Hi all, very quickly because at the moment I am in London with an intermittent connection.
The quality scores are computed as follows: for each read,
all the existing mappings for both ends are found up to a (very high) number of substitutions/indels/splices
a score is computed for each mapping: the more unique the mapping, the better the score.
Hence the scores are relative, not absolute: their purpose is that of deciding which mapping is the best one among its fellows, not to stratify all the mappings in the SAM file by their number of errors (which you can very well do in the obvious way, since the number of mismatches is recorded in the NM field).
For instance: the first mapping for the first pair you consider,
has an overall quality score of 180. This is due to the fact that there are several mappings, but the best one (the one described in the regular SAM record), to chr1:14704/chr1:14770 is anyway better than the second best one (the one to chr15,-102516387/chr15,+102516328 described in the XA optional field). In fact, the mapping to chr1 has 7 mismatches (following GEM's scoring system), while the mapping to chr15 has 8 mismatches. So: in absolute terms all mappings are bad because the second end does not map well to any position, but still one can say that the mapping to chr1 is better than the other ones, and this is why it gets a high relative score.
If for some reason you feel uncomfortable with using mapping having a high number of mismacthes (which is an absolute score), you can easily filter them out based on the NM tag, or on other criteria (for instance, if you had filtered out mappings with NM>5 this pair would have disappeared).
Hope this clarifies things. I do not have the time now to explain how the relative score is computed, but I will be happy to do that if you are interested. Best, -------Paolo
I noticed the read length discordance myself very recently, and
was going to bring it up. This is really unfortunate - people
processing the data in Barcelona didn't follow the explicit
instructions of submitting 75 bp data. This is something that I
should have checked though, and I thought I had, but apparently I
didn't for the mRNA data. However, I don't think this will really
affect things. The Barcelona samples don't show worse mapping
stats, and I definitely don't want to remap these samples without
a very strong reason.
Regarding the GEM mapping quality scores, Paolo, Thasso and
Micha, can you please comment on this? Matthias and
Daniela, what do you mean by referring to the example reads as
being well or badly mapped? The classifications below is the
information I have from Paolo, but I don't know the algorithms
that they use to calculate the MAPQ. In my understanding the
qualities are calculated independently for the two mates. I'm
using reads with MAPQ >150, i.e. reads in categories 1 and 2
below. It depends on the analysis whether I require both mates to
have this quality (e.g. exon quantifications) or if I can just use
a single good-quality mate regardless of the quality of its mate
(e.g. ASE).
Matches which are unique, and do not have any subdominant
match:
251 >= MAPQ >= 255, XT=U
Matches which are unique, and have subdominant matches but a
different score:
175 >= MAPQ >= 181, XT=U
Matches which are putatively unique (not unique, but
distinguishable by score):
119 >= MAPQ >= 127, XT=U
Matches which are a perfect tie:
78 >= MAPQ >= 90, XT=R.
best regards,
Tuuli
Tuuli Lappalainen, PhD
Department of Genetic Medicine and Development
University of Geneva Medical School
CMU / Rue Michel-Servet 1
1211 Geneva 4
Switzerland
Tel. +41-(0)22-3795550tuuli.lappalainen@unige.ch
On 7/4/12 3:24 PM, Matthias Barann wrote:
Dear all,
we noticed some inconsistencies in the read lengths of the GEM
mappings (I didn't check the BWA mappings, but it's probably the
same).
Some samples appear to have up to 76 bp matched, while other
samples only have 75 bp. In regard to comparability this might
cause some (probably very little) differences between the samples.
i.e.
NA20589.1.M_111124_3.bam has 75 bp
NA20812.2.M_111216_6.bam has 76 bp
NA20760.3.M_120202_5.bam has 75 bp
NA20783.4.M_120208_6.bam has 75 bp
NA20768.5.M_120131_1.bam has 75 bp
NA20798.6.M_120119_6.bam has 75 bp
NA20803.7.M_120219_1.bam has 75 bp
We checked some more files for institute 2, and they seem to have
generally 1 bp more than the others.
We're also a bit lost regarding GEM's quality score. We would like
to filter reads for good mapping quality, we're just not sure how
to accomplish this.
Below are two read pairs as an example.
The fist pair has a mapping quality of 180. The second read
however was terribly aligned.
The second pair has only a quality of 99, while the reads mapped
much better (at least I would say so).
We're not sure what's the reason for this.
Curiously, both reads of a pair get the same mapping quality. This
could be by intention (i.e. it's always the pair quality rather
than the read quality) or, which could also explain the quality
differences for the reads, both reads of the pair get the quality
of the first mapped read.
We're thankful for any suggestions on how to filter for 'good'
mappings.
--
Matthias Barann
Institute of Clinical Molecular Biology
Christian Albrechts University Kiel
Schittenhelmstr. 12
D-24105 Kiel, Germany
m.barann@ikmb.uni-kiel.de+49 - (0)431 - 597 8681 (office)