-10-2011, 06:08 AM   #11
oliviera
Member
 
Location: germany

Join Date: Apr 2010
Posts: 31
Default

Dear all,
I have a similar concern. I get 119021 transcripts model
In my case we have generate > 200 Million paired end reads so coverage should be high.
Have you managed to tune your tophat/cuffklinks pipeline to decrease the transcripts model?? And if yes, how?

In addition how do you evaluate the stats from cuffcompare? Here is an example of what I get.
# Query mRNAs : 119021 in 114586 loci (22194 multi-exon transcripts)
# (3456 multi-transcript loci, ~1.0 transcripts per locus)
# Reference mRNAs : 50278 in 31712 loci (44173 multi-exon)
# Corresponding super-loci: 14397
#--------------------| Sn | Sp | fSn | fSp
Base level: 47.9 30.7 - -
Exon level: 18.4 27.7 25.7 38.5
Intron level: 28.7 83.0 29.9 86.5
Intron chain level: 7.1 14.2 15.7 31.3
Transcript level: 0.0 0.0 0.1 0.0
Locus level: 9.7 2.7 14.2 3.9
Missed exons: 155159/300668 ( 51.6%)
Wrong exons: 77024/200099 ( 38.5%)
Missed introns: 162909/243880 ( 66.8%)
Wrong introns: 6774/84272 ( 8.0%)
Missed loci: 15952/31712 ( 50.3%)
Wrong loci: 67846/114586 ( 59.2%)

Total union super-loci across all input datasets: 82472

Olivier
oliviera is offline   Reply With Quote
Old 05-12-2011, 12:51 PM   #12
polyatail
Member
 
Location: New York, NY

Join Date: Dec 2010
Posts: 25
Default

* If you're using paired-end reads, check the cufflinks log to be sure they're aligned and recognized as PE. In other threads, that wasn't the case.

* Tune the anchor length and multiplicity (-a and -g) at the TopHat step. The defaults assume 36 bp single-end reads. For 72 bp PE, we found -a 16 -g 5 produced the best results.

* Provide a tRNA/rRNA mask file to Cufflinks. This will remove some high-coverage single exon transcripts from contamination.

* I, personally, have had success tweaking -A and -j, but not -F in Cufflinks

119k transcripts is not an unreasonable amount for single-end reads. Are you running with a reference annotation (-g in Cufflinks v1) to guide assembly?
polyatail is offline   Reply With Quote
Old 05-15-2014, 08:14 PM   #13
11xinqi
Member
 
Location: china

Join Date: Mar 2011
Posts: 31
Default

Quote:
Originally Posted by chrisbala View Post
I have a similar situation (and I guess this is common) to have a large number of predicted transcripts from cufflinks.

I'm trying to adjust the pre-mrna fraction (-j) to see if this helps at all (as it seems that some of my transcripts are might be from premrna. )

does anyone else have any suggestions about how to filter out the junk? Afterall its sort of hard to know what junk is?

Low coverage stuff makes some sense. But is there a way in cufflinks to require that a transcript be represented by some # of reads in advance?

Are there any other filters that come to mind? Many of my dubious transcripts are very short, and unspliced, would it be too risky to filter on such features? hmmm probably yes.
Hi, do you have any idea about why cufflinks gives a large number of predicted transcripts and how to filter the result now? Thank you.
11xinqi is offline   Reply With Quote
Old 05-15-2014, 08:15 PM   #14
11xinqi
Member
 
Location: china

Join Date: Mar 2011
Posts: 31
Default

Quote:
Originally Posted by IrisZhu View Post
I've tried using tophat and cufflinks on 3 different sets of data, at least two of which I know are of very high quality. I was surprised by the output of cufflinks --- it generated > 400,000 transcripts!!

Could anybody tell me how many transcripts you got from tophat - cufflinks pipeline?

Thank you in advance!

Iris
Hi, do you have any idea about why cufflinks gives a large number of predicted transcripts and how to filter the result now? Thank you.
11xinqi is offline   Reply With Quote
Reply

Thread Tools

Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off




All times are GMT -8. The time now is 05:24 AM.


Powered by vBulletin® Version 3.8.9
Copyright ©2000 - 2019, vBulletin Solutions, Inc.
Single Sign On provided by vBSSO