Free legionnaires disease software for linux

GeneRecon is a software package for linkage disequilibrium mapping using coalescent theory. GeneRecon project is based on a Bayesian Markov-chain Monte Carlo (MCMC) method for fine-scale linkage-disequilibrium gene mapping using high-density marker maps.
GeneRecon explicitly models the genealogy of a sample of the case chromosomes in the vicinity of a disease locus. Given case and control data in the form of genotype or haplotype information, it estimates a number of parameters, most importantly, the disease position.
GeneRecon is written in C++ and Guile Scheme and is available as source code (under the GNU General Public License, GPL) and as binary versions as Linux RPM files.
The source code has been successfully compiled on various Linux and UNIX systems, under OS X and under Windows with Cygwin.
As I have only limited access to architectures other than Linux, it is not possible for me to make binary distributions for other platforms, but if anyone is willing to build the distributions I will be more than happy to put them on this site.
Installation:
$ tar zxf generecon-version.tar.gz
$ cd generecon-version
$ ./configure
$ make
$ make check
$ make install
Usage:
GeneRecon is started from the command-line; the input data and parameters for the analysis are described in one or more configuration scripts written in the Scheme programming language. Starting GeneRecon with the configuration script input.scm is done as:
$ generecon input.scm
Run generecon --help to get a complete list of command-line options accepted by GeneRecon, or see Getting Started for a quick guide to running GeneRecon.
Enhancements:
- This version fixes an incorrect prior on the coalescent tree that resulted in very long convergence times.
- The fix greatly improves both accuracy and number of iterations needed for accurate mapping.

Blossoc is a linkage disequilibrium association mapping tool that attempts to build (perfect) genealogies for each site in the input, score these according to non-random clustering of affected individuals, and judge high-scoring areas as likely candidates for containing disease affecting variation.
Building the local genealogy trees is based on a number of heuristics that are not guaranteed to build true trees, but have the advantage over more sophisticated methods of being extremely fast. Blossoc can therefore handle much larger data sets than more sophisticated tools, but at the cost of sacrificing some accuracy.
Installation:
Blossoc is written in C++ and is available as source code (under the GNU General Public License, GPL) and as binary versions as Linux RPM files. The source code has been successfully compiled on various Linux and UNIX systems. As I have only limited access to architectures other than Linux, it is not possible for me to make binary distributions for other platforms, but if anyone is willing to build the distributions I will be more than happy to put them on this site.
Usage:
Blossoc is started from the command-line and takes, as input, a file containing the positions of markers and a file containing haplotype data.
The format of the haplotype file is: One line per haplotype, where a haplotype is represented as a list of space-separated alleles, and each allele represented as either a 0 or a 1.
The first column is a pseudo-allele used for the case/control dichotomy: a 0 in the first column is taken to mean that the haplotype is a control haplotype and a 1 at the first column is taken to mean that the haplotype is a case haplotype.
Run blossoc --help to get a complete list of command-line options accepted by Blossoc.
Enhancements:
- This version adds support for unphased genotype data through a perfect-phylogeny haplotyping algorithm.
- If enabled, the release will also support the SNPfile binary format.

Statistics::ROC is a Perl module with receiver-operator-characteristic (ROC) curves with nonparametric confidence bounds.

SYNOPSIS

use Statistics::ROC;

my ($y) = loggamma($x);
my ($y) = betain($x, $p, $q, $beta);
my ($y) = Betain($x, $p, $q);
my ($y) = xinbta($p, $q, $beta, $alpha);
my ($y) = Xinbta($p, $q, $alpha);
my (@rk) = rank($type, @r);
my (@ROC) = roc($model_type,$conf,@val_grp);

This program determines the ROC curve and its nonparametric confidence bounds for data categorized into two groups. A ROC curve shows the relationship of probability of false alarm (x-axis) to probability of detection (y-axis) for a certain test. Expressed in medical terms: the probability of a positive test, given no disease to the probability of a positive test, given disease. The ROC curve may be used to determine an optimal cutoff point for the test.
The main function is roc(). The other exported functions are used by roc(), but might be useful for other nonparametric statistical procedures.

loggamma

This procedure evaluates the natural logarithm of gamma(x) for all x>0, accurate to 10 decimal places. Stirlings formula is used for the central polynomial part of the procedure. For x=0 a value of 743.746924740801 will be returned: this is loggamma(9.9999999999E-324).

betain

Computes incomplete beta function ratio

Remarks:
Complete beta function: B(p,q)=gamma(p)*gamma(q)/gamma(p+q)
log(B(p,q))=ln(gamma(p))+ln(gamma(q))-ln(gamma(p+q))

Incomplete beta function ratio:
I_x(p,q)=1/B(p,q) * int_0^x t^{p-1}*(1-t)^{q-1} dt

--> log(B(p,q)) has to be supplied to calculate I_x(p,q)
log denotes the natural logarithm
$beta = log(B(p,q))
$x = x
$p = p
$q = q
The subroutine returns I_x(p,q). If an error occurs a negative value
{-1,-2} is returned.

Betain

Computes the incomplete beta function by calling loggamma() and betain().

xinbta

Computes inverse of incomplete beta function ratio

Remarks:

Complete beta function: B(p,q)=gamma(p)*gamma(q)/gamma(p+q)
log(B(p,q))=ln(gamma(p))+ln(gamma(q))-ln(gamma(p+q))

Incomplete beta function ratio:
alpha = I_x(p,q) = 1/B(p,q) * int_0^x t^{p-1}*(1-t)^{q-1} dt

--> log(B(p,q)) has to be supplied to calculate I_x(p,q)
log denotes the natural logarithm
$beta = log(B(p,q))
$alpha= I_x(p,q)
$p = p
$q = q
The subroutine returns x. If an error occurs a negative value {-1,-2,-3}
is returned.

Xinbta

Computes the inverse of the incomplete beta function by calling loggamma() and xinbta().

rank

Computes the ranks of the values specified as the second argument (an array). Returns a vector of ranks corresponding to the input vector. Different types of ranking are possible (high, low, mean), and are specified as first argument. These differ in the way ties of the input vector, i.e. identical values, are treated:

high:

replace ranks of identical values with their highest rank

low:

replace ranks of identical values with their lowest rank

mean:

replace ranks of identical values with the mean of their ranks

roc

Determines the ROC curve and its nonparametric confidence bounds. The ROC curve shows the relationship of "probability of false alarm" (x-axis) to "probability of detection" (y-axis) for a certain test. Or in medical terms: the "probability of a positive test, given no disease" to the "probability of a positive test, given disease". The ROC curve may be used to determine an "optimal" cutoff point for the test.

The routine takes three arguments:

(1) type of model: decrease or increase, this states the assumption that a higher (increase) value of the data tends to be an indicator of a positive test result or for the model decrease a lower value.
(2) two-sided confidence interval (usually 0.95 is chosen).
(3) the data stored as a list-of-lists: each entry in this list consits of an "value / true group" pair, i.e. value / disease present. Group values are from {0,1}. 0 stands for disease (or signal) not present (prior knowledge) and 1 for disease (or signal) present (prior knowledge). Example: @s=([2, 0], [12.5, 1], [3, 0], [10, 1], [9.5, 0], [9, 1]); Notice the small overlap of the groups. The optimal cutoff point to separate the two groups would be between 9 and 9.5 if the criterion of optimality is to maximize the probability of detection and simultaneously minimize the probability of false alarm.

Returns a list-of-lists with the three curves: @ROC=([@lower_b], [@roc], [@upper_b]) each of the curves is again a list-of-lists with each entry consisting of one (x,y) pair.

Examples:

$,=" ";
print loggamma(10), "n";
print Xinbta(3,4,Betain(.6,3,4)),"n";

@e=(0.7, 0.7, 0.9, 0.6, 1.0, 1.1, 1,.7,.6);
print rank(low,@e),"n";
print rank(high,@e),"n";
print rank(mean,@e),"n";

@var_grp=([1.5,0],[1.4,0],[1.4,0],[1.3,0],[1.2,0],[1,0],[0.8,0],
[1.1,1],[1,1],[1,1],[0.9,1],[0.7,1],[0.7,1],[0.6,1]);
@curves=roc(decrease,0.95,@var_grp);
print "$curves[0][2][0] $curves[0][2][1] n";

Bomberman for Java is an original 2D "5 player on one computer" (2 keyboard, 1 mouse, and 2 joystick players) Bomberman game.
Features include a level editor, dynamic key configuration, bomb kicker, bomb stopper, remote bombs, bomb stripper, revenge bombs, portals, rolling floor, flame mirrors, farting items, 10 diseases, adjustable items and disease probabilities, player names, an advanced scoring scheme, adjustable lifetime durations, etc.
Main features:
- fast: your player runs incredible fast
- slow: your player walks very slow
- reverse controls: you go right when you press left, ...
- invisibility: you are invisible, though not invinsible
- auto bomb putting: you put your bombs automatically
- immediate bomb explosion: your bombs explode within a second
- fart: like the item
- autoblock putting: you leave a trail of rocks behind yourself
- invisible bombs: your bombs are invisible, can be very handy
- bomb constipation: you cant lay bombs
- level editor, random level chooser, specific level chooser
- small and medium levels
- adjustable
- screen size, sound on or off, player names
- bonus lifetime, bomb explode time, amount of bonusses, remote lifetime
- fire lifetime, nr of blocks, block reappearance speed
- adjustable bonus and disease probabilities
- full dynamic control setup
- joystick support for two players
- mouse support for one player
- two players on one keyboard: four is possible, but your keyboard will not be able to handle all the pressed buttons.
- keeping track of the wins of every player, resetable via the options menu
- when a player dies, some items are created around his position.
- different background colors
- removed background music and sound effects, added other sound effects
- bomb stop item
- portals
- bomb stripper
- mirrors: reflects fire