This function collapses isomiRs into different groups. It is a similar concept than how to work with gene isoforms. With this function, different changes can be put together into a single miRNA variant. For instance all sequences with variants at 3' end can be considered as different elements in the table or analysis having the following naming hsa-miR-124a-5p.iso.t3:AAA.

isoCounts(ids, ref = FALSE, iso5 = FALSE, iso3 = FALSE, add = FALSE,
  subs = FALSE, seed = FALSE, minc = 1, mins = 1)

Arguments

ids

Object of class IsomirDataSeq.

ref

Differentiate reference miRNA from rest.

iso5

Differentiate trimming at 5 miRNA from rest.

iso3

Differentiate trimming at 3 miRNA from rest.

add

Differentiate additions miRNA from rest.

subs

Differentiate nt substitution miRNA from rest.

seed

Differentiate changes in 2-7 nts from rest.

minc

Int minimum number of isomiR sequences to be included.

mins

Int minimum number of samples with number of sequences bigger than minc counts.

Value

IsomirDataSeq object with new count table. The count matrix can be access with counts(ids).

Details

You can merge all isomiRs into miRNAs by calling the function only with the first parameter isoCounts(ids). You can get a table with isomiRs altogether and the reference miRBase sequences by calling the function with ref=TRUE. You can get a table with 5' trimming isomiRS, miRBase reference and the rest by calling with isoCounts(ids, ref=TRUE, iso5=TRUE). If you set up all parameters to TRUE, you will get a table for each different sequence mapping to a miRNA (i.e. all isomiRs).

Examples for the naming used for the isomiRs are at http://seqcluster.readthedocs.org/mirna_annotation.html#mirna-annotation.

Examples

data(mirData) ids <- isoCounts(mirData, ref=TRUE) head(counts(ids))
#> pc2 pt2 pt7 pc1 pt6 pc3 pt3 pt5 #> hsa-let-7a-2-3p.iso 6 3 0 9 2 4 4 0 #> hsa-let-7a-2-3p.ref 5 4 10 4 2 9 5 3 #> hsa-let-7a-3p.iso 782 634 1002 1140 536 857 1169 380 #> hsa-let-7a-3p.ref 146 111 157 153 77 116 192 53 #> hsa-let-7a-5p.iso 96391 84487 126832 124343 76467 96519 136940 41708 #> hsa-let-7a-5p.ref 259187 239647 391118 382703 222561 279317 363483 110483 #> pt4 pc5 pc4 pc7 pc6 pt1 #> hsa-let-7a-2-3p.iso 0 7 10 4 5 0 #> hsa-let-7a-2-3p.ref 0 7 10 2 5 2 #> hsa-let-7a-3p.iso 888 1313 903 1050 516 444 #> hsa-let-7a-3p.ref 90 301 147 169 121 98 #> hsa-let-7a-5p.iso 98125 130896 136026 93118 58277 39226 #> hsa-let-7a-5p.ref 321629 337896 353169 247664 157358 111195
# taking into account isomiRs and reference sequence. ids <- isoCounts(mirData, ref=TRUE, minc=10, mins=6) head(counts(ids))
#> pc2 pt2 pt7 pc1 pt6 pc3 pt3 pt5 #> hsa-let-7a-3p.iso 782 634 1002 1140 536 857 1169 380 #> hsa-let-7a-3p.ref 146 111 157 153 77 116 192 53 #> hsa-let-7a-5p.iso 96391 84487 126832 124343 76467 96519 136940 41708 #> hsa-let-7a-5p.ref 259187 239647 391118 382703 222561 279317 363483 110483 #> hsa-let-7b-3p.iso 1966 1404 1589 1639 1051 1264 1992 566 #> hsa-let-7b-5p.iso 41690 31802 41571 50956 23576 35542 48289 13555 #> pt4 pc5 pc4 pc7 pc6 pt1 #> hsa-let-7a-3p.iso 888 1313 903 1050 516 444 #> hsa-let-7a-3p.ref 90 301 147 169 121 98 #> hsa-let-7a-5p.iso 98125 130896 136026 93118 58277 39226 #> hsa-let-7a-5p.ref 321629 337896 353169 247664 157358 111195 #> hsa-let-7b-3p.iso 1144 2852 1984 1722 875 749 #> hsa-let-7b-5p.iso 32629 46634 45151 32215 19793 14587