Calculates a Spearman correlation coefficient (rho), in the case of ties, averages the ranks
and returns a Pearson correlation coefficient on the ranks.
Generates multiplicative scalars based on a set of points using a combination of a cubic spline for values within the provided points
and linear regression for points outside the value range.
For bulk file upload should be 23 cells
0 Name
1 Alias
2 Source
4 Reference
5 Type Bacteria, Yeast, Worm, Insect, Plant, Fish, Cell Line, Bird, Mammal or Other
6 Recipients
7 Organism name
8 Markers names, comma seperated
9 Plasmid Ids
10 Parent Strain Ids
11 Storage Location
12 Mutagen EMS, ENU, MMS, MNU, X-ray, UV, Transposon, T-DNA, Spontaneous or Other
13 Genotype/ Background
14 Phenotype
15 Growth Conditions
16 Restock
17 Remaining Aliquots
18 Array Type Extra Chromosomal or Integration
19 Seed Type Individual Line, Individual Pool, Set of Lines, or Set of Pools
20 Cell Type (Cell Lines)
21 Passage Number ( Cell Lines)
22 Mating Type ( Yeast) diploid, a, alpha, h+, or h-)
23 Availability
24 Visibility
25 Notes
Use something like -> gene|ncRNA|snoRNA|tRNA|rRNA|transposable_element|pseudogene|CDS|mRNA|exon
Only those gff lines with a type matching this regular expression will be made into GFF3Feature's.
Returns a collection of sgr lines representing the gff feature:
1) seqId startMin1 0
2) seqId start score
3) seqId end score
4) seqId endPlus1 0
Does not include a final return, thus println(gff.sgrBundle()).
Safely splits a three item, colon delimited concat (ie 3: zyx:4-99: 235, 3999) into a String[3],
OK to have internal colons provided no space follows the colon.
Splits a String on a regular expression, watching out for escaped characters
ie Cat\=Mouse would not be split when = is given as the regex, a String[0],
{"Cat\=Mouse"} would be returned.