Gene-CluEDO 0.0.0.1 → 0.0.0.2
raw patch · 7 files changed
+167/−12 lines, 7 filesPVP ok
version bump matches the API change (PVP)
API changes (from Hackage documentation)
Files
- Gene-CluEDO.cabal +13/−2
- README.md +32/−10
- data/bla-hox-noisy.dis +16/−0
- data/hsa-adh-noisy.dis +8/−0
- data/hsa-psg.dis +11/−0
- data/mmu-rhox-noisy.dis +22/−0
- data/run-all.sh +65/−0
Gene-CluEDO.cabal view
@@ -1,5 +1,5 @@ name: Gene-CluEDO-version: 0.0.0.1+version: 0.0.0.2 author: Christian Hoener zu Siederdissen, 2017 copyright: Christian Hoener zu Siederdissen, 2017 homepage: https://github.com/choener/Gene-CluEDO@@ -11,22 +11,28 @@ build-type: Simple stability: experimental cabal-version: >= 1.10.0-tested-with: GHC == 7.10.3, GHC == 8.0.1+tested-with: GHC == 8.0.2 synopsis: Hox gene clustering description: Gene Cluster Evolution Determined Order .+ *Expansion of Gene Clusters and the Shortest Hamiltonian Path Problem*, Prohaska et al, 2017+ . Calculate the most likely order of genes in a gene cluster. . Apart from being an interesting problem in computational biology, it also serves as an example problem for dynamic programming over unordered sets with interfaces.+ .+ Binaries available from github: <https://github.com/choener/Gene-CluEDO/releases> Extra-Source-Files: README.md changelog.md+ data/*.dis+ data/run-all.sh @@ -118,4 +124,9 @@ source-repository head type: git location: git://github.com/choener/Gene-CluEDO++source-repository this+ type: git+ location: git://github.com/choener/Gene-CluEDO/tree/0.0.0.2+ tag: 0.0.0.2
README.md view
@@ -4,23 +4,26 @@ # Gene-CluEDO: Gene Cluster Evolution Determined Order -1. Hoener zu Siederdissen, Christian and Prohaska, Sonja J. and Stadler, Peter F. - *Dynamic Programming for Set Data Types* - 2014, Lecture Notes in Bioinformatics, 8826, - preprint: http://www.bioinf.uni-leipzig.de/~choener/pdfs/hoe-pro-2014.pdf --1. Hoener zu Siederdissen, Christian and Prohaska, Sonja J. and Stadler, Peter F. - *Algebraic Dynamic Programming over General Data Structures* - 2015, BMC Bioinformatics - oa: https://doi.org/10.1186/1471-2105-16-S19-S2 +The first paper describes the biological problem. The 2nd and 3rd paper provide+algorithmic background. 1. Prohaska, Sonja J. and Berkemer, Sarah and Externbrink, Fabian and Gatter, Thomas and Retzlaff, Nancy and The Students of the Graphs and Biological Networks Lab 2017 - and H\"oner zu Siederdissen, Christian and Stadler, Peter F. + and Hoener zu Siederdissen, Christian and Stadler, Peter F. *Expansion of Gene Clusters and the Shortest Hamiltonian Path Problem* 2017 preprint: http://www.bioinf.uni-leipzig.de/~choener/pdfs/pro-ber-2017.pdf +1. Hoener zu Siederdissen, Christian and Prohaska, Sonja J. and Stadler, Peter F. + *Algebraic Dynamic Programming over General Data Structures* + 2015, BMC Bioinformatics + oa: https://doi.org/10.1186/1471-2105-16-S19-S2 ++1. Hoener zu Siederdissen, Christian and Prohaska, Sonja J. and Stadler, Peter F. + *Dynamic Programming for Set Data Types* + 2014, Lecture Notes in Bioinformatics, 8826, + preprint: http://www.bioinf.uni-leipzig.de/~choener/pdfs/hoe-pro-2014.pdf + This program accepts a matrix with distances between nodes (see below for an example). It then proceeds to calculate the Hamiltonian path with the shortest distance between each pair of nodes, where the path has to travel from the@@ -35,6 +38,24 @@ Finally, we calculate the probability that a node is one of the terminal nodes in the Hamiltonian path, i.e. either the first or the last node. ++## Installation / Pre-compiled Binaries++- Binaries are available from github for Linux x86-64. They can be downloaded+ here: <https://github.com/choener/Gene-CluEDO/releases>+- Installation from sources is possible using the Haskell stack tool, as+ described at the bottom of this page:+ <http://www.bioinf.uni-leipzig.de/~choener/software/Gene-CluEDO.html>+- Another installation option is via ``cabal new-install`` (preferred for+ development, but more involved to setup)+++## Input data used for the *Expansion of Gene Clusters* paper++The data sets are available together with the sources or the binary release.+Check the ``data`` folder. The ``run-all.sh`` script runs the four examples.++ ## The Biological Problem We Solve [Wikipedia on Hox clusters.](https://en.wikipedia.org/wiki/Hox_cluster)@@ -46,6 +67,7 @@ The long time scales involved make it hard to produce a tree that can be trusted. This program therefore produces summary information in the form of edge path probabilities.+ ## Example matrix:
+ data/bla-hox-noisy.dis view
@@ -0,0 +1,16 @@+# Hox1 Hox2 Hox3 Hox4 Hox5 Hox6 Hox7 Hox8 Hox9 Hox10 Hox11 Hox12 Hox13 Hox14 Hox15+Hox1 0.0 182.24 185.02 214.64 200.33 207.22 207.22 210.86 236.23 246.45 252.01 252.01 231.5 246.45 246.45+Hox2 182.24 0.0 214.64 231.5 231.5 231.5 252.01 227.0 264.21 241.2 257.91 246.45 264.21 264.21 257.91+Hox3 185.02 214.64 0.0 146.13 182.24 185.02 176.9 203.71 241.2 270.95 270.95 294.62 264.21 252.01 252.01+Hox4 214.64 231.5 146.13 0.0 153.95 153.95 160.27 179.53 231.5 236.23 257.91 270.95 286.06 246.45 257.91+Hox5 200.33 231.5 182.24 153.95 0.0 148.02 142.44 156.01 187.89 203.71 210.86 252.01 246.45 236.23 246.45+Hox6 207.22 231.5 185.02 153.95 148.02 0.0 127.44 151.93 218.58 252.01 241.2 270.95 294.62 257.91 241.2+Hox7 207.22 252.01 176.9 160.27 142.44 127.44 0.0 137.18 203.71 236.23 222.7 264.21 278.2 246.45 246.45+Hox8 210.86 227.0 203.71 179.53 156.01 151.93 137.18 0.0 214.64 231.5 231.5 252.01 278.2 270.95 241.2+Hox9 236.23 264.21 241.2 231.5 187.89 218.58 203.71 214.64 0.0 174.34 148.02 193.91 218.58 241.2 241.2+Hox10 246.45 241.2 270.95 236.23 203.71 252.01 236.23 231.5 174.34 0.0 160.27 185.02 190.85 222.7 246.45+Hox11 252.01 257.91 270.95 257.91 210.86 241.2 222.7 231.5 148.02 160.27 0.0 164.73 227.0 257.91 264.21+Hox12 252.01 246.45 294.62 270.95 252.01 270.95 264.21 252.01 193.91 185.02 164.73 0.0 241.2 257.91 264.21+Hox13 231.5 264.21 264.21 286.06 246.45 294.62 278.2 278.2 218.58 190.85 227.0 241.2 0.0 158.12 197.06+Hox14 246.45 264.21 252.01 246.45 236.23 257.91 246.45 270.95 241.2 222.7 257.91 257.91 158.12 0.0 190.85+Hox15 246.45 257.91 252.01 257.91 246.45 241.2 246.45 241.2 241.2 246.45 264.21 264.21 197.06 190.85 0.0
+ data/hsa-adh-noisy.dis view
@@ -0,0 +1,8 @@+# ADH7 ADH1C ADH1B ADH1A ADH6 ADH4 ADH5+ADH7 0.0 19.88 20.55 21.91 24.69 24.69 20.55+ADH1C 19.88 0.0 5.02 7.34 25.39 29.01 25.39+ADH1B 20.55 5.02 0.0 4.45 23.98 26.82 23.29+ADH1A 21.91 7.34 4.45 0.0 21.23 26.11 23.98+ADH6 24.69 25.39 23.98 21.23 0.0 17.89 19.21+ADH4 24.69 29.01 26.82 26.11 17.89 0.0 13.4+ADH5 20.55 25.39 23.29 23.98 19.21 13.4 0.0
+ data/hsa-psg.dis view
@@ -0,0 +1,11 @@+# PSG3 PSG9 PSG1 PSG6 PSG4 PSG5 PSG2 PSG11 PSG7 PSG8+PSG3 0.0 17.82 14.3 15.37 15.91 38.73 43.31 44.04 15.64 14.3+PSG9 17.82 0.0 22.05 17.27 20.05 46.24 51.21 52.4 20.9 19.77+PSG1 14.3 22.05 0.0 18.09 16.45 44.77 45.13 48.13 15.1 12.71+PSG6 15.37 17.27 18.09 0.0 16.45 43.67 47.37 47.75 16.45 16.72+PSG4 15.91 20.05 16.45 16.45 0.0 43.67 46.24 48.51 14.3 16.18+PSG5 38.73 46.24 44.77 43.67 43.67 0.0 75.18 79.31 44.04 43.67+PSG2 43.31 51.21 45.13 47.37 46.24 75.18 0.0 37.36 44.4 44.77+PSG11 44.04 52.4 48.13 47.75 48.51 79.31 37.36 0.0 45.5 46.62+PSG7 15.64 20.9 15.1 16.45 14.3 44.04 44.4 45.5 0.0 15.1+PSG8 14.3 19.77 12.71 16.72 16.18 43.67 44.77 46.62 15.1 0.0
+ data/mmu-rhox-noisy.dis view
@@ -0,0 +1,22 @@+# rHOX2A rHOX3A rHOX4A rHOX2B rHOX4B rHOX2C rHOX3C rHOX4C rHOX2D rHOX4D rHOX2E rHOX3E rHOX4E rHOX2F rHOX3F rHOX4F rHOX3G rHOX2G rHOX4G rHOX2H rHOX3H+rHOX2A 0.0 160.12 103.5 29.31 106.12 29.31 160.12 106.12 35.42 104.8 26.97 160.12 106.12 31.1 157.8 103.5 162.5 34.16 103.5 37.98 160.12+rHOX3A 160.12 0.0 147.0 160.12 153.33 157.8 15.55 149.06 155.54 151.17 160.12 14.54 151.17 155.54 18.15 147.0 44.0 153.33 149.06 153.33 16.07+rHOX4A 103.5 147.0 0.0 103.5 23.01 103.5 147.0 20.82 100.95 21.91 103.5 147.0 21.36 102.22 147.0 24.12 149.06 102.22 22.46 100.95 147.0+rHOX2B 29.31 160.12 103.5 0.0 106.12 29.31 160.12 106.12 36.05 104.8 29.31 160.12 106.12 32.31 157.8 103.5 162.5 34.79 103.5 38.63 160.12+rHOX4B 106.12 153.33 23.01 106.12 0.0 106.12 153.33 22.46 103.5 20.28 106.12 153.33 21.91 104.8 153.33 22.46 155.54 104.8 20.82 103.5 153.33+rHOX2C 29.31 157.8 103.5 29.31 106.12 0.0 157.8 106.12 35.42 104.8 29.31 157.8 106.12 32.31 155.54 103.5 160.12 32.93 103.5 37.98 157.8+rHOX3C 160.12 15.55 147.0 160.12 153.33 157.8 0.0 149.06 155.54 151.17 160.12 15.55 151.17 155.54 17.1 147.0 44.0 153.33 149.06 153.33 15.55+rHOX4C 106.12 149.06 20.82 106.12 22.46 106.12 149.06 0.0 103.5 22.46 106.12 149.06 20.82 104.8 149.06 23.56 151.17 104.8 21.91 103.5 149.06+rHOX2D 35.42 155.54 100.95 36.05 103.5 35.42 155.54 103.5 0.0 102.22 35.42 155.54 103.5 37.98 155.54 100.95 160.12 32.93 100.95 36.69 155.54+rHOX4D 104.8 151.17 21.91 104.8 20.28 104.8 151.17 22.46 102.22 0.0 104.8 151.17 20.82 103.5 151.17 23.56 153.33 103.5 21.91 102.22 151.17+rHOX2E 26.97 160.12 103.5 29.31 106.12 29.31 160.12 106.12 35.42 104.8 0.0 160.12 106.12 31.1 157.8 103.5 162.5 34.16 103.5 37.98 160.12+rHOX3E 160.12 14.54 147.0 160.12 153.33 157.8 15.55 149.06 155.54 151.17 160.12 0.0 151.17 155.54 18.15 147.0 44.0 153.33 149.06 153.33 16.07+rHOX4E 106.12 151.17 21.36 106.12 21.91 106.12 151.17 20.82 103.5 20.82 106.12 151.17 0.0 104.8 151.17 25.25 153.33 104.8 22.46 103.5 151.17+rHOX2F 31.1 155.54 102.22 32.31 104.8 32.31 155.54 104.8 37.98 103.5 31.1 155.54 104.8 0.0 155.54 102.22 160.12 37.33 102.22 34.79 155.54+rHOX3F 157.8 18.15 147.0 157.8 153.33 155.54 17.1 149.06 155.54 151.17 157.8 18.15 151.17 155.54 0.0 147.0 46.1 153.33 149.06 153.33 17.1+rHOX4F 103.5 147.0 24.12 103.5 22.46 103.5 147.0 23.56 100.95 23.56 103.5 147.0 25.25 102.22 147.0 0.0 149.06 102.22 21.91 100.95 147.0+rHOX3G 162.5 44.0 149.06 162.5 155.54 160.12 44.0 151.17 160.12 153.33 162.5 44.0 153.33 160.12 46.1 149.06 0.0 157.8 151.17 157.8 44.0+rHOX2G 34.16 153.33 102.22 34.79 104.8 32.93 153.33 104.8 32.93 103.5 34.16 153.33 104.8 37.33 153.33 102.22 157.8 0.0 102.22 37.98 153.33+rHOX4G 103.5 149.06 22.46 103.5 20.82 103.5 149.06 21.91 100.95 21.91 103.5 149.06 22.46 102.22 149.06 21.91 151.17 102.22 0.0 100.95 149.06+rHOX2H 37.98 153.33 100.95 38.63 103.5 37.98 153.33 103.5 36.69 102.22 37.98 153.33 103.5 34.79 153.33 100.95 157.8 37.98 100.95 0.0 153.33+rHOX3H 160.12 16.07 147.0 160.12 153.33 157.8 15.55 149.06 155.54 151.17 160.12 16.07 151.17 155.54 17.1 147.0 44.0 153.33 149.06 153.33 0.0
+ data/run-all.sh view
@@ -0,0 +1,65 @@+#!/usr/bin/env bash++# This script runs the four data sets included with the paper "Expansion of+# Gene Clusters, Circular Orders, and the Shortest Hamiltonian Path Problem",+# Prohaska et al, 2017.++# Run this script from the main directory. It should have the binary as+# ./GeneCluEDO and the data folder under ./data.++# find GeneCluEDO binary, complain if missing.++if [ -e data ]+then+ cd data+fi++BIN=""++# local binary?+if [ -x ../GeneCluEDO ]+then+ BIN="../GeneCluEDO"+fi++# cabal new-build result+if [ -f ../Gene-CluEDO.cabal ]+then+ BIN="cabal new-run GeneCluEDO --"+fi++# binary in path?+WBIN=$(which GeneCluEDO 2>/dev/null)+if [ -x "$WBIN" ]+then+ BIN="$WBIN"+fi++if [ "$BIN" == "" ]+then+ echo "GeneCluEDO not found! Are you running from the correct directory? (The one containing the binary?)"+ echo "$BIN"+ exit 1+fi++# parameters for each file++# TODO check that these are the parameters used for the paper. (If not, they+# are somewhat sane defaults, however)++# branchiostoma lanceolatum, hox, noisy cleaned up+echo "computing: bla, hox"+$BIN --temperature 0.0025 bla-hox-noisy.dis++# homo sapiens, adh, noisy cleaned up+echo "computing: hsa, adh"+$BIN --temperature 0.0025 hsa-adh-noisy.dis++# homo sapiens, psg+echo "computing: hsa, psg"+$BIN --temperature 0.0025 hsa-psg.dis++# mus musculus, α rhox, noisy cleaned up+echo "computing: mmu rhox (takes longer)"+$BIN --temperature 0.0025 mmu-rhox-noisy.dis+