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@article{DBLP:journals/corr/FlorioP15,
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@article{DBLP:journals/corr/FlorioP15,
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@article{floridi05,
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@proceedings{DBLP:conf/agents/2000t,
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	title = "{Formal Aspects in Security and Trust, Third International Workshop, FAST 2005, Newcastle upon Tyne, UK, July 18-19, 2005, Revised Selected Papers}",
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@incollection{earl99,
	author = "Cvetkovich, George and Lofstedt, Ragnar E.",
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@incollection{earl99,
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@incollection{cvetkovich99,
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@incollection{cvetkovich99,
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@phdthesis{ClarkePhD,
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@phdthesis{ClarkePhD,
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	title = "{Trust$^{*}$: Extending the Reach of Trust in Distributed Systems}",
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	publisher = "Springer",
	series = "{Lecture Notes in Computer Science}",
	timestamp = "Wed, 06 Feb 2013 13:51:52 +0100",
	title = "{Security Protocols XVII, 17th International Workshop, Cambridge, UK, April 1-3, 2009. Revised Selected Papers}",
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	isbn = "978-3-642-36212-5, 978-3-642-36213-2",
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	publisher = "Springer",
	series = "{Lecture Notes in Computer Science}",
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	title = "{Security Protocols XVII, 17th International Workshop, Cambridge, UK, April 1-3, 2009. Revised Selected Papers}",
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	title = "{Living in an Impossible World: Real-izing the Consequences of Intransitive Trust}",
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@article{DBLP:journals/csur/ChapinSW08,
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@article{Chakraborty2012534,
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@article{Chakraborty2012534,
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@phdthesis{Can:2007:TAP:1368848,
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	author = "Can, Ahmet Burak",
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	note = "AAI3291189",
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	year = "2007"
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@phdthesis{Can:2007:TAP:1368848,
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	author = "Can, Ahmet Burak",
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	publisher = "Purdue University",
	title = "{Trust and Anonymity in Peer-to-peer Systems}",
	year = "2007"
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@techreport{secureNDC,
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@techreport{BLPM,
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@inproceedings{barnprimiero2015,
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@phdthesis{abdul05,
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@phdthesis{abdul05,
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@misc{0install,
	location = "http://0install.net/solver.html",
	title = "{Zero Install}"
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@article{DBLP:journals/jss/AbateCTZ12,
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	publisher = "ACM",
	series = "{ICSE 2014}",
	title = "{Towards Efficient Optimization in Package Management Systems}",
	url = "http://doi.acm.org/10.1145/2568225.2568306",
	year = "2014"
}

@inproceedings{Abate:2011:MMP:2000229.2000255,
	acmid = "2000255",
	address = "New York, NY, USA",
	author = "Abate, Pietro and DiCosmo, Roberto and Treinen, Ralf and Zacchiroli, Stefano",
	booktitle = "{Proceedings of the 14th International ACM Sigsoft Symposium on Component Based Software Engineering}",
	doi = "10.1145/2000229.2000255",
	isbn = "978-1-4503-0723-9",
	keywords = "package managers",
	location = "Boulder, Colorado, USA",
	numpages = "10",
	pages = "179--188",
	publisher = "ACM",
	series = "{CBSE '11}",
	title = "{MPM: A Modular Package Manager}",
	url = "http://doi.acm.org/10.1145/2000229.2000255",
	year = "2011"
}

@article{DBLP:journals/eceasst/Boender11,
	author = "Boender, Jaap",
	bibsource = "dblp computer science bibliography, http://dblp.org",
	biburl = "http://dblp.uni-trier.de/rec/bib/journals/eceasst/Boender11",
	journal = "{ECEASST}",
	timestamp = "Tue, 14 May 2013 14:22:52 +0200",
	title = "{Formal verification of a theory of packages}",
	url = "http://journal.ub.tu-berlin.de/eceasst/article/view/798",
	volume = "48",
	year = "2011"
}

@book{restall,
	author = "Restall, Greg",
	publisher = "Routledge",
	title = "{An Introduction to Substructural Logics}",
	year = "2000"
}

@article{Soleymani2015,
	abstract = "The basis of vehicular ad hoc networks (VANETs) is the exchange of data between entities, and making a decision on received data/event is usually based on information provided by other entities. Many researchers utilize the concept of trust to assess the trustworthiness of the received data. Nevertheless, the lack of a review to sum up the best available research on specific questions on trust management in vehicular ad hoc networks is sensible. This paper presents a systematic literature review to provide comprehensive and unbiased information about various current trust conceptions, proposals, problems, and solutions in VANETs to increase quality of data in transportation. For the purpose of the writing of this paper, a total of 111 articles related to the trust model in VANETs published between 2005 and 2014 were extracted from the most relevant scientific sources (IEEE Computer Society, ACM Digital Library, Springer Link, Science Direct, and Wiley Online Library). Finally, ten articles were eventually analyzed due to several reasons such as relevancy and comprehensiveness of discussion presented in the articles. Using the systematic method of review, this paper succeeds to reveal the main challenges and requirements for trust in VANETs and future research within this scope.",
	author = "Soleymani, Seyed Ahmad and Abdullah, Abdul Hanan and Hassan, Wan Haslina and Anisi, Mohammad Hossein and Goudarzi, Shidrokh and {Rezazadeh Baee}, Mir Ali and Mandala, Satria",
	doi = "10.1186/s13638-015-0353-y",
	issn = "1687-1499",
	journal = "EURASIP Journal on Wireless Communications and Networking",
	number = "1",
	pages = "146",
	title = "{Trust management in vehicular ad hoc network: a systematic review}",
	url = "http://dx.doi.org/10.1186/s13638-015-0353-y",
	volume = "2015",
	year = "2015"
}

@article{5641621,
	author = "Minhas, U. F. and Zhang, J. and Tran, T. and Cohen, R.",
	doi = "10.1109/TSMCC.2010.2084571",
	issn = "1094-6977",
	journal = "IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)",
	keywords = "multi-agent systems; telecommunication computing; vehicular ad hoc networks; VANET; Wi-Fi devices; agent trust; experience-based trust; global positioning system; intelligent agents; majority-based trust; mobile ad hoc vehicular networks; multiagent systems; multifaceted trust modeling; passenger safety; priorit-based trust; road safety; role-based trust; vehicle-to-vehicle communication; vehicular ad hoc network; Computational modeling; Context; Measurement; Roads; Security; Social network services; Vehicles; Intelligent agent, intelligent vehicles, multiagent systems",
	month = "May",
	number = "3",
	pages = "407--420",
	title = "{A Multifaceted Approach to Modeling Agent Trust for Effective Communication in the Application of Mobile Ad Hoc Vehicular Networks}",
	volume = "41",
	year = "2011"
}

@article{GomezMarmol:2012:TTR:2160992.2161100,
	acmid = "2161100",
	address = "London, UK, UK",
	author = "{G{\'o}mez M{\'a}rmol}, F{\'e}lix and {Mart{\'i}nez P{\'e}rez}, Gregorio",
	doi = "10.1016/j.jnca.2011.03.028",
	issn = "1084-8045",
	issue_date = "May, 2012",
	journal = "J. Netw. Comput. Appl.",
	keywords = "Distributed networks; Security in VANETs; Trust and reputation management; Vehicular networks",
	month = may,
	number = "3",
	numpages = "8",
	pages = "934--941",
	publisher = "Academic Press Ltd.",
	title = "{TRIP, a Trust and Reputation Infrastructure-based Proposal for Vehicular Ad Hoc Networks}",
	url = "http://dx.doi.org/10.1016/j.jnca.2011.03.028",
	volume = "35",
	year = "2012"
}

@article{Lo2009,
	abstract = "Traffic safety applications on vehicular ad hoc networks (VANETs) have drawn a lot of attention in recent years with their promising functions on car accident reduction, real-time traffic information support, and enhancement of comfortable driving experience on roadways. However, an inaccurate traffic warning message will impact drivers' decisions, waste drivers' time and fuel in their vehicles, and even invoke serious car accidents. To enable eco-friendly driving VANET environments, that is, to save fuel and time in this context, we proposed an event-based reputation system to prevent the spread of false traffic warning messages. In this system, a dynamic reputation evaluation mechanism is introduced to determine whether an incoming traffic message is significant and trustworthy to the driver. The proposed system is characterized and evaluated through experimental simulations. The simulation results show that, with a proper reputation adaptation mechanism and appropriate threshold settings, our proposed system can effectively prevent false messages spread on various VANET environments.",
	author = "Lo, Nai-Wei and Tsai, Hsiao-Chien",
	doi = "10.1155/2009/125348",
	issn = "1687-1499",
	journal = "EURASIP Journal on Wireless Communications and Networking",
	number = "1",
	pages = "125348",
	title = "{A Reputation System for Traffic Safety Event on Vehicular Ad Hoc Networks}",
	url = "http://dx.doi.org/10.1155/2009/125348",
	volume = "2009",
	year = "2009"
}

@inbook{Wei2012,
	address = "Dordrecht",
	author = "Wei, Yu-Chih and Chen, Yi-Ming",
	booktitle = "{Human Centric Technology and Service in Smart Space: HumanCom 2012}",
	doi = "10.1007/978-94-007-5086-9_14",
	FIXMEeditor = "Park, James J. (Jong Hyuk) and Jin, Qun and {Sang-soo Yeo}, Martin and Hu, Bin",
	isbn = "978-94-007-5086-9",
	pages = "105--112",
	publisher = "Springer Netherlands",
	title = "{Reliability and Efficiency Improvement for Trust Management Model in VANETs}",
	url = "http://dx.doi.org/10.1007/978-94-007-5086-9_14",
	year = "2012"
}

@inproceedings{glenford,
	author = "Vanni, R and Jaimes, L.M.S. and Mapp, G. and Moreira, E.",
	booktitle = "{AICT 2016, The Twelfth Advanced International Conference on Telecommunications }",
	pages = "14--19",
	publisher = "IARIA",
	title = "{Ontology Driven Reputation Model for VANET}",
	year = "2016"
}

@article{DBLP:journals/fac/KonurFDK14,
	author = "Konur, Savas and Fisher, Michael and Dobson, Simon and Knox, Stephen",
	bibsource = "dblp computer science bibliography, http://dblp.org",
	biburl = "http://dblp.uni-trier.de/rec/bib/journals/fac/KonurFDK14",
	doi = "10.1007/s00165-013-0277-4",
	journal = "Formal Asp. Comput.",
	number = "4",
	pages = "677--694",
	timestamp = "Tue, 01 Jul 2014 15:40:01 +0200",
	title = "{Formal verification of a pervasive messaging system}",
	url = "http://dx.doi.org/10.1007/s00165-013-0277-4",
	volume = "26",
	year = "2014"
}

@proceedings{DBLP:conf/vtc/2011s,
	bibsource = "dblp computer science bibliography, http://dblp.org",
	biburl = "http://dblp2.uni-trier.de/rec/bib/conf/vtc/2011s",
	isbn = "978-1-4244-8331-0",
	publisher = "{IEEE}",
	timestamp = "Mon, 12 Sep 2011 13:32:31 +0200",
	title = "{Proceedings of the 73rd {IEEE} Vehicular Technology Conference, {VTC} Spring 2011, 15-18 May 2011, Budapest, Hungary}",
	year = "2011"
}

@proceedings{DBLP:conf/vtc/2008s,
	bibsource = "dblp computer science bibliography, http://dblp.org",
	biburl = "http://dblp.uni-trier.de/rec/bib/conf/vtc/2008s",
	publisher = "{IEEE}",
	timestamp = "Sun, 16 Nov 2008 09:23:19 +0100",
	title = "{Proceedings of the 67th {IEEE} Vehicular Technology Conference, {VTC} Spring 2008, 11-14 May 2008, Singapore}",
	year = "2008"
}

@article{DBLP:journals/ijaisc/ChaurasiaTV15,
	author = "Chaurasia, Brijesh Kumar and Tomar, Ranjeet Singh and Verma, Shekhar",
	bibsource = "dblp computer science bibliography, http://dblp.org",
	biburl = "http://dblp.uni-trier.de/rec/bib/journals/ijaisc/ChaurasiaTV15",
	doi = "10.1504/IJAISC.2015.070633",
	journal = "{IJAISC}",
	number = "2",
	pages = "105--116",
	timestamp = "Fri, 31 Jul 2015 08:58:01 +0200",
	title = "{Using trust for lightweight communication in VANETs}",
	url = "http://dx.doi.org/10.1504/IJAISC.2015.070633",
	volume = "5",
	year = "2015"
}

@proceedings{DBLP:conf/um/2012,
	bibsource = "dblp computer science bibliography, http://dblp.org",
	biburl = "http://dblp.uni-trier.de/rec/bib/conf/um/2012",
	doi = "10.1007/978-3-642-31454-4",
	editor = "Masthoff, Judith and Mobasher, Bamshad and Desmarais, Michel C. and Nkambou, Roger",
	isbn = "978-3-642-31453-7",
	publisher = "Springer",
	series = "{Lecture Notes in Computer Science}",
	timestamp = "Tue, 19 Jun 2012 16:52:08 +0200",
	title = "{User Modeling, Adaptation, and Personalization - 20th International Conference, {UMAP} 2012, Montreal, Canada, July 16-20, 2012. Proceedings}",
	url = "http://dx.doi.org/10.1007/978-3-642-31454-4",
	volume = "7379",
	year = "2012"
}

@article{bouassida2011authentication,
  title={Authentication vs. Privacy within Vehicular Ad Hoc Networks},
  author={Bouassida, Mohamed Salah},
  journal={International Journal of Network Security},
  volume={13},
  number={3},
  pages={121--134},
  year={2011},
}

@INPROCEEDINGS{tesla-cpn,
author={M. H. Jahanian and F. Amin and A. H. Jahangir},
booktitle={2015 6th International Conference on Information and Communication Systems (ICICS)},
title={Analysis of TESLA protocol in vehicular ad hoc networks using timed colored Petri nets},
year={2015},
pages={222-227},
keywords={Petri nets;cryptographic protocols;synchronisation;vehicular ad hoc networks;TESLA protocol;VANET;broadcast source authentication protocols;timed colored Petri nets;timed model checking approach;vehicle-to-vehicle applications;vehicular ad hoc networks;Authentication;Clocks;Petri nets;Protocols;Receivers;Synchronization;Model checking;Synchronization;TESLA;Timed colored Petri nets;Vehicular ad hoc networks},
doi={10.1109/IACS.2015.7103231},
month={April},}

license_type: permissive

branch_name: refs/heads/master

extension: bib


text:
@article{anhedonia-transdiagnostic,
  title = {Anhedonia in Major Depression and Schizophrenia: A Transdiagnostic Challenge},
  author={Lambert C, Da Silva S, Ceniti AK, Rizvi SJ, Foussias G, Kennedy SH},
  journal = {CNS Neuroscience & Therapeutics},
  year    = 2018,
  volume  = 24,
  number  = 7
}

license: MIT

repository: itineca/itineca

repo_name: itineca/itineca

gha_license_id: MIT

gha_language: Shell


text:
@inproceedings{merkx-frank-2021-human,
    title = "Human Sentence Processing: Recurrence or Attention?",
    author = "Merkx, Danny  and
      Frank, Stefan L.",
    booktitle = "Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.cmcl-1.2",
    doi = "10.18653/v1/2021.cmcl-1.2",
    pages = "12--22",
    abstract = "Recurrent neural networks (RNNs) have long been an architecture of interest for computational models of human sentence processing. The recently introduced Transformer architecture outperforms RNNs on many natural language processing tasks but little is known about its ability to model human language processing. We compare Transformer- and RNN-based language models{'} ability to account for measures of human reading effort. Our analysis shows Transformers to outperform RNNs in explaining self-paced reading times and neural activity during reading English sentences, challenging the widely held idea that human sentence processing involves recurrent and immediate processing and provides evidence for cue-based retrieval.",
}

repository: rycolab/website

repo_name: rycolab/website


text:
cmake_minimum_required(VERSION 3.6)

function(add_source_groups files)
	if(files)
		foreach(file ${files})
			add_file_to_source_group(${file})
		endforeach()
	endif()
endfunction(add_source_groups)

function(add_file_to_source_group file)
    get_filename_component (file_path ${file} PATH)
    file (RELATIVE_PATH rel_file_path ${CMAKE_CURRENT_LIST_DIR} ${file_path})
	if(NOT "${rel_file_path}" STREQUAL "")
		string (REPLACE "/" "\\" rel_file_path ${rel_file_path})
	endif()
	source_group ("${rel_file_path}" FILES ${file})
endfunction(add_file_to_source_group)

function(set_compile_flags TARGET)
    get_target_property(CURRENT_COMPILE_FLAGS ${TARGET} COMPILE_FLAGS)
    if("${CURRENT_COMPILE_FLAGS}" STREQUAL "CURRENT_COMPILE_FLAGS-NOTFOUND")
        set (CURRENT_COMPILE_FLAGS "")
    endif()
	get_target_property(CURRENT_COMPILE_FLAGS_DEBUG ${TARGET} COMPILE_FLAGS_DEBUG)
    if("${CURRENT_COMPILE_FLAGS_DEBUG}" STREQUAL "CURRENT_COMPILE_FLAGS-NOTFOUND")
        set (CURRENT_COMPILE_FLAGS_DEBUG "")
    endif()
	get_target_property(CURRENT_COMPILE_FLAGS_RELEASE ${TARGET} COMPILE_FLAGS_RELEASE)
    if("${CURRENT_COMPILE_FLAGS_RELEASE}" STREQUAL "CURRENT_COMPILE_FLAGS-NOTFOUND")
        set (CURRENT_COMPILE_FLAGS_RELEASE "")
    endif()

	if (CMAKE_CXX_COMPILER_ID MATCHES "(GNU|.*Clang)")
		set(CURRENT_COMPILE_FLAGS "${CURRENT_COMPILE_FLAGS} -pedantic -Werror -Wall -Wextra -Wno-unused-parameter -Wno-error=unused-variable -Wno-error=sign-compare")
		set(CURRENT_COMPILE_FLAGS_DEBUG "${CURRENT_COMPILE_FLAGS_DEBUG} -g")
		if(NOT COVERAGE)
			set(CURRENT_COMPILE_FLAGS_DEBUG "${CURRENT_COMPILE_FLAGS_DEBUG} -O0")
		endif()
		set(CURRENT_COMPILE_FLAGS_RELEASE "${CURRENT_COMPILE_FLAGS_RELEASE} -g -O2 -DNDEBUG")

	elseif(MSVC)
		# /Zi - Produces a program database (PDB) that contains type information and symbolic debugging information for use with the debugger.
		# /FS - Allows multiple cl.exe processes to write to the same .pdb file
		# /DEBUG - Enable debug during linking
		# /Od - Disables optimization
		# /WX - Warnings as errors
		set(CURRENT_COMPILE_FLAGS "${CURRENT_COMPILE_FLAGS} /WX")
		set(CURRENT_COMPILE_FLAGS_DEBUG "${CURRENT_COMPILE_FLAGS_DEBUG} /Zi /FS /DEBUG /Od /MDd")
		# /Ox - Full optimization
		set(CURRENT_COMPILE_FLAGS_RELEASE "${CURRENT_COMPILE_FLAGS_RELEASE} /Ox -DNDEBUG")
	endif()

	set_target_properties (${TARGET} PROPERTIES COMPILE_FLAGS "${CURRENT_COMPILE_FLAGS}")
	set_target_properties (${TARGET} PROPERTIES COMPILE_FLAGS_DEBUG "${CURRENT_COMPILE_FLAGS_DEBUG}")
	set_target_properties (${TARGET} PROPERTIES COMPILE_FLAGS_RELEASE "${CURRENT_COMPILE_FLAGS_RELEASE}")
endfunction(set_compile_flags)

extension: cmake


text:
DESCRIPTION = "Metapackage for Matchbox suite"
LICENSE = "GPL"
DEPENDS = "matchbox-common matchbox-wm matchbox-panel matchbox-desktop"
RDEPENDS_${PN} = "matchbox-common matchbox-wm matchbox-panel matchbox-desktop"
SECTION = "x11/wm"
PACKAGES= "${PN}"
ALLOW_EMPTY = "1"
PR = "r1"

repository: overo/overo-oe-natty

repo_name: overo/overo-oe-natty

branch_name: HEAD

extension: bb


text:
package main

import (
	"log"
	"fmt"
	"strings"
	"github.com/biogo/store/interval"
	utils "github.com/opoirion/snATACUtils/ATACdemultiplexUtils"
	"strconv"
	"path"
	"bytes"
	stats "github.com/glycerine/golang-fisher-exact"
	"sort"
)

/*CLUSTERGENEFILE file name */
var CLUSTERGENEFILE utils.Filename

/*CLUSTERRNASPECIFICEQTL <cluster> count*/
var CLUSTERRNASPECIFICEQTL map[string]int

/*EQTLRESTCOUNT <cluster> count*/
var EQTLRESTCOUNT map[string]int

/*PEAKRESTOUTSIDECOUNT <cluster> count*/
var PEAKRESTOUTSIDECOUNT map[string]int

/*PEAKRESTCOUNT <cluster> count*/
var PEAKRESTCOUNT map[string]int

/*CLUSTERSPECIFICCOUNT <cluster> count*/
var CLUSTERSPECIFICCOUNT map[string]int

/*TOTALRNAEQTLCOUNT <cluster> count*/
var TOTALRNAEQTLCOUNT map[string]int

/*CLUSTERGENEDICT map[clusterID]map[gene]bool*/
var CLUSTERGENEDICT map[string]map[string]bool

/*TOTALNUMBEREQTL ...*/
var TOTALNUMBEREQTL int

/*EQTLPEAKRNASPECIFIC <cluster> count*/
var EQTLPEAKRNASPECIFIC  map[string]int

/*EQTLPEAKSPECIFIC <cluster> count*/
var EQTLPEAKSPECIFIC  map[string]int

/*EQTLRNASPECIFIC <cluster> count*/
var EQTLRNASPECIFIC  map[string]int

/*EQTLREST <cluster> count*/
var EQTLREST  map[string]int

func performGlobalEQTLAnalsysis() {

	switch {
	case CLUSTERGENEFILE == "":
		log.Fatal(fmt.Printf("!!!! Error -cluster_gene option must be provided\n"))

	case GENEIDTONAMEFILE == "":
		log.Fatal(fmt.Printf("!!!! Error -gene_ID_to_name option must be provided\n"))

	case FEATUREPVALUEFILE == "":
		log.Fatal(fmt.Printf("!!!! Error -ptable option must be provided\n"))

	case len(SNPFILES) == 0:
		log.Fatal(fmt.Printf("!!!! Error -eQTL option must be provided\n"))

	case PEAKFILE == "":
		log.Fatal(fmt.Printf("!!!! Error -peak option must be provided\n"))

	case OUTFILE == "":
		ext := path.Ext(FEATUREPVALUEFILE.String())
		OUTFILE = fmt.Sprintf("%s.globaleQTL.tsv",
			FEATUREPVALUEFILE[:len(FEATUREPVALUEFILE) - len(ext)])
	}

	PEAKRESTOUTSIDECOUNT = make(map[string]int)
	PEAKRESTCOUNT = make(map[string]int)
	EQTLRESTCOUNT = make(map[string]int)
	CLUSTERRNASPECIFICEQTL = make(map[string]int)
	CLUSTERSPECIFICCOUNT = make(map[string]int)
	TOTALRNAEQTLCOUNT = make(map[string]int)

	if LDFILE != "" {
		//Load LD group
		loadRefLDFile()
	}

	createRefGeneDict()
	loadClusterGeneDict()
	createPeakIntervalTree()
	createSNPIntervalTree()
	createRefGeneDict()
	scanPtable()
	scanPeaks()
	countForNonRNAeQTLCount()
	scanSNPList()
	writeGlobaleQTLOutput()
	writeGlobaleQTLOutputTable2()
}

func countForNonRNAeQTLCount() {
	var gene, cluster string

	for gene = range GENETOEQTLCOUNT {
		TOTALNUMBEREQTL += GENETOEQTLCOUNT[gene]
	}

	for cluster = range CLUSTERGENEDICT {
		for gene = range CLUSTERGENEDICT[cluster] {
			TOTALRNAEQTLCOUNT[cluster] += GENETOEQTLCOUNT[gene]
		}
	}
}

func writeGlobaleQTLOutput() {
	writer := utils.ReturnWriter(OUTFILE)
	defer utils.CloseFile(writer)
	var buffer bytes.Buffer
	var n11, n12, n21, n22 int

	buffer.WriteString(
		"ClusterID\tCluster-RNA-eQTL\tCluster-eQTL\tpeak-EQTL\tnon-cluster-eQTL\tchi2 p-value\n")

	clusterList := []string{}

	for cluster := range CLUSTERGENEDICT {
		clusterList = append(clusterList, strings.Trim(cluster, " "))
	}

	sort.Strings(clusterList)

	for _, cluster := range clusterList {
		n11 = CLUSTERRNASPECIFICEQTL[cluster]
		n12 = TOTALRNAEQTLCOUNT[cluster]
		n21 = CLUSTERSPECIFICCOUNT[cluster] - n11
		n22 = TOTALNUMBEREQTL - n12

		_, pvalue :=  stats.ChiSquareTest(n11, n12,
			n21, n22, true)

		buffer.WriteString(fmt.Sprintf("%s\t%d\t%d\t%d\t%d\t%f\n",
			cluster, n11, n12, n21, n22, pvalue))

	}

	_, err := writer.Write(buffer.Bytes())
	utils.Check(err)

	fmt.Printf("results:\n%s\n", buffer.String())
}

func writeGlobaleQTLOutputTable2() {
	ext := path.Ext(FEATUREPVALUEFILE.String())
	outfile := fmt.Sprintf("%s.globaleQTL.Table2.tsv",
		FEATUREPVALUEFILE[:len(FEATUREPVALUEFILE) - len(ext)])

	writer := utils.ReturnWriter(outfile)
	defer utils.CloseFile(writer)
	var buffer bytes.Buffer
	var n11, n12, n21, n22 int

	fmt.Printf("\n\n####Analysis 2 ####\n")

	buffer.WriteString(
		"ClusterID\tC-specific scRNA + chromatin\tC-specific chromatin\tC-specific scRNA\tOther eQTL\tP-value\n")

	clusterList := []string{}

	for cluster := range CLUSTERGENEDICT {
		clusterList = append(clusterList, strings.Trim(cluster, " "))
	}

	sort.Strings(clusterList)

	for _, cluster := range clusterList {
		n11 = EQTLPEAKRNASPECIFIC[cluster]
		n12 = EQTLPEAKSPECIFIC[cluster]
		n21 = EQTLRNASPECIFIC[cluster]
		n22 = EQTLREST[cluster]

		_, pvalue :=  stats.ChiSquareTest(n11, n12,
			n21, n22, true)

		buffer.WriteString(fmt.Sprintf("%s\t%d\t%d\t%d\t%d\t%f\n",
			cluster, n11, n12, n21, n22, pvalue))

	}

	_, err := writer.Write(buffer.Bytes())
	utils.Check(err)

	fmt.Printf("results:\n%s\n", buffer.String())

	fmt.Printf("\nFile: %s written\n", outfile)
}

func scanPtable() {
	var split []string
	var chro, cluster, gene string
	var start, end int
	var err error
	var intervals []interval.IntInterface
	var inter interval.IntInterface
	var isInside bool
	var snp Snp
	var interRange interval.IntRange

	scanner, file := FEATUREPVALUEFILE.ReturnReader(0)
	defer utils.CloseFile(file)

	//Skip first line
	scanner.Scan()

	SNPCLUSTERLIST = make(map[string]map[Snp]bool)

	for scanner.Scan() {
		split = strings.Split(scanner.Text(), "\t")
		chro = split[0][3:]

		start, err = strconv.Atoi(split[1])
		utils.Check(err)

		end, err = strconv.Atoi(split[2])
		utils.Check(err)

		cluster = split[3]

		if _, isInside = SNPINTERVALDICT[chro];!isInside {
			continue
		}

		if _, isInside = SNPCLUSTERLIST[cluster];!isInside {
			SNPCLUSTERLIST[cluster] = make(map[Snp]bool)
		}

		intervals = SNPINTERVALDICT[chro].Get(IntInterval{
			Start:start, End:end})

		PEAKRESTCOUNT[cluster]++
		CLUSTERSPECIFICCOUNT[cluster] += len(intervals)

		for _, inter = range intervals {
			gene = GENEUINTDICT[inter.ID()]

			interRange = inter.Range()

			snp.chrID = chro
			snp.Start = interRange.Start
			snp.End = interRange.End
			snp.gene = gene

			SNPCLUSTERLIST[cluster][snp] = true

			if CLUSTERGENEDICT[cluster][gene] {
				CLUSTERRNASPECIFICEQTL[cluster]++
			}
		}
	}
}

func scanPeaks() {
	var split []string
	var start, end int
	var chro, cluster, gene string

	var intervals []interval.IntInterface
	var interval interval.IntInterface
	var isInside bool
	var err error

	scanner, file := PEAKFILE.ReturnReader(0)
	defer utils.CloseFile(file)

	for scanner.Scan() {

		split = strings.Split(scanner.Text(), "\t")
		chro = split[0][3:]

		start, err = strconv.Atoi(split[1])
		utils.Check(err)

		end, err = strconv.Atoi(split[2])
		utils.Check(err)

		if _, isInside = SNPINTERVALDICT[chro];!isInside {
			continue
		}

		intervals = SNPINTERVALDICT[chro].Get(IntInterval{
			Start:start, End:end})

		for cluster = range CLUSTERGENEDICT {
			cluster = strings.Trim(cluster, " ")
			PEAKRESTOUTSIDECOUNT[cluster]++

			for _, interval = range intervals {
				gene = GENEUINTDICT[interval.ID()]

				switch cluster {
				case cluster:
					if CLUSTERGENEDICT[cluster][gene] {
						EQTLRESTCOUNT[cluster]++
					}

				}

			}

		}

	}

}

func scanSNPList() {

	EQTLPEAKRNASPECIFIC = make(map[string]int)
	EQTLPEAKSPECIFIC = make(map[string]int)
	EQTLRNASPECIFIC = make(map[string]int)
	EQTLREST = make(map[string]int)

	var snp Snp
	var cluster string

	for snp = range SNPLIST {

		for cluster = range CLUSTERGENEDICT {
			if SNPCLUSTERLIST[cluster][snp] {
				if CLUSTERGENEDICT[cluster][snp.gene] {
					EQTLPEAKRNASPECIFIC[cluster]++
				} else {
					EQTLPEAKSPECIFIC[cluster]++

				}
			} else {
				if CLUSTERGENEDICT[cluster][snp.gene] {
					EQTLRNASPECIFIC[cluster]++
				} else {
					EQTLREST[cluster]++
				}
			}
		}
	}
}

func loadClusterGeneDict() {
	var line, cluster string
	var fname utils.Filename
	var split []string

	CLUSTERGENEDICT = make(map[string]map[string]bool)

	scanner, file := CLUSTERGENEFILE.ReturnReader(0)
	defer utils.CloseFile(file)

	for scanner.Scan() {
		line = scanner.Text()
		split = strings.Split(line, "\t")

		if len(split) < 2 {
			log.Fatal(fmt.Sprintf("error with line %s from file %s. Cannot split with <tab>!\n",
				line, CLUSTERGENEFILE))
		}

		cluster, fname = split[0], utils.Filename(split[1])
		cluster = strings.Trim(cluster, " ")

		loadOneGeneFile(fname, cluster)
	}
}

func loadOneGeneFile(fname utils.Filename, cluster string) {
	var gene string
	CLUSTERGENEDICT[cluster] = make(map[string]bool)

	scanner, file := fname.ReturnReader(0)
	defer utils.CloseFile(file)

	for scanner.Scan() {
		gene = strings.Split(scanner.Text(), "\t")[0]

		CLUSTERGENEDICT[cluster][gene] = true
	}
}

repository: opoirion/snATACUtils

repo_name: opoirion/snATACUtils

extension: go


text:
@Article{devailly_dynamics_2015,
  title = {Dynamics of {MBD2} deposition across methylated {DNA} regions during malignant transformation of human mammary epithelial cells},
  volume = {43},
  copyright = {All rights reserved},
  author = {Guillaume Devailly and M{\a'e}lodie Grandin and Laury Perriaud and Pauline Mathot and Jean-Guy Delcros and Yannick Bidet and Anne-Pierre Morel and Jean-Yves Bignon and Alain Puisieux and Patrick Mehlen and Robert Dante},
  year = {2015},
  doi = {10.1093/nar/gkv508},
  pages = {5838--5854},
  issn = {1362-4962},
  abstract = {DNA methylation is thought to induce transcriptional silencing through the combination of two mechanisms: the repulsion of transcriptional activators unable to bind their target sites when methylated, and the recruitment of transcriptional repressors with specific affinity for methylated DNA. The Methyl CpG Binding Domain proteins MeCP2, MBD1 and MBD2 belong to the latter category. Here, we present MBD2 ChIPseq data obtained from the endogenous MBD2 in an isogenic cellular model of oncogenic transformation of human mammary cells. In immortalized (HMEC-hTERT) or transformed (HMLER) cells, MBD2 was found in a large proportion of methylated regions and associated with transcriptional silencing. A redistribution of MBD2 on methylated DNA occurred during oncogenic transformation, frequently independently of local DNA methylation changes. Genes downregulated during HMEC-hTERT transformation preferentially gained MBD2 on their promoter. Furthermore, depletion of MBD2 induced an upregulation of MBD2-bound genes methylated at their promoter regions, in HMLER cells. Among the 3,160 genes downregulated in transformed cells, 380 genes were methylated at their promoter regions in both cell lines, specifically associated by MBD2 in HMLER cells, and upregulated upon MBD2 depletion in HMLER. The transcriptional MBD2-dependent downregulation occurring during oncogenic transformation was also observed in two additional models of mammary cell transformation. Thus, the dynamics of MBD2 deposition across methylated DNA regions was associated with the oncogenic transformation of human mammary cells.},
  language = {eng},
  journal = {Nucleic Acids Research},
  pmid = {26007656},
  pmcid = {PMC4499136},
  keywords = {DNA Methylation, Humans, Repressor Proteins, Female, Cell Line, DNA-Binding Proteins, Transcription Factors, Binding Sites, Down-Regulation, Breast, Phenotype, Tumor Suppressor Protein p53, Cell Transformation, Neoplastic, Cell Line, Transformed, Epithelial Cells, Homeodomain Proteins, Telomerase, Zinc Finger E-box-Binding Homeobox 1},
  number = {12},
  month = {jul},
  date = {2015-01-01},
}

repository: gdevailly/siteperso

repo_name: gdevailly/siteperso


text:
@inproceedings{courty:hal-00710683,
 address = {United Kingdom},
 author = {Courty, Nicolas and Burger, Thomas and Marteau, Pierre-François},
 booktitle = {ECML-PKDD 2012},
 hal_id = {hal-00710683},
 hal_version = {v1},
 pages = {--},
 title = {Geodesic Analysis on the Gaussian RKHS hypersphere},
 url = {https://hal.archives-ouvertes.fr/hal-00710683},
 year = {2012}
}

repository: ncourty/academic-kickstart

repo_name: ncourty/academic-kickstart


text:
SUMMARY = "A very basic image with VDR features"
LICENSE = "MIT"

require base-image.bb

IMAGE_INSTALL += " \
    tvheadend \
    fw-technisat \
    fw-tevii \
"

repository: shagu/meta-teapot

repo_name: shagu/meta-teapot

gha_language: BitBake


text:
require autofs.inc

SRC_URI = "${KERNELORG_MIRROR}/pub/linux/daemons/autofs/v4/autofs-${PV}.tar.bz2 \
           ${KERNELORG_MIRROR}/pub/linux/daemons/autofs/v4/autofs-4.1.4-misc-fixes.patch;patch=1 \
           ${KERNELORG_MIRROR}/pub/linux/daemons/autofs/v4/autofs-4.1.4-multi-parse-fix.patch;patch=1 \
           ${KERNELORG_MIRROR}/pub/linux/daemons/autofs/v4/autofs-4.1.4-non-replicated-ping.patch;patch=1 \
           ${KERNELORG_MIRROR}/pub/linux/daemons/autofs/v4/autofs-4.1.4-locking-fix-1.patch;patch=1 \
           file://cross.patch;patch=1 \
           file://Makefile.rules-cross.patch;patch=1 \
	   file://install.patch;patch=1 \
	   file://auto.net-sort-option-fix.patch;patch=1 \
	   file://autofs-additional-distros.patch;patch=1 \
	   file://no-bash.patch;patch=1 \
	   file://autofs-add-hotplug.patch;patch=1"

SRC_URI_append_opendreambox = " \
           file://auto.master \
           file://auto.network \
           file://autofs"

PR = "${INC_PR}.1"

inherit update-rc.d

INITSCRIPT_NAME = "autofs"
INITSCRIPT_PARAMS = "defaults 21 19"

# FIXME: modules/Makefile has crappy rules that don't obey LDFLAGS
CFLAGS += "${LDFLAGS}"
EXTRA_OEMAKE = "STRIP=/bin/true"
PARALLEL_MAKE = ""

do_install_append_opendreambox () {
	install -d ${D}${sysconfdir}/init.d
	install ${WORKDIR}/autofs ${D}${sysconfdir}/init.d
	install ${WORKDIR}/auto.master ${D}${sysconfdir}/auto.master
	install ${WORKDIR}/auto.network ${D}${sysconfdir}/auto.network
}

repository: demsey/openembedded

repo_name: demsey/openembedded


text:
var breakpoints = require('../breakpoint');
var view = require('../view');
var ui = require('../ui');
var event = require('../event');
var preferences = require('../preferences');
var utils = require('../utils');
var syncScroll = require('../sync-scroll');
var overrideScroll = require('../override-scroll');
var eventRouter = require('../event-router');
var serializer = require('../serializer');
var chromeUtils = require('./utils');

// the domain key used to store user preferences
var DOMAIN = location.href;
var allBreakpoints = null;
var allViews = null;
var uiContainer = null;
var defaultPreferences = {
	maxWidthEnabled: true,
	maxWidth: 700,
	syncScroll: true
};

function initMainView(bp) {
	if (!bp || !bp.length) {
		return uiContainer.classList.add('emmet-re-view_error');
	}

	var skipped = preferences.get('skipBreakpoints', []);
	bp = bp.filter(function(b) {
		return !~skipped.indexOf(b.id);
	});

	var url = location.href;
	var fragment = document.createDocumentFragment();
	allViews = bp.map(function(b) {
		var v = view.create(url, b, viewOptions(b));
		fragment.appendChild(v);
		return v;
	})
	ui.scroller(uiContainer).appendChild(fragment);

	// update views sizes, if required
	setTimeout(function() {
		// updateAllViews();
		allViews.forEach(function(v) {
			syncScroll.init(v);
		});

		if (preferences.get('overrideScroll')) {
			overrideScroll.enable(ui.scroller(uiContainer));
		}
	}, 100);
}

function reset() {
	while (allViews.length) {
		view.remove(allViews.pop());
	}
	overrideScroll.disable();
	preferences.load(defaultPreferences, {overrideScroll: overrideScroll.guessState()});
	savePreferences();
	initMainView(allBreakpoints);
}

function viewOptions(bp) {
	var options = {};
	if (preferences.get('maxWidthEnabled')) {
		options.maxWidth = preferences.get('maxWidth');
	}

	// it’s a view
	if (bp && 'nodeType' in bp) {
		bp = view.breakpointForView(bp);
	}

	if (bp) {
		var widths = preferences.get('breakpointWidths', {});
		if (bp.id in widths) {
			options.width = widths[bp.id];
		}
	}

	return options;
}

function updateAllViews() {
	allViews.forEach(function(v) {
		view.update(v, viewOptions(v));
	});
}

function loadCSS(url, callback) {
	chromeUtils.sendMessage('loadCSS', {url: url}, function(response) {
		if (response.err) {
			console.log(response.err);
			return callback(null);
		}

		var ast = response.ast;
		if (typeof ast === 'string') {
			ast = JSON.parse(ast);
		}
		callback(ast);
	});
}

function hideUI(evt) {
	if (evt && evt.keyCode !== 27) {
		return;
	}

	ui.remove();
	document.removeEventListener('keyup', hideUI);
	overrideScroll.disable();
}

function injectFont() {
	var fontCSS = document.createElement('link');
	fontCSS.setAttribute('rel', 'stylesheet');
	fontCSS.setAttribute('href', 'http://fonts.googleapis.com/css?family=Lato');
	document.head.appendChild(fontCSS);
}

function savePreferences() {
	var localData = preferences.dump();
	var globalData = {};

	if ('overrideScroll' in localData) {
		globalData.overrideScroll = localData.overrideScroll;
		delete localData.overrideScroll;
	}

	var data = {};
	data[DOMAIN] = localData;
	data['global'] = globalData;
	chrome.storage.local.set(data);
}

// route events
eventRouter.setup({
	updateViews: utils.throttle(updateAllViews, 100),
	savePreferences: utils.throttle(savePreferences, 100),
	reset: reset
});

event
	.on('view:remove', function(v) {
		if (~allViews.indexOf(v)) {
			allViews.splice(allViews.indexOf(v), 1);
		}
	})
	.on('option:copyURL', function() {
		var hash = serializer.serialize({
			url: location.href,
			breakpoints: allBreakpoints
		});
		var url = 'http://re-view.emmet.io/#' + hash;
		console.log('Copied Re:View URL:', url);
		chromeUtils.sendMessage('clipboardCopy', url);
	});

// start the app
chrome.storage.local.get(['global', DOMAIN], function(data) {
	preferences.load(data[DOMAIN] || defaultPreferences, data.global);
	uiContainer = ui.currentUI();
	if (uiContainer) {
		// UI view already created, remove it
		return hideUI();
	}

	document.addEventListener('keyup', hideUI, false);

	var overrideScrollEnabled = preferences.get('overrideScroll');
	if (typeof preferences.get('overrideScroll') === 'undefined') {
		preferences.set('overrideScroll', overrideScroll.guessState());
	}

	uiContainer = ui.create({
		panel: true,
		maxWidth: {
			enabled: preferences.get('maxWidthEnabled'),
			value: preferences.get('maxWidth')
		},
		syncScroll: preferences.get('syncScroll'),
		overrideScroll: preferences.get('overrideScroll'),
		reset: true,
		copyURL: true
	});
	document.body.appendChild(uiContainer);
	breakpoints.get({loadCSS: loadCSS}, function(bp) {
		injectFont();
		console.log('Re:View received breakpoints', bp);
		allBreakpoints = bp;
		initMainView(bp);
	});
});

repository: justsml/re-view

repo_name: justsml/re-view

extension: js


text:
DESCRIPTION = "Python Bindings for libphone-utils"
SECTION = "devel/python"
DEPENDS = "libphone-utils python-cython-native python-pyrex-native"
RDEPENDS_${PN} = "libphone-utils"

SRCREV = "8a7c719e0c3f1f8c10f77f17422da02d7177f0dd"
PV = "0.0.2+gitr${SRCPV}"
PR = "r3"

SRC_URI = "git://git.shr-project.org/repo/libphone-utils.git;protocol=http;branch=master"
S = "${WORKDIR}/git/src/python"

inherit setuptools


text:
@article{Apru19,
 title = {Robust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networks},
 author = {Aprupe, Lilija and Litjens, Geert and Brinker, Titus J. and van der Laak, Jeroen and Grabe, Niels},
 year = 2019,
 month = apr,
 keywords = {Lung cancer, Immune cells, Deep learning, Cancer micro-environment, Biomarker quantification},
 abstract = {
            Recent years have seen a growing awareness of the role the immune system plays in successful cancer treatment, especially in novel therapies like immunotherapy. The characterization of the immunological composition of tumors and their micro-environment is thus becoming a necessity. In this paper we introduce a deep learning-based immune cell detection and quantification method, which is based on supervised learning, i.e., the input data for training comprises labeled images. Our approach objectively deals with staining variation and staining artifacts in immunohistochemically stained lung cancer tissue and is as precise as humans. This is evidenced by the low cell count difference to humans of 0.033 cells on average. This method, which is based on convolutional neural networks, has the potential to provide a new quantitative basis for research on immunotherapy.
         },
 volume = 7,
 pages = {e6335},
 journal = {PeerJ},
 issn = {2167-8359},
 url = {https://doi.org/10.7717/peerj.6335},
 doi = {10.7717/peerj.6335}
}

branch_name: refs/heads/main