TopHat -paired end vs single end reads

[zun]

hello anurag.gautam,

I also have used tophat series with same O.sativa reads since 2010,
but I haven't encountered the same situation as yours.
In fact the number of mapped reads varied a little, but not drastically like your case.....hmm I don't know the reason why, sorry...

> adarshjose
I had a same problem before, and realized that was because tophat abandoned the mate pairs which mapped on different chromosomes when uniting the left/right reads mapped by bowtie.
but tophat2 has a option called "--report-discordant-pair-alignment" which allows mate pairs to map to different chromosomes.
so you will get higher mapping rate with tophat2...
hope this will help you....

zun

[anurag.gautam]

Reference genome of ORyza sativa indica is of good quality and has good coverage. The reads are also of higher quality. , But still the question remains the same , why different mapping stats?

[pbluescript]

Yes both are same
Tophat1.1.4 2,000,000 227,554
Tophat1.3.0 2,000,000 230,817
Tophat1.3.1 2,000,000 231,935
Tophat1.3.2 2,000,000 4,517
Tophat1.3.3 2,000,000 231,935
Tophat1.4.1 2,000,000 137,724

That's not a lot of mapped reads. Either something went wrong with the library prep, sequencing, or mapping method. How good is the reference genome for Oryza sativa indica?

[anurag.gautam]

Yes both are same
Tophat1.1.4 2,000,000 227,554
Tophat1.3.0 2,000,000 230,817
Tophat1.3.1 2,000,000 231,935
Tophat1.3.2 2,000,000 4,517
Tophat1.3.3 2,000,000 231,935
Tophat1.4.1 2,000,000 137,724

[pbluescript]

Hi ,
I tried to map illumina ~2 million reads to Oryza sativa indica reference genome with its reference gtf file using different versions of Tophat 1.1.4, 1.3.0, 1.3.1, 1.3.2, 1.3.3 and the current one 1.4.1 .
I used the defalut options just to check if the mapping statistics really gets affected. As a result, I got the following stats:
Reads Used Reads Mapped
Tophat1.1.4 2,000,000 2,27,554
Tophat1.3.0 2,000,000 2,30,817
Tophat1.3.1 2,000,000 2,31,935
Tophat1.3.2 2,000,000 4,517
Tophat1.3.3 2,000,000 2,31,935
Tophat1.4.1 2,000,000 1,37,724

I wanted to know why the number of reads mapped is varying in each version even though using the same data. Secondly, why there is a drastic change in the mapping stats with version 1.3.2 and 1.4.1 as compared with other versions? Can please anybody throw some light on this matter

Could you fix your comma placement? I don't know how many alignments Tophat gave you. Does 2,27,554 mean 227,554?

[anurag.gautam]

Hi ,
I tried to map illumina ~2 million reads to Oryza sativa indica reference genome with its reference gtf file using different versions of Tophat 1.1.4, 1.3.0, 1.3.1, 1.3.2, 1.3.3 and the current one 1.4.1 .
I used the defalut options just to check if the mapping statistics really gets affected. As a result, I got the following stats:
Reads Used Reads Mapped
Tophat1.1.4 2,000,000 2,27,554
Tophat1.3.0 2,000,000 2,30,817
Tophat1.3.1 2,000,000 2,31,935
Tophat1.3.2 2,000,000 4,517
Tophat1.3.3 2,000,000 2,31,935
Tophat1.4.1 2,000,000 1,37,724

I wanted to know why the number of reads mapped is varying in each version even though using the same data. Secondly, why there is a drastic change in the mapping stats with version 1.3.2 and 1.4.1 as compared with other versions? Can please anybody throw some light on this matter

[jameslz]

The reads may be trimmed....

[arrchi]

Hi adarshjose,

Did you solve your problem? I would be very interested in how you solved the discrepancy.

-a

[arrchi]

Hi adarshjose,

Did you solve your problem? I would be very interested in how you solved the discrepancy.

-a

[sphil]

hey,

probably the distance between your paired-ends is to high such that TopHat isn't able to map it accurate to the source sequence. This could result of a high standard deviation in the sample prep. of the reads you use (i.e. too large clone libraries).
If you map the read on their own they could be mapped because the information of mate pairs doesn't really matter in such a case. Try to enlarge the possible gaps while using TopHat and review the results.

Don't know if it really helps but i guess that this could be a reason.


cheers

phil

[adarshjose]

Hi,

I was trying to map paired end Illumina GA IIE 85 bp reads to a reference genome using TopHat. When I tried to map both the pairs together only a small fraction (< 10 % ) of the reads mapped to the genome, but > 80 % of the reads mapped to the reference when I mapped the pairs separately.

mapping using each paired end data separately:
tophat -r 200 -o ./tophatr200 Ref/Zm.seq.uniq seqs__filtered_6_1.fastq
tophat -r 200 -o ./tophatr200 Ref/Zm.seq.uniq seqs__filtered_6_2.fastq

(> 80 % of reads mapped here.)

mapping paired data together:
tophat -r 200 -o ./tophatr200 Ref/Zm.seq.uniq seqs__filtered_6_1.fastq seqs__filtered_6_2.fastq

(< 10 % of reads mapped here.)

Has anyone seen this before ? Could this have something to do with the -r value ? Any suggestion will be greatly appreciated.

Thanks

Adarsh Jose
Iowa State University