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The nucleotide sequences ( 250 bp flanking sequences from the translation start site of each strain ’ s phenazine biosynthetic operon ) were aligned and edited using MUSCLE ( MEGA 7 ) .
The cross - correlation method and the significance tests for coefficients are implemented using Python 2.7.5 ( https://www.python.org ) .
Haplotypes were identified using ARLEQUIN 3.11 [33] .
SPM 8 ( http://www.fil.ion.ucl.ac.uk/spm ) was used for analysis .
The first generation Bayesian Evolutionary Analysis by Sampling Trees ( BEAST ) package [1] , [2] has become a popular platform for solving such problems and takes a modeling philosophy that all of these evolutionary analysis problems share at their core one or more phylogenetic time - trees .
We performed both univariate and multivariate analyses .
Statistical analyses were performed in SPSS 19.0 and R 3.0.1 [42] .
SPSS for windows version 20.0 was used .
Then browsing a recent release directory ( e.g. , PhysiCell 1.2.2 ) , and downloading the ova file . https://github.com/MathCancer/PhysiCell/releases/latest
Analyses were conducted using SPSS version 24 for Mac ( IBM SPSS Statistics for Windows , Version 23 .
For this , the statistical program SPSS ( Statistical Package for Social Sciences ) for Windows version 19 was used .
Strawberry is available as a free software at https://github.com/ruolin/strawberry under the MIT license .
A second major version of CellProfiler , rewritten in Python from its original MATLAB implementation , was published in 2011 [5] and included methods for tracking cells in movies and measuring neurons , worms , and tissue samples .
Measurement model analysis was conducted using AMOS 23 , whereas the remaining analyses were computed using SPSS 23 .
All these analyses were performed using GraphPad Prism v 7.0 ( GraphPad Software , La Jolla , CA , USA ) .
All draft genomes were annotated using NCBI ’ s Prokaryotic Genomes Automatic Annotation Pipeline ( PGAAP [40] , ) .
Statistical tests were carried out using SPSS 16.0 ( SPSS Inc . , Chicago , IL ) for Windows .
The statistical analyses were performed with IBM SPSS 20 .
Podbat is open source software implemented as a desktop application in Java and can be freely and anonymously downloaded from www.podbat.org or as supplemental material accompanying this paper ( Software S1 ) .
Statistical analyses were performed using Stata software , version 13 ( StataCorp , College Station , TX , US ) .
We carried out genome - wide association analyses for BMDC using additive linear regression in Mach2QTL for both ALSPAC and GOOD ( using GRIMP [20] for the GOOD analyses ) .
Ensembler is free and open source software licensed under the GNU General Public License ( GPL ) v 2 .
In Family A only , IBD analysis was performed using the HCS genotypes and the BEAGLE software package , Version 3.3.2 [79] .
Data analysis was performed using the Statistical Package for the Social Sciences ( SPSS for Windows , version 19.0 , SPSS Inc , Chicago , IL , USA ) and included frequency distribution and association tests .
We used descriptive statistics to characterize the study population according to SRH .
Absolute differences and relative risks were estimated with the GENMOD procedure in SAS version 9 βˆ™ 3 ( SAS Institute , Cary , N.C . ) The absolute and relative effect of the CCP was estimated for each of the four baseline treatment status groups .
Two separate multiple regression models were used to evaluate the relationships between TL in 2013 and 1 ) β€œ change in number of surviving offspring ( 2000 - 2013 ) ” , maternal age at first birth and average inter - birth interval , as well as 2 ) β€œ total number of surviving offspring ” , maternal age at first birth and average inter - birth interval using JMP ( version 12 ; SAS Institute ) .
Statistical analyses were performed using GraphPad Prism 4.0 for Windows ( GraphPad Software , San Diego California USA ) .
This list provided a content analysis grid to code the entire data .
All of the participants in this investigation agreed to allow the data they provided to be used for research purposes ( Supplementary material , S2 File ) .
The R - packages , tximport [52] and edgeR [53] , were used to respectively summarize the expression at gene - level and normalize the data .
ENMs were developed using a maximum entropy algorithm implemented in the software MaxEnt version 3.3.3k [23] .
SPSS version 15.0 software ( SPSS Inc . 2007 , Chicago , Illinois , USA ) was used for statistical calculations .
The pairwise genetic differentiation values were assumed to measure the extent of DNA divergence between populations , and the significance was tested using 1,000 permutations with Arlequin v. 3.11 [51] .
Data were analyzed using GraphPad Prism version 5.0 for Mac OS X .
Stata version 13.1 ( Stata Corp LP , College Station , Texas ) was used to estimate the analysis models .
We used the Statistical Package for Social Sciences ( IBM SPSS v. 24.0.0.0 ) for all analyses .
Genotyping , logR Ratio ( LRR ) and B - allele - fraction ( BAF ) were corrected and normalized using the Genotyping module from GenomeStudio 2.0 ( Illumina ) and all positions with cluster separation > 0.75 were exported ( 594k SNPs ) for further analysis .
In contrast to the original tool , ggsashimi internally generates an R script which uses the ggplot 2 library [5] for the graphical rendering .
Data were analysed using STATA 12.0 ( Stata Corp , College Station , TX , USA ) .
All quantified regions were analyzed by Multivariate Analysis of Variance ( MANOVA ) for main effects of genotype , competition dose , and genotype x dose interactions using IBM SPSS Statistics 22 .
Data were analysed using a generalised linear mixed model ( GLMM ) in R 3.3.1 [37] using the lme 4 package [38] .
B.O . , S.S .B . and J.B . cross - checked all data .
Statistical analysis was performed using the SPSS and Excel software , version 2010 for Mac .
Baseline data were used , as the CLSA has only recently been launched and follow - up data were , at the time the present study was conducted , not yet available .
The code for Ensembler is hosted on the collaborative open source software development platform GitHub ( github.com / choderalab / ensembler ) .
Since ggsashimi uses the most popular file formats and has very few dependencies , it can be easily integrated in any splicing analysis pipeline , and can facilitate the interrogation of alternative splicing in large - scale RNA sequencing projects , such as ENCODE [6] and GTEx [7] . ggsashimi is freely available at https://github.com/guigolab/ggsashimi .