hernan if you need some help you can also find a smart student and ask ESUG to sponsor him during a summertalk. Stef Le 26/1/15 21:03, Hernán Morales Durand a écrit :
2015-01-26 9:01 GMT-03:00 Sven Van Caekenberghe <sven@stfx.eu <mailto:sven@stfx.eu>>:
Hernán,
> On 26 Jan 2015, at 08:00, Hernán Morales Durand <hernan.morales@gmail.com <mailto:hernan.morales@gmail.com>> wrote: > > It is possible :) > I work with DNA sequences, there could be millions of common SNPs in a genome.
Still weird for CSV. How many record are there then ?
We genotyped few individuals (24 records) but now we have a genotyping platform (GeneTitan) with array plates allowing up to 96 samples, which is up to 2.6 million of markers. The first run I completed generated CSVs of 1 million of records (see attach). Sadly the high-level analysis of this data (annotation, clustering, discrimination) now is performed with R with packages like SNPolisher.
And this is microarray analysis, NGS platforms produce larger volumes of data in a shorter period of time (several genomes in a day). See http://www.slideshare.net/allenday/renaissance-in-medicine-strata-nosql-and-... for the 2014-2020 predictions.
Feel free to contact me if you want to experiment with metrics.
I assume they all have the same number of fields ?
Yes, never seen CSV file with variable number of fields (in this domain)
Anyway, could you point me to the specification of the format you want to read ?
Actually I have no rush for this, I want to avoid awk, sed and shell scripts in the next run. I would like to avoid Python but spreads like a virus.
I will be working mostly with CSV's from Axiom annotation files [1] and genotyping results. Other file formats I use are genotype file formats for programs like PLINK [2] (PED files, column 7 onwards) and HaploView. Is worst than you might think, because you have to transpose the output generated by genotyping platforms (millions of records), and then filter & cut them by chromosome because those Java programs cannot deal with all chromosomes at the same time.
And to the older the that you used to use ?
http://www.smalltalkhub.com/#!/~hernan/CSV <http://www.smalltalkhub.com/#%21/%7Ehernan/CSV>
Cheers, Hernán
[1] http://www.affymetrix.com/support/technical/annotationfilesmain.affx [2] http://pngu.mgh.harvard.edu/~purcell/plink/data.shtml#ped <http://pngu.mgh.harvard.edu/%7Epurcell/plink/data.shtml#ped>
Thx,
Sven
> Cheers, > > Hernán > > > 2015-01-26 3:33 GMT-03:00 Sven Van Caekenberghe <sven@stfx.eu <mailto:sven@stfx.eu>>: > > > On 26 Jan 2015, at 06:32, Hernán Morales Durand <hernan.morales@gmail.com <mailto:hernan.morales@gmail.com>> wrote: > > > > > > > > 2015-01-23 18:00 GMT-03:00 Sven Van Caekenberghe <sven@stfx.eu <mailto:sven@stfx.eu>>: > > > > > On 23 Jan 2015, at 20:53, Hernán Morales Durand <hernan.morales@gmail.com <mailto:hernan.morales@gmail.com>> wrote: > > > > > > Hi Sven, > > > > > > 2015-01-23 16:06 GMT-03:00 Sven Van Caekenberghe <sven@stfx.eu <mailto:sven@stfx.eu>>: > > > Hi Hernán, > > > > > > > On 23 Jan 2015, at 19:50, Hernán Morales Durand <hernan.morales@gmail.com <mailto:hernan.morales@gmail.com>> wrote: > > > > > > > > I used to use a CSV parser from Squeak where I could attach conditional iterations: > > > > > > > > csvParser rowsSkipFirst: 2 do: [: row | " some action ignoring first 2 fields on each row " ]. > > > > csvParser rowsSkipLast: 2 do: [: row | " some action ignoring last 2 fields on each row " ]. > > > > > > With NeoCSVParser you can describe how each field is read and converted, using the same mechanism you can ignore fields. Have a look at the senders of #addIgnoredField from the unit tests. > > > > > > > > > I am trying to understand the implementation, I see you included #addIgnoredFields: for consecutive fields in Neo-CSV-Core-SvenVanCaekenberghe.21 > > > A question about usage then, adding ignored field(s) requires adding field types on all other remaining fields? > > > > Yes, like this: > > > > testReadWithIgnoredField > > | input | > > input := (String crlf join: #( '1,2,a,3' '1,2,b,3' '1,2,c,3' '')). > > self > > assert: ((NeoCSVReader on: input readStream) > > addIntegerField; > > addIntegerField; > > addIgnoredField; > > addIntegerField; > > upToEnd) > > equals: { > > #(1 2 3). > > #(1 2 3). > > #(1 2 3).} > > > > > > > > May be you like to know if you make a pass to NeoCSV, for some data sets I have 1 million of columns, it would be nice an addFieldsInterval: or such. > > 1 million columns ? How is that possible, useful ? > > The reader is like a builder. You could try to do this yourself by writing a little loop or two. > > But still, 1 million ? > > > Thank you. > > > > Hernán > > > > >