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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/29683?offset=1350</link>
	<atom:link href="https://bioinformaticsonline.com/related/29683?offset=1350" rel="self" type="application/rss+xml" />
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<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10459/associate-professor-bio-informatics-at-university-of-allahabad-in-allahabad</guid>
  <pubDate>Wed, 07 May 2014 00:26:53 -0500</pubDate>
  <link></link>
  <title><![CDATA[Associate Professor - Bio-Informatics at University of Allahabad in Allahabad]]></title>
  <description><![CDATA[
<p>No of vacancies: 01</p>

<p>Pay scale: Pay Band of Rs. 37400-67000 with AGP of Rs. 9000.</p>

<p>i. Educational Qualification: Good academic record with a Ph.D. Degree in the concerned/allied/relevant disciplines.</p>

<p>ii. A Master's Degree with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed).</p>

<p>iii. A minimum of eight years of experience of teaching and/or research in an academic/research position equivalent to that of Assistant Professor in a University, College or Accredited Research Institution/industry excluding the period of Ph.D. research with evidence of published work and a minimum of 5 publications as books and/or research/policy papers.</p>

<p>iv. Contribution to educational innovation, design of new curricula and courses, and technology - mediated teaching learning process with evidence of having guided doctoral candidates and research students.</p>

<p>v. A minimum score as stipulated in the Academic Performance Indicator (API) based Performance Based Appraisal System (PBAS), set out in UGC Regulation.</p>

<p>Download application form from website: http://www.allduniv.ac.in/</p>

<p>Send your application to the Registrar, University of Allahabad, Allahabad-211002 (U.P.) on or before 30th April 2014</p>

<p>For more details: http://www.allduniv.ac.in/images/adv/backlog/advt-details.pdf OR http://www.allduniv.ac.in/images/news/extension-notice.pdf</p>

<p>Last Apply Date: 30 May 2014</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/blog/view/45177/installing-crossroad-on-ubuntu</guid>
	<pubDate>Fri, 29 May 2026 05:19:45 -0500</pubDate>
	<link>https://bioinformaticsonline.com/blog/view/45177/installing-crossroad-on-ubuntu</link>
	<title><![CDATA[Installing croSSRoad on Ubuntu !]]></title>
	<description><![CDATA[<p><strong>(base) hp@hp-HP-Z2-Tower-G9-Workstation-Desktop-PC:~/jitendraTEST$ conda</strong><br />usage: conda [-h] [-v] [--no-plugins] [-V] COMMAND ...</p><p>conda is a tool for managing and deploying applications, environments and packages.</p><p>options:<br /> -h, --help Show this help message and exit.<br /> -v, --verbose Can be used multiple times. Once for detailed output, twice for INFO logging, thrice for DEBUG logging, four times for TRACE logging.<br /> --no-plugins Disable all plugins that are not built into conda.<br /> -V, --version Show the conda version number and exit.</p><p>commands:<br /> The following built-in and plugins subcommands are available.</p><p>COMMAND<br /> activate Activate a conda environment.<br /> clean Remove unused packages and caches.<br /> commands List all available conda subcommands (including those from plugins). Generally only used by tab-completion.<br /> compare Compare packages between conda environments.<br /> config Modify configuration values in .condarc.<br /> create Create a new conda environment from a list of specified packages.<br /> deactivate Deactivate the current active conda environment.<br /> doctor Display a health report for your environment.<br /> env Create and manage conda environments.<br /> export Export a given environment<br /> info Display information about current conda install.<br /> init Initialize conda for shell interaction.<br /> install Install a list of packages into a specified conda environment.<br /> list List installed packages in a conda environment.<br /> notices Retrieve latest channel notifications.<br /> package Create low-level conda packages. (EXPERIMENTAL)<br /> remove (uninstall) Remove a list of packages from a specified conda environment.<br /> rename Rename an existing environment.<br /> repoquery Advanced search for repodata.<br /> run Run an executable in a conda environment.<br /> search Search for packages and display associated information using the MatchSpec format.<br /> update (upgrade) Update conda packages to the latest compatible version.<br />(base) hp@hp-HP-Z2-Tower-G9-Workstation-Desktop-PC:~/jitendraTEST$ conda create -n jitENV<br />Retrieving notices: done<br />Channels:<br /> - ursky<br /> - bioconda<br /> - conda-forge<br />Platform: linux-64<br />Collecting package metadata (repodata.json): done<br />Solving environment: done</p><p><br />==&gt; WARNING: A newer version of conda exists. &lt;==<br /> current version: 25.7.0<br /> latest version: 26.5.0</p><p>Please update conda by running</p><p>$ conda update -n base -c conda-forge conda</p><p>&nbsp;</p><p>## Package Plan ##</p><p>environment location: /home/hp/miniforge3/envs/jitENV</p><p>&nbsp;</p><p>Proceed ([y]/n)? y</p><p><br />Downloading and Extracting Packages:</p><p>Preparing transaction: done<br />Verifying transaction: done<br />Executing transaction: done<br />#<br /># To activate this environment, use<br />#<br /># $ conda activate jitENV<br />#<br /># To deactivate an active environment, use<br />#<br /># $ conda deactivate</p><p><strong>(base) hp@hp-HP-Z2-Tower-G9-Workstation-Desktop-PC:~/jitendraTEST$ conda activate jitENV</strong><br /><strong>(jitENV) hp@hp-HP-Z2-Tower-G9-Workstation-Desktop-PC:~/jitendraTEST$ conda install conda-forge::mamba</strong><br />Channels:<br /> - ursky<br /> - bioconda<br /> - conda-forge<br />Platform: linux-64<br />Collecting package metadata (repodata.json): done<br />Solving environment: done</p><p><br />==&gt; WARNING: A newer version of conda exists. &lt;==<br /> current version: 25.7.0<br /> latest version: 26.5.0</p><p>Please update conda by running</p><p>$ conda update -n base -c conda-forge conda</p><p>&nbsp;</p><p>## Package Plan ##</p><p>environment location: /home/hp/miniforge3/envs/jitENV</p><p>added / updated specs:<br /> - conda-forge::mamba</p><p><br />The following packages will be downloaded:</p><p>package | build<br /> ---------------------------|-----------------<br /> ca-certificates-2026.5.20 | hbd8a1cb_0 127 KB conda-forge<br /> cpp-expected-1.3.1 | h171cf75_0 24 KB conda-forge<br /> fmt-12.1.0 | hff5e90c_0 193 KB conda-forge<br /> libarchive-3.8.7 | gpl_hc2c16d8_101 869 KB conda-forge<br /> libcurl-8.20.0 | hcf29cc6_0 458 KB conda-forge<br /> libgcc-15.2.0 | he0feb66_19 1017 KB conda-forge<br /> libgcc-ng-15.2.0 | h69a702a_19 27 KB conda-forge<br /> libgomp-15.2.0 | he0feb66_19 590 KB conda-forge<br /> libmamba-2.6.2 | hd28c85e_0 2.7 MB conda-forge<br /> libmsgpack-c-6.1.0 | h54a6638_6 39 KB conda-forge<br /> libsolv-0.7.38 | h9463b59_0 509 KB conda-forge<br /> libstdcxx-15.2.0 | h934c35e_19 5.6 MB conda-forge<br /> libxml2-2.15.3 | h49c6c72_0 46 KB conda-forge<br /> libxml2-16-2.15.3 | hca6bf5a_0 547 KB conda-forge<br /> mamba-2.6.2 | hce6dcdd_0 553 KB conda-forge<br /> ncurses-6.6 | hdb14827_0 897 KB conda-forge<br /> nlohmann_json-abi-3.12.0 | h0f90c79_1 4 KB conda-forge<br /> reproc-14.2.7.post0 | hb03c661_1 35 KB conda-forge<br /> reproc-cpp-14.2.7.post0 | hecca717_1 26 KB conda-forge<br /> simdjson-4.6.4 | hb700be7_0 310 KB conda-forge<br /> spdlog-1.17.0 | hab81395_1 192 KB conda-forge<br /> ------------------------------------------------------------<br /> Total: 14.6 MB</p><p>The following NEW packages will be INSTALLED:</p><p>_openmp_mutex conda-forge/linux-64::_openmp_mutex-4.5-20_gnu <br /> bzip2 conda-forge/linux-64::bzip2-1.0.8-hda65f42_9 <br /> c-ares conda-forge/linux-64::c-ares-1.34.6-hb03c661_0 <br /> ca-certificates conda-forge/noarch::ca-certificates-2026.5.20-hbd8a1cb_0 <br /> cpp-expected conda-forge/linux-64::cpp-expected-1.3.1-h171cf75_0 <br /> fmt conda-forge/linux-64::fmt-12.1.0-hff5e90c_0 <br /> icu conda-forge/linux-64::icu-78.3-h33c6efd_0 <br /> keyutils conda-forge/linux-64::keyutils-1.6.3-hb9d3cd8_0 <br /> krb5 conda-forge/linux-64::krb5-1.22.2-ha1258a1_0 <br /> libarchive conda-forge/linux-64::libarchive-3.8.7-gpl_hc2c16d8_101 <br /> libcurl conda-forge/linux-64::libcurl-8.20.0-hcf29cc6_0 <br /> libedit conda-forge/linux-64::libedit-3.1.20250104-pl5321h7949ede_0 <br /> libev conda-forge/linux-64::libev-4.33-hd590300_2 <br /> libgcc conda-forge/linux-64::libgcc-15.2.0-he0feb66_19 <br /> libgcc-ng conda-forge/linux-64::libgcc-ng-15.2.0-h69a702a_19 <br /> libgomp conda-forge/linux-64::libgomp-15.2.0-he0feb66_19 <br /> libiconv conda-forge/linux-64::libiconv-1.18-h3b78370_2 <br /> liblzma conda-forge/linux-64::liblzma-5.8.3-hb03c661_0 <br /> libmamba conda-forge/linux-64::libmamba-2.6.2-hd28c85e_0 <br /> libmsgpack-c conda-forge/linux-64::libmsgpack-c-6.1.0-h54a6638_6 <br /> libnghttp2 conda-forge/linux-64::libnghttp2-1.68.1-h877daf1_0 <br /> libsolv conda-forge/linux-64::libsolv-0.7.38-h9463b59_0 <br /> libssh2 conda-forge/linux-64::libssh2-1.11.1-hcf80075_0 <br /> libstdcxx conda-forge/linux-64::libstdcxx-15.2.0-h934c35e_19 <br /> libxml2 conda-forge/linux-64::libxml2-2.15.3-h49c6c72_0 <br /> libxml2-16 conda-forge/linux-64::libxml2-16-2.15.3-hca6bf5a_0 <br /> libzlib conda-forge/linux-64::libzlib-1.3.2-h25fd6f3_2 <br /> lz4-c conda-forge/linux-64::lz4-c-1.10.0-h5888daf_1 <br /> lzo conda-forge/linux-64::lzo-2.10-h280c20c_1002 <br /> mamba conda-forge/linux-64::mamba-2.6.2-hce6dcdd_0 <br /> ncurses conda-forge/linux-64::ncurses-6.6-hdb14827_0 <br /> nlohmann_json-abi conda-forge/noarch::nlohmann_json-abi-3.12.0-h0f90c79_1 <br /> openssl conda-forge/linux-64::openssl-3.6.2-h35e630c_0 <br /> reproc conda-forge/linux-64::reproc-14.2.7.post0-hb03c661_1 <br /> reproc-cpp conda-forge/linux-64::reproc-cpp-14.2.7.post0-hecca717_1 <br /> simdjson conda-forge/linux-64::simdjson-4.6.4-hb700be7_0 <br /> spdlog conda-forge/linux-64::spdlog-1.17.0-hab81395_1 <br /> yaml-cpp conda-forge/linux-64::yaml-cpp-0.8.0-h3f2d84a_0 <br /> zstd conda-forge/linux-64::zstd-1.5.7-hb78ec9c_6</p><p><br />Proceed ([y]/n)? y</p><p><br />Downloading and Extracting Packages:<br /> <br />Preparing transaction: done <br />Verifying transaction: done <br />Executing transaction: done <br />(jitENV) hp@hp-HP-Z2-Tower-G9-Workstation-Desktop-PC:~/jitendraTEST$ mamba install -c jitendralab -c bioconda -c conda-forge crossroad -y <br />jitendralab/noarch ??.?MB @ ??.?MB/s 0.3s<br />jitendralab/linux-64 ??.?MB @ ??.?MB/s 0.4s<br />bioconda/linux-64 5.6MB @ 2.9MB/s 1.9s<br />bioconda/noarch 5.6MB @ 2.5MB/s 2.2s<br />conda-forge/noarch 26.4MB @ 6.0MB/s 4.5s<br />conda-forge/linux-64 53.8MB @ 6.7MB/s 8.2s</p><p><br />Transaction <br /> <br /> Prefix: /home/hp/miniforge3/envs/jitENV <br /> <br /> Updating specs: <br /> <br /> - crossroad</p><p>Package Version Build Channel Size<br />─────────────────────────────────────────────────────────────────────────────────────────────────<br /> Install:<br />─────────────────────────────────────────────────────────────────────────────────────────────────</p><p>+ annotated-doc 0.0.4 pyhcf101f3_0 conda-forge Cached<br /> + annotated-types 0.7.0 pyhd8ed1ab_1 conda-forge Cached<br /> + anyio 4.13.0 pyhcf101f3_0 conda-forge 147kB<br /> + argcomplete 3.6.3 pyhd8ed1ab_0 conda-forge Cached<br /> + aws-c-auth 0.10.3 h3aafcba_1 conda-forge 134kB<br /> + aws-c-cal 0.9.14 h8e43964_1 conda-forge 57kB<br /> + aws-c-common 0.13.1 hb03c661_0 conda-forge 242kB<br /> + aws-c-compression 0.3.2 h16e98cb_1 conda-forge 22kB<br /> + aws-c-event-stream 0.7.1 h9be7a74_1 conda-forge 59kB<br /> + aws-c-http 0.11.0 hcbcd92d_1 conda-forge 230kB<br /> + aws-c-io 0.26.3 h955231c_3 conda-forge 182kB<br /> + aws-c-mqtt 0.15.2 h8af55cf_3 conda-forge 222kB<br /> + aws-c-s3 0.12.3 h00bea6e_2 conda-forge 153kB<br /> + aws-c-sdkutils 0.2.4 h16e98cb_5 conda-forge 59kB<br /> + aws-checksums 0.2.10 h16e98cb_1 conda-forge 102kB<br /> + aws-crt-cpp 0.38.3 h7b0d4b4_2 conda-forge 413kB<br /> + aws-sdk-cpp 1.11.747 h5a171d8_5 conda-forge 4MB<br /> + azure-core-cpp 1.16.2 h206d751_0 conda-forge 349kB<br /> + azure-identity-cpp 1.13.3 hed0cdb0_1 conda-forge 251kB<br /> + azure-storage-blobs-cpp 12.17.0 hf824e48_1 conda-forge 587kB<br /> + azure-storage-common-cpp 12.13.0 ha7a2c86_0 conda-forge 159kB<br /> + azure-storage-files-datalake-cpp 12.15.0 h1e5b466_0 conda-forge 304kB<br /> + backports.zstd 1.5.0 py314h680f03e_0 conda-forge 8kB<br /> + bedtools 2.31.1 h13024bc_3 bioconda Cached<br /> + biopython 1.87 py314h5bd0f2a_0 conda-forge 3MB<br /> + brotli 1.2.0 hed03a55_1 conda-forge Cached<br /> + brotli-bin 1.2.0 hb03c661_1 conda-forge Cached<br /> + brotli-python 1.2.0 py314h3de4e8d_1 conda-forge 367kB<br /> + certifi 2026.5.20 pyhd8ed1ab_0 conda-forge 134kB<br /> + charset-normalizer 3.4.7 pyhd8ed1ab_0 conda-forge Cached<br /> + click 8.4.1 pyhc90fa1f_0 conda-forge 105kB<br /> + colorama 0.4.6 pyhd8ed1ab_1 conda-forge Cached<br /> + contourpy 1.3.3 py314h97ea11e_4 conda-forge 324kB<br /> + crossroad 0.3.6 pyh7e60211_0 jitendralab 2MB<br /> + cycler 0.12.1 pyhcf101f3_2 conda-forge Cached<br /> + dnspython 2.8.0 pyhcf101f3_0 conda-forge Cached<br /> + email-validator 2.3.0 pyhd8ed1ab_0 conda-forge 47kB<br /> + email_validator 2.3.0 hd8ed1ab_0 conda-forge 7kB<br /> + exceptiongroup 1.3.1 pyhd8ed1ab_0 conda-forge Cached<br /> + expat 2.8.1 hecca717_0 conda-forge 148kB<br /> + fastapi 0.136.3 h5ddb490_0 conda-forge 5kB<br /> + fastapi-cli 0.0.23 pyhcf101f3_0 conda-forge 19kB<br /> + fastapi-core 0.136.3 pyhcf101f3_0 conda-forge 96kB<br /> + fastar 0.11.0 py314h0b738fb_0 conda-forge 423kB<br /> + font-ttf-dejavu-sans-mono 2.37 hab24e00_0 conda-forge Cached<br /> + font-ttf-inconsolata 3.000 h77eed37_0 conda-forge Cached<br /> + font-ttf-source-code-pro 2.038 h77eed37_0 conda-forge Cached<br /> + font-ttf-ubuntu 0.83 h77eed37_3 conda-forge Cached<br /> + fontconfig 2.18.0 h27c8c51_0 conda-forge 281kB<br /> + fonts-conda-forge 1 hc364b38_1 conda-forge Cached<br /> + fonttools 4.63.0 pyh7db6752_0 conda-forge 846kB<br /> + freetype 2.14.3 ha770c72_0 conda-forge Cached<br /> + gflags 2.2.2 h5888daf_1005 conda-forge 120kB<br /> + glog 0.7.1 hbabe93e_0 conda-forge 143kB<br /> + h11 0.16.0 pyhcf101f3_1 conda-forge 39kB<br /> + h2 4.3.0 pyhcf101f3_0 conda-forge Cached<br /> + hpack 4.1.0 pyhd8ed1ab_0 conda-forge Cached<br /> + httpcore 1.0.9 pyh29332c3_0 conda-forge Cached<br /> + httptools 0.7.1 py314h5bd0f2a_1 conda-forge 99kB<br /> + httpx 0.28.1 pyhd8ed1ab_0 conda-forge Cached<br /> + hyperframe 6.1.0 pyhd8ed1ab_0 conda-forge Cached<br /> + idna 3.17 pyhcf101f3_0 conda-forge 57kB<br /> + jinja2 3.1.6 pyhcf101f3_1 conda-forge Cached<br /> + kaleido-core 0.2.1 h3644ca4_0 conda-forge Cached<br /> + kiwisolver 1.5.0 py314h97ea11e_0 conda-forge 77kB<br /> + lcms2 2.19.1 h0c24ade_0 conda-forge 251kB<br /> + ld_impl_linux-64 2.45.1 default_hbd61a6d_102 conda-forge Cached<br /> + lerc 4.1.0 hdb68285_0 conda-forge Cached<br /> + libabseil 20260107.1 cxx17_h7b12aa8_0 conda-forge 1MB<br /> + libarrow 24.0.0 h6f10b76_3_cpu conda-forge 7MB<br /> + libarrow-acero 24.0.0 h635bf11_3_cpu conda-forge 592kB<br /> + libarrow-compute 24.0.0 h53684a4_3_cpu conda-forge 3MB<br /> + libarrow-dataset 24.0.0 h635bf11_3_cpu conda-forge 592kB<br /> + libarrow-substrait 24.0.0 hb4dd7c2_3_cpu conda-forge 502kB<br /> + libblas 3.11.0 8_h4a7cf45_openblas conda-forge 19kB<br /> + libbrotlicommon 1.2.0 hb03c661_1 conda-forge Cached<br /> + libbrotlidec 1.2.0 hb03c661_1 conda-forge Cached<br /> + libbrotlienc 1.2.0 hb03c661_1 conda-forge Cached<br /> + libcblas 3.11.0 8_h0358290_openblas conda-forge 19kB<br /> + libcrc32c 1.1.2 h9c3ff4c_0 conda-forge Cached<br /> + libdeflate 1.25 h17f619e_0 conda-forge Cached<br /> + libevent 2.1.12 hf998b51_1 conda-forge Cached<br /> + libexpat 2.8.1 hecca717_0 conda-forge 77kB<br /> + libffi 3.5.2 h3435931_0 conda-forge Cached<br /> + libfreetype 2.14.3 ha770c72_0 conda-forge Cached<br /> + libfreetype6 2.14.3 h73754d4_0 conda-forge Cached<br /> + libgfortran 15.2.0 h69a702a_19 conda-forge 28kB<br /> + libgfortran5 15.2.0 h68bc16d_19 conda-forge 2MB<br /> + libgoogle-cloud 3.5.0 h25dbb67_0 conda-forge 3MB<br /> + libgoogle-cloud-storage 3.5.0 hdbdcf42_0 conda-forge 780kB<br /> + libgrpc 1.78.1 h1d1128b_0 conda-forge 7MB<br /> + libjpeg-turbo 3.1.4.1 hb03c661_0 conda-forge Cached<br /> + liblapack 3.11.0 8_h47877c9_openblas conda-forge 19kB<br /> + libmpdec 4.0.0 hb03c661_1 conda-forge 92kB<br /> + libopenblas 0.3.33 pthreads_h94d23a6_0 conda-forge 6MB<br /> + libopentelemetry-cpp 1.26.0 h9692893_0 conda-forge 934kB<br /> + libopentelemetry-cpp-headers 1.26.0 ha770c72_0 conda-forge 396kB<br /> + libparquet 24.0.0 h7376487_3_cpu conda-forge 1MB<br /> + libpng 1.6.58 h421ea60_0 conda-forge 318kB<br /> + libprotobuf 6.33.5 h6eeba95_1 conda-forge 4MB<br /> + libre2-11 2025.11.05 h0dc7533_1 conda-forge 213kB<br /> + libsqlite 3.53.1 h0c1763c_0 conda-forge 955kB<br /> + libstdcxx-ng 15.2.0 hdf11a46_19 conda-forge 28kB<br /> + libthrift 0.22.0 h7d032f7_2 conda-forge 424kB<br /> + libtiff 4.7.1 h9d88235_1 conda-forge Cached<br /> + libutf8proc 2.11.3 hfe17d71_0 conda-forge 86kB<br /> + libuuid 2.42.1 h5347b49_0 conda-forge 40kB<br /> + libuv 1.52.1 h280c20c_0 conda-forge 420kB<br /> + libwebp-base 1.6.0 hd42ef1d_0 conda-forge Cached<br /> + libxcb 1.17.0 h8a09558_0 conda-forge Cached<br /> + markdown-it-py 4.2.0 pyhd8ed1ab_0 conda-forge 69kB<br /> + markupsafe 3.0.3 py314h67df5f8_1 conda-forge 27kB<br /> + mathjax 2.7.7 ha770c72_3 conda-forge Cached<br /> + matplotlib-base 3.10.9 py314h1194b4b_0 conda-forge 9MB<br /> + mdurl 0.1.2 pyhd8ed1ab_1 conda-forge Cached<br /> + munkres 1.0.7 py_1 bioconda Cached<br /> + narwhals 2.21.2 pyhcf101f3_0 conda-forge 284kB<br /> + nlohmann_json 3.12.0 h54a6638_1 conda-forge 136kB<br /> + nspr 4.38 h29cc59b_0 conda-forge Cached<br /> + nss 3.118 h445c969_0 conda-forge Cached<br /> + numpy 2.4.6 py314h2b28147_0 conda-forge 9MB<br /> + openjpeg 2.5.4 h55fea9a_0 conda-forge Cached<br /> + orc 2.3.0 h21090e2_0 conda-forge 1MB<br /> + packaging 26.2 pyhc364b38_0 conda-forge 92kB<br /> + pandas 3.0.3 py314hb4ffadd_0 conda-forge 15MB<br /> + perf_ssr 0.4.8 py_0 jitendralab 720kB<br /> + pillow 12.2.0 py314h8ec4b1a_0 conda-forge 1MB<br /> + pip 26.1.1 pyh145f28c_0 conda-forge 1MB<br /> + plotly 6.6.0 pyhd8ed1ab_0 conda-forge Cached<br /> + plotly-upset-hd 0.0.2 py_0 jitendralab 356kB<br /> + prometheus-cpp 1.3.0 ha5d0236_0 conda-forge 200kB<br /> + pthread-stubs 0.4 hb9d3cd8_1002 conda-forge Cached<br /> + pyarrow 24.0.0 py314hdafbbf9_0 conda-forge 27kB<br /> + pyarrow-core 24.0.0 py314h969be7f_0_cpu conda-forge 5MB<br /> + pydantic 2.13.4 pyhcf101f3_0 conda-forge 347kB<br /> + pydantic-core 2.46.4 py314h2e6c369_0 conda-forge 2MB<br /> + pydantic-extra-types 2.11.2 pyhcf101f3_0 conda-forge 74kB<br /> + pydantic-settings 2.14.1 pyhcf101f3_0 conda-forge 52kB<br /> + pygments 2.20.0 pyhd8ed1ab_0 conda-forge Cached<br /> + pyparsing 3.3.2 pyhcf101f3_0 conda-forge Cached<br /> + pysocks 1.7.1 pyha55dd90_7 conda-forge Cached<br /> + python 3.14.5 habeac84_100_cp314 conda-forge 37MB<br /> + python-dateutil 2.9.0.post0 pyhe01879c_2 conda-forge Cached<br /> + python-dotenv 1.2.2 pyhcf101f3_0 conda-forge Cached<br /> + python-kaleido 0.2.1 pyhd8ed1ab_0 conda-forge Cached<br /> + python-multipart 0.0.29 pyhcf101f3_0 conda-forge 38kB<br /> + python_abi 3.14 8_cp314 conda-forge 7kB<br /> + pyyaml 6.0.3 py314h67df5f8_1 conda-forge 202kB<br /> + qhull 2020.2 h434a139_5 conda-forge Cached<br /> + re2 2025.11.05 h5301d42_1 conda-forge 27kB<br /> + readline 8.3 h853b02a_0 conda-forge Cached<br /> + requests 2.34.2 pyhcf101f3_0 conda-forge 69kB<br /> + rich 15.0.0 pyhcf101f3_0 conda-forge Cached<br /> + rich-argparse 1.8.0 pyhd8ed1ab_0 conda-forge 27kB<br /> + rich-click 1.9.8 pyh8f84b5b_0 conda-forge 64kB<br /> + rich-toolkit 0.19.10 pyhcf101f3_0 conda-forge 33kB<br /> + s2n 1.7.3 hc5a330e_0 conda-forge 388kB<br /> + seqkit 2.13.0 he881be0_0 bioconda Cached<br /> + seqtk 1.5 h577a1d6_1 bioconda 142kB<br /> + shellingham 1.5.4 pyhd8ed1ab_2 conda-forge Cached<br /> + six 1.17.0 pyhe01879c_1 conda-forge Cached<br /> + snappy 1.2.2 h03e3b7b_1 conda-forge Cached<br /> + sniffio 1.3.1 pyhd8ed1ab_2 conda-forge Cached<br /> + sqlite 3.53.1 hbc0de68_0 conda-forge 205kB<br /> + starlette 1.1.0 pyhcf101f3_0 conda-forge 64kB<br /> + tk 8.6.13 noxft_h366c992_103 conda-forge Cached<br /> + tomli 2.4.1 pyhcf101f3_0 conda-forge 22kB<br /> + tqdm 4.67.3 pyh8f84b5b_0 conda-forge Cached<br /> + typer 0.26.3 pyhcf101f3_0 conda-forge 184kB<br /> + typing-extensions 4.15.0 h396c80c_0 conda-forge Cached<br /> + typing-inspection 0.4.2 pyhcf101f3_2 conda-forge 21kB<br /> + typing_extensions 4.15.0 pyhcf101f3_0 conda-forge Cached<br /> + tzdata 2025c hc9c84f9_1 conda-forge Cached<br /> + unicodedata2 17.0.1 py314h5bd0f2a_0 conda-forge 410kB<br /> + upsetplot 0.9.0 pyhd8ed1ab_1 conda-forge 28kB<br /> + urllib3 2.7.0 pyhd8ed1ab_0 conda-forge 104kB<br /> + uvicorn 0.48.0 pyhc90fa1f_0 conda-forge 56kB<br /> + uvicorn-standard 0.48.0 he364bde_0 conda-forge 4kB<br /> + uvloop 0.22.1 py314h5bd0f2a_1 conda-forge 593kB<br /> + watchfiles 1.2.0 py314ha5689aa_0 conda-forge 416kB<br /> + websockets 16.0 py314h0f05182_1 conda-forge 383kB<br /> + xorg-libxau 1.0.12 hb03c661_1 conda-forge Cached<br /> + xorg-libxdmcp 1.1.5 hb03c661_1 conda-forge Cached<br /> + yaml 0.2.5 h280c20c_3 conda-forge Cached<br /> + zlib 1.3.2 h25fd6f3_2 conda-forge Cached<br /> + zlib-ng 2.3.3 hceb46e0_1 conda-forge Cached</p><p>Summary:</p><p>Install: 186 packages</p><p>Total download: 142MB</p><p>─────────────────────────────────────────────────────────────────────────────────────────────────</p><p>&nbsp;</p><p>Transaction starting<br />libgrpc 7.0MB @ 2.3MB/s 3.0s<br />numpy 8.9MB @ 2.3MB/s 3.8s<br />matplotlib-base 8.5MB @ 2.0MB/s 4.2s<br />libarrow 6.5MB @ 2.3MB/s 2.8s<br />pandas 15.3MB @ 2.5MB/s 6.2s<br />libopenblas 5.9MB @ 2.3MB/s 2.5s<br />pyarrow-core 4.8MB @ 1.6MB/s 3.0s<br />libprotobuf 3.7MB @ 2.4MB/s 1.6s<br />aws-sdk-cpp 3.6MB @ 3.1MB/s 1.2s<br />biopython 3.4MB @ 2.0MB/s 1.7s<br />libgfortran5 2.5MB @ 2.6MB/s 1.0s<br />libgoogle-cloud 2.6MB @ 2.4MB/s 1.1s<br />pydantic-core 1.9MB @ 2.7MB/s 0.7s<br />libarrow-compute 3.0MB @ 1.9MB/s 1.6s<br />orc 1.5MB @ 2.8MB/s 0.5s<br />libparquet 1.4MB @ 3.1MB/s 0.5s<br />pip 1.2MB @ 2.9MB/s 0.4s<br />libabseil 1.4MB @ 2.2MB/s 0.6s<br />pillow 1.1MB @ 2.7MB/s 0.4s<br />libsqlite 955.0kB @ 2.9MB/s 0.3s<br />libgoogle-cloud-storage 779.6kB @ 2.7MB/s 0.3s<br />fonttools 846.0kB @ 2.1MB/s 0.4s<br />libopentelemetry-cpp 934.3kB @ 1.8MB/s 0.5s<br />libarrow-acero 592.3kB @ 2.2MB/s 0.2s<br />uvloop 593.4kB @ 1.3MB/s 0.4s<br />libarrow-dataset 592.2kB @ 2.7MB/s 0.2s<br />libarrow-substrait 501.9kB @ 1.8MB/s 0.2s<br />azure-storage-blobs-cpp 587.1kB @ 1.6MB/s 0.3s<br />libthrift 423.9kB @ 2.8MB/s 0.2s<br />crossroad 1.8MB @ 663.3kB/s 2.6s<br />libuv 419.9kB @ 2.3MB/s 0.2s<br />fastar 423.4kB @ 966.7kB/s 0.3s<br />aws-crt-cpp 412.5kB @ 2.9MB/s 0.1s<br />watchfiles 415.6kB @ 1.6MB/s 0.3s<br />unicodedata2 409.6kB @ 1.8MB/s 0.2s<br />libopentelemetry-cpp-headers 396.4kB @ 2.2MB/s 0.2s<br />s2n 388.1kB @ 2.5MB/s 0.1s<br />brotli-python 367.4kB @ 1.7MB/s 0.1s<br />websockets 383.0kB @ 1.3MB/s 0.3s<br />azure-core-cpp 348.7kB @ 2.7MB/s 0.1s<br />pydantic 346.5kB @ 1.9MB/s 0.2s<br />contourpy 324.0kB @ 2.3MB/s 0.1s<br />libpng 317.7kB @ 1.8MB/s 0.2s<br />azure-storage-files-datalake-cpp 303.8kB @ 1.9MB/s 0.1s<br />narwhals 284.3kB @ 1.8MB/s 0.2s<br />fontconfig 280.9kB @ 866.6kB/s 0.2s<br />python 36.7MB @ 3.0MB/s 12.0s<br />azure-identity-cpp 250.5kB @ 1.5MB/s 0.1s<br />lcms2 251.1kB @ 2.0MB/s 0.1s<br />aws-c-common 242.3kB @ 2.8MB/s 0.1s<br />libre2-11 213.1kB @ 66.4kB/s 0.1s<br />aws-c-http 230.3kB @ 1.7MB/s 0.1s<br />aws-c-mqtt 221.7kB @ 307.2kB/s 0.1s<br />sqlite 205.4kB @ ??.?MB/s 0.1s<br />perf_ssr 720.0kB @ 247.3kB/s 2.3s<br />prometheus-cpp 199.5kB @ 962.8kB/s 0.1s<br />pyyaml 202.4kB @ 1.6MB/s 0.1s<br />typer 184.4kB @ 1.9MB/s 0.1s<br />aws-c-io 181.6kB @ 1.9MB/s 0.1s<br />aws-c-s3 153.0kB @ 2.2MB/s 0.1s<br />azure-storage-common-cpp 159.1kB @ 1.8MB/s 0.1s<br />expat 148.2kB @ ??.?MB/s 0.0s<br />anyio 146.8kB @ 2.2MB/s 0.1s<br />glog 143.5kB @ 2.6MB/s 0.1s<br />seqtk 141.8kB @ 1.8MB/s 0.1s<br />nlohmann_json 136.2kB @ 2.1MB/s 0.1s<br />aws-c-auth 134.4kB @ 1.5MB/s 0.1s<br />certifi 134.2kB @ 1.8MB/s 0.1s<br />click 105.0kB @ 1.5MB/s 0.1s<br />gflags 119.7kB @ 148.2kB/s 0.1s<br />urllib3 103.6kB @ ??.?MB/s 0.0s<br />aws-checksums 101.6kB @ ??.?MB/s 0.0s<br />fastapi-core 95.5kB @ ??.?MB/s 0.0s<br />libmpdec 92.4kB @ ??.?MB/s 0.0s<br />packaging 91.6kB @ ??.?MB/s 0.0s<br />libutf8proc 86.0kB @ ??.?MB/s 0.0s<br />kiwisolver 77.4kB @ ??.?MB/s 0.0s<br />libexpat 77.3kB @ 885.4kB/s 0.1s<br />pydantic-extra-types 73.9kB @ ??.?MB/s 0.0s<br />markdown-it-py 69.0kB @ ??.?MB/s 0.0s<br />requests 68.7kB @ ??.?MB/s 0.0s<br />rich-click 64.4kB @ ??.?MB/s 0.0s<br />aws-c-event-stream 59.3kB @ ??.?MB/s 0.0s<br />starlette 63.7kB @ ??.?MB/s 0.0s<br />aws-c-sdkutils 59.1kB @ ??.?MB/s 0.0s<br />aws-c-cal 56.9kB @ ??.?MB/s 0.0s<br />idna 56.9kB @ ??.?MB/s 0.0s<br />uvicorn 56.3kB @ ??.?MB/s 0.0s<br />pydantic-settings 52.3kB @ ??.?MB/s 0.0s<br />email-validator 46.8kB @ ??.?MB/s 0.0s<br />libuuid 40.2kB @ ??.?MB/s 0.0s<br />h11 39.1kB @ ??.?MB/s 0.0s<br />python-multipart 37.8kB @ ??.?MB/s 0.0s<br />rich-toolkit 32.9kB @ ??.?MB/s 0.0s<br />upsetplot 28.0kB @ ??.?MB/s 0.0s<br />libstdcxx-ng 27.8kB @ ??.?MB/s 0.0s<br />libgfortran 27.7kB @ ??.?MB/s 0.0s<br />re2 27.5kB @ ??.?MB/s 0.0s<br />markupsafe 27.4kB @ ??.?MB/s 0.0s<br />pyarrow 26.8kB @ ??.?MB/s 0.0s<br />aws-c-compression 22.0kB @ ??.?MB/s 0.0s<br />tomli 21.6kB @ ??.?MB/s 0.0s<br />typing-inspection 20.9kB @ ??.?MB/s 0.0s<br />fastapi-cli 18.9kB @ ??.?MB/s 0.0s<br />libblas 18.8kB @ ??.?MB/s 0.0s<br />httptools 99.0kB @ ??.?MB/s 0.4s<br />liblapack 18.8kB @ ??.?MB/s 0.0s<br />libcblas 18.8kB @ ??.?MB/s 0.0s<br />email_validator 7.1kB @ ??.?MB/s 0.0s<br />backports.zstd 7.5kB @ ??.?MB/s 0.0s<br />python_abi 7.0kB @ ??.?MB/s 0.0s<br />fastapi 4.8kB @ ??.?MB/s 0.0s<br />uvicorn-standard 4.1kB @ ??.?MB/s 0.0s<br />rich-argparse 26.8kB @ ??.?MB/s 0.2s<br />plotly-upset-hd 356.0kB @ 181.5kB/s 1.8s<br />Linking seqkit-2.13.0-he881be0_0<br />Linking bedtools-2.31.1-h13024bc_3<br />Linking seqtk-1.5-h577a1d6_1<br />Linking libuuid-2.42.1-h5347b49_0<br />Linking readline-8.3-h853b02a_0<br />Linking libexpat-2.8.1-hecca717_0<br />Linking nspr-4.38-h29cc59b_0<br />Linking mathjax-2.7.7-ha770c72_3<br />Linking libuv-1.52.1-h280c20c_0<br />Linking yaml-0.2.5-h280c20c_3<br />Linking ld_impl_linux-64-2.45.1-default_hbd61a6d_102<br />Linking libmpdec-4.0.0-hb03c661_1<br />Linking libwebp-base-1.6.0-hd42ef1d_0<br />Linking zlib-ng-2.3.3-hceb46e0_1<br />Linking libstdcxx-ng-15.2.0-hdf11a46_19<br />Linking pthread-stubs-0.4-hb9d3cd8_1002<br />Linking xorg-libxau-1.0.12-hb03c661_1<br />Linking xorg-libxdmcp-1.1.5-hb03c661_1<br />Linking libgfortran5-15.2.0-h68bc16d_19<br />Linking libpng-1.6.58-h421ea60_0<br />Linking libbrotlicommon-1.2.0-hb03c661_1<br />Linking libjpeg-turbo-3.1.4.1-hb03c661_0<br />Linking libdeflate-1.25-h17f619e_0<br />Linking lerc-4.1.0-hdb68285_0<br />Linking libsqlite-3.53.1-h0c1763c_0<br />Linking libffi-3.5.2-h3435931_0<br />Linking tk-8.6.13-noxft_h366c992_103<br />Linking azure-core-cpp-1.16.2-h206d751_0<br />Linking libabseil-20260107.1-cxx17_h7b12aa8_0<br />Linking libutf8proc-2.11.3-hfe17d71_0<br />Linking libopentelemetry-cpp-headers-1.26.0-ha770c72_0<br />Linking zlib-1.3.2-h25fd6f3_2<br />Linking snappy-1.2.2-h03e3b7b_1<br />Linking nlohmann_json-3.12.0-h54a6638_1<br />Linking aws-c-common-0.13.1-hb03c661_0<br />Linking s2n-1.7.3-hc5a330e_0<br />Linking gflags-2.2.2-h5888daf_1005<br />Linking libevent-2.1.12-hf998b51_1<br />Linking expat-2.8.1-hecca717_0<br />Linking libcrc32c-1.1.2-h9c3ff4c_0<br />Linking qhull-2020.2-h434a139_5<br />Linking libxcb-1.17.0-h8a09558_0<br />Linking libgfortran-15.2.0-h69a702a_19<br />Linking libfreetype6-2.14.3-h73754d4_0<br />Linking libbrotlienc-1.2.0-hb03c661_1<br />Linking libbrotlidec-1.2.0-hb03c661_1<br />Linking libtiff-4.7.1-h9d88235_1<br />Linking sqlite-3.53.1-hbc0de68_0<br />Linking nss-3.118-h445c969_0<br />Linking azure-identity-cpp-1.13.3-hed0cdb0_1<br />Linking azure-storage-common-cpp-12.13.0-ha7a2c86_0<br />Linking libprotobuf-6.33.5-h6eeba95_1<br />Linking libre2-11-2025.11.05-h0dc7533_1<br />Linking prometheus-cpp-1.3.0-ha5d0236_0<br />Linking aws-c-compression-0.3.2-h16e98cb_1<br />Linking aws-checksums-0.2.10-h16e98cb_1<br />Linking aws-c-sdkutils-0.2.4-h16e98cb_5<br />Linking aws-c-cal-0.9.14-h8e43964_1<br />Linking glog-0.7.1-hbabe93e_0<br />Linking libthrift-0.22.0-h7d032f7_2<br />Linking libopenblas-0.3.33-pthreads_h94d23a6_0<br />Linking libfreetype-2.14.3-ha770c72_0<br />Linking brotli-bin-1.2.0-hb03c661_1<br />Linking lcms2-2.19.1-h0c24ade_0<br />Linking openjpeg-2.5.4-h55fea9a_0<br />Linking azure-storage-blobs-cpp-12.17.0-hf824e48_1<br />Linking re2-2025.11.05-h5301d42_1<br />Linking aws-c-io-0.26.3-h955231c_3<br />Linking libblas-3.11.0-8_h4a7cf45_openblas<br />Linking fontconfig-2.18.0-h27c8c51_0<br />Linking freetype-2.14.3-ha770c72_0<br />Linking brotli-1.2.0-hed03a55_1<br />Linking azure-storage-files-datalake-cpp-12.15.0-h1e5b466_0<br />Linking libgrpc-1.78.1-h1d1128b_0<br />Linking aws-c-event-stream-0.7.1-h9be7a74_1<br />Linking aws-c-http-0.11.0-hcbcd92d_1<br />Linking libcblas-3.11.0-8_h0358290_openblas<br />Linking liblapack-3.11.0-8_h47877c9_openblas<br />Linking libopentelemetry-cpp-1.26.0-h9692893_0<br />Linking aws-c-auth-0.10.3-h3aafcba_1<br />Linking aws-c-mqtt-0.15.2-h8af55cf_3<br />Linking libgoogle-cloud-3.5.0-h25dbb67_0<br />Linking aws-c-s3-0.12.3-h00bea6e_2<br />Linking libgoogle-cloud-storage-3.5.0-hdbdcf42_0<br />Linking aws-crt-cpp-0.38.3-h7b0d4b4_2<br />Linking aws-sdk-cpp-1.11.747-h5a171d8_5<br />Linking python_abi-3.14-8_cp314<br />Linking font-ttf-dejavu-sans-mono-2.37-hab24e00_0<br />Linking tzdata-2025c-hc9c84f9_1<br />Linking font-ttf-ubuntu-0.83-h77eed37_3<br />Linking font-ttf-inconsolata-3.000-h77eed37_0<br />Linking font-ttf-source-code-pro-2.038-h77eed37_0<br />Linking fonts-conda-forge-1-hc364b38_1<br />Linking orc-2.3.0-h21090e2_0<br />Linking python-3.14.5-habeac84_100_cp314<br />Linking kaleido-core-0.2.1-h3644ca4_0<br />Linking libarrow-24.0.0-h6f10b76_3_cpu<br />Linking libparquet-24.0.0-h7376487_3_cpu<br />Linking libarrow-compute-24.0.0-h53684a4_3_cpu<br />Linking libarrow-acero-24.0.0-h635bf11_3_cpu<br />Linking libarrow-dataset-24.0.0-h635bf11_3_cpu<br />Linking libarrow-substrait-24.0.0-hb4dd7c2_3_cpu<br />Linking pip-26.1.1-pyh145f28c_0<br />Linking tomli-2.4.1-pyhcf101f3_0<br />Linking six-1.17.0-pyhe01879c_1<br />Linking pysocks-1.7.1-pyha55dd90_7<br />Linking hyperframe-6.1.0-pyhd8ed1ab_0<br />Linking hpack-4.1.0-pyhd8ed1ab_0<br />Linking backports.zstd-1.5.0-py314h680f03e_0<br />Linking pyparsing-3.3.2-pyhcf101f3_0<br />Linking cycler-0.12.1-pyhcf101f3_2<br />Linking sniffio-1.3.1-pyhd8ed1ab_2<br />Linking mdurl-0.1.2-pyhd8ed1ab_1<br />Linking narwhals-2.21.2-pyhcf101f3_0<br />Linking packaging-26.2-pyhc364b38_0<br />Linking charset-normalizer-3.4.7-pyhd8ed1ab_0<br />Linking certifi-2026.5.20-pyhd8ed1ab_0<br />Linking idna-3.17-pyhcf101f3_0<br />Linking pygments-2.20.0-pyhd8ed1ab_0<br />Linking shellingham-1.5.4-pyhd8ed1ab_2<br />Linking annotated-doc-0.0.4-pyhcf101f3_0<br />Linking colorama-0.4.6-pyhd8ed1ab_1<br />Linking typing_extensions-4.15.0-pyhcf101f3_0<br />Linking click-8.4.1-pyhc90fa1f_0<br />Linking tqdm-4.67.3-pyh8f84b5b_0<br />Linking python-kaleido-0.2.1-pyhd8ed1ab_0<br />Linking python-multipart-0.0.29-pyhcf101f3_0<br />Linking python-dotenv-1.2.2-pyhcf101f3_0<br />Linking argcomplete-3.6.3-pyhd8ed1ab_0<br />Linking python-dateutil-2.9.0.post0-pyhe01879c_2<br />Linking h2-4.3.0-pyhcf101f3_0<br />Linking dnspython-2.8.0-pyhcf101f3_0<br />Linking markdown-it-py-4.2.0-pyhd8ed1ab_0<br />Linking plotly-6.6.0-pyhd8ed1ab_0<br />Linking exceptiongroup-1.3.1-pyhd8ed1ab_0<br />Linking typing-inspection-0.4.2-pyhcf101f3_2<br />Linking typing-extensions-4.15.0-h396c80c_0<br />Linking h11-0.16.0-pyhcf101f3_1<br />Linking email-validator-2.3.0-pyhd8ed1ab_0<br />Linking rich-15.0.0-pyhcf101f3_0<br />Linking anyio-4.13.0-pyhcf101f3_0<br />Linking annotated-types-0.7.0-pyhd8ed1ab_1<br />Linking uvicorn-0.48.0-pyhc90fa1f_0<br />Linking email_validator-2.3.0-hd8ed1ab_0<br />Linking rich-toolkit-0.19.10-pyhcf101f3_0<br />Linking typer-0.26.3-pyhcf101f3_0<br />Linking rich-click-1.9.8-pyh8f84b5b_0<br />Linking rich-argparse-1.8.0-pyhd8ed1ab_0<br />Linking httpcore-1.0.9-pyh29332c3_0<br />Linking starlette-1.1.0-pyhcf101f3_0<br />Linking httpx-0.28.1-pyhd8ed1ab_0<br />Linking pyarrow-core-24.0.0-py314h969be7f_0_cpu<br />Linking unicodedata2-17.0.1-py314h5bd0f2a_0<br />Linking brotli-python-1.2.0-py314h3de4e8d_1<br />Linking pillow-12.2.0-py314h8ec4b1a_0<br />Linking kiwisolver-1.5.0-py314h97ea11e_0<br />Linking fastar-0.11.0-py314h0b738fb_0<br />Linking markupsafe-3.0.3-py314h67df5f8_1<br />Linking websockets-16.0-py314h0f05182_1<br />Linking uvloop-0.22.1-py314h5bd0f2a_1<br />Linking pyyaml-6.0.3-py314h67df5f8_1<br />Linking httptools-0.7.1-py314h5bd0f2a_1<br />Linking numpy-2.4.6-py314h2b28147_0<br />Linking pydantic-core-2.46.4-py314h2e6c369_0<br />Linking watchfiles-1.2.0-py314ha5689aa_0<br />Linking pyarrow-24.0.0-py314hdafbbf9_0<br />Linking contourpy-1.3.3-py314h97ea11e_4<br />Linking biopython-1.87-py314h5bd0f2a_0<br />Linking pandas-3.0.3-py314hb4ffadd_0<br />Linking munkres-1.0.7-py_1<br />Linking urllib3-2.7.0-pyhd8ed1ab_0<br />Linking jinja2-3.1.6-pyhcf101f3_1<br />Linking pydantic-2.13.4-pyhcf101f3_0<br />Linking uvicorn-standard-0.48.0-he364bde_0<br />Linking fonttools-4.63.0-pyh7db6752_0<br />Linking requests-2.34.2-pyhcf101f3_0<br />Linking pydantic-settings-2.14.1-pyhcf101f3_0<br />Linking pydantic-extra-types-2.11.2-pyhcf101f3_0<br />Linking fastapi-core-0.136.3-pyhcf101f3_0<br />Linking fastapi-cli-0.0.23-pyhcf101f3_0<br />Linking fastapi-0.136.3-h5ddb490_0<br />Linking plotly-upset-hd-0.0.2-py_0<br />Linking matplotlib-base-3.10.9-py314h1194b4b_0<br />Linking upsetplot-0.9.0-pyhd8ed1ab_1<br />Linking perf_ssr-0.4.8-py_0<br />Linking crossroad-0.3.6-pyh7e60211_0</p><p>Transaction finished</p><p><strong>(jitENV) hp@hp-HP-Z2-Tower-G9-Workstation-Desktop-PC:~/jitendraTEST$ crossroad -h</strong><br /> <br /> Usage: crossroad [OPTIONS] <br /> <br /> Run the main croSSRoad analysis pipeline, or manage jobs. <br /> <br />╭─ Options ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮<br />│ --version -v Show version, logo, citation, and links. │<br />│ --install-completion Install completion for the current shell. │<br />│ --show-completion Show completion for the current shell, to copy it or customize the installation. │<br />│ --help -h Show this message and exit. │<br />╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯<br />╭─ Mode Selection ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮<br />│ --api -a Run the Crossroad web API server. │<br />│ --slurm -s Submit the analysis job to a Slurm cluster. │<br />│ --job-status JOB_ID Query the status of a specific job ID. │<br />╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯<br />╭─ Input Files (provide --input-dir OR --fasta) ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮<br />│ --input-dir -i PATH Directory containing: `all_genome.fa`, ``, ``. Exclusive with `--fasta`. │<br />│ --fasta -fa PATH Input FASTA file (e.g., `all_genome.fa`). Alternative to `--input-dir`. │<br />│ --categories -c PATH Genome categories TSV file. Optional if using `--fasta`. Ignored if `--input-dir` is used (looks for `genome_categories.tsv` inside). │<br />│ --gene-bed -b PATH Gene BED file for SSR-gene analysis. Optional. If `--input-dir` is used, looks for `gene.bed` inside. │<br />╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯<br />╭─ Analysis Parameters ────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮<br />│ --reference-id -ref TEXT Reference genome ID for comparative analysis. Optional parameter for reference-based comparisons. │<br />│ --output-dir -o DIRECTORY Base output directory for jobs. Overrides CROSSROAD_JOB_DIR env var. │<br />│ --flanks -f Process flanking regions. │<br />╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯<br />╭─ PERF SSR Detection Parameters ──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮<br />│ --mono INTEGER Mononucleotide repeat threshold. [default: 12] │<br />│ --di INTEGER Dinucleotide repeat threshold. [default: 6] │<br />│ --tri INTEGER Trinucleotide repeat threshold. [default: 4] │<br />│ --tetra INTEGER Tetranucleotide repeat threshold. [default: 3] │<br />│ --penta INTEGER Pentanucleotide repeat threshold. [default: 3] │<br />│ --hexa INTEGER Hexanucleotide repeat threshold. [default: 2] │<br />╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯<br />╭─ Filtering Parameters ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮<br />│ --min-len -l INTEGER Minimum genome length for filtering. [default: 1000] │<br />│ --max-len -L INTEGER Maximum genome length for filtering. [default: 10000000] │<br />│ --unfair -u INTEGER Maximum number of N's allowed per genome for Crossroad analysis. [default: 0] │<br />│ --repeat-threshold -rc INTEGER Repeat count Threshold for hotspot filtering (keeps records &gt; this value). [default: 1] │<br />│ --genome-threshold -g INTEGER Genome count Threshold for hotspot filtering (keeps records &gt; this value). [default: 2] │<br />╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯<br />╭─ Performance &amp; Output ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╮<br />│ --threads -t INTEGER Number of threads for Crossroad analysis. [default: 50] │<br />│ --plots -p Enable plot generation. │<br />│ --intrim-dir TEXT Name for the intermediate files directory (within the main job output dir). [default: intrim] │<br />╰──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯</p><p>(jitENV) hp@hp-HP-Z2-Tower-G9-Workstation-Desktop-PC:~/jitendraTEST$</p><p>&nbsp;</p>]]></description>
	<dc:creator>ComBioX</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10664/dna-replication-process-3d-animation</guid>
	<pubDate>Sat, 10 May 2014 04:41:22 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10664/dna-replication-process-3d-animation</link>
	<title><![CDATA[DNA Replication Process [3D Animation]]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/27TxKoFU2Nw" frameborder="0" allowfullscreen></iframe>See an organised list of all the animations: http://doctorprodigious.wordpress.com/hd-animations/]]></description>
	
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/38752/hgtector-an-automated-method-facilitating-genome-wide-discovery-of-putative-horizontal-gene-transfers</guid>
	<pubDate>Mon, 21 Jan 2019 06:50:05 -0600</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/38752/hgtector-an-automated-method-facilitating-genome-wide-discovery-of-putative-horizontal-gene-transfers</link>
	<title><![CDATA[HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers]]></title>
	<description><![CDATA[<p>A computational pipeline for genome-wide detection of putative horizontal gene transfer (HGT) events based on sequence homology search hit distribution statistics</p>
<p>Authors: Qiyun Zhu (<a href="mailto:qiyunzhu@gmail.com">qiyunzhu@gmail.com</a>), Katharina Dittmar (<a href="mailto:katharinad@gmail.com">katharinad@gmail.com</a>)</p>
<p>Affiliation: Department of Biological Sciences, University at Buffalo, State University of New York, Buffalo, USA</p>
<p>Zhu Q, Kosoy M, Dittmar K. HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers.&nbsp;<em style="font-size: 12.8px;">BMC Genomics</em>. 2014. 15:717.</p>
<p>Usage: Simply execute&nbsp;<span style="font-size: 12.8px;">perl HGTector.pl</span>, or, open&nbsp;<span style="font-size: 12.8px;">GUI.html</span>&nbsp;in a web browser to see a step-by-step wizard.</p>
<p>Download&nbsp;<a href="https://github.com/DittmarLab/HGTector/archive/0.2.2.zip">HGTector 0.2.2</a>.</p><p>Address of the bookmark: <a href="https://github.com/DittmarLab/HGTector" rel="nofollow">https://github.com/DittmarLab/HGTector</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10748/bioinformatics-phd-at-cuk-kerala</guid>
  <pubDate>Sat, 10 May 2014 20:21:22 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics PhD at CUK Kerala]]></title>
  <description><![CDATA[
<p>Applications are invited from highly motivated students (UGC-CSIR-JRF) with a background in Genomics/ Biotechnology/ Molecular Microbiology/ Biochemistry and Bioinformatics to pursue research leading to Ph.D. in the following areas;</p>

<p>    1. Cancer Genomics</p>

<p>    2. Microbial Genetics and Metagenomics</p>

<p>    3. Human Infective Diseases</p>

<p>    4. Computational Drug Design</p>

<p>Interested candidates may apply to Dr. Ranjith N. Kumavath, Assistant Professor &amp; Head, Department of Genomic Science, School of Biological Sciences, Central University of Kerala, Padannakad (PO), Nileshwar, Kasaragod-671328,Kerala. Email: RNkumavath@gmail.com</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/11175/next-generation-sequencingngs-books</guid>
	<pubDate>Fri, 30 May 2014 04:48:04 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/11175/next-generation-sequencingngs-books</link>
	<title><![CDATA[Next generation sequencing(NGS) books]]></title>
	<description><![CDATA[<p>Employing different technologies, the purpose of NGS platform is to decode the identity or modification on the nucleotides. NGS platforms evolve quickly and capture the main stream.</p>
<p>This bookmark is created to provide NGS online books links.</p><p>Address of the bookmark: <a href="http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version" rel="nofollow">http://en.wikibooks.org/wiki/Next_Generation_Sequencing_%28NGS%29/Print_version</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10925/a-brief-bioinformatics-tutorial</guid>
	<pubDate>Wed, 21 May 2014 12:50:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10925/a-brief-bioinformatics-tutorial</link>
	<title><![CDATA[A Brief Bioinformatics Tutorial]]></title>
	<description><![CDATA[<p>This is about how to use a computer to find what is known about a gene of interest and also how to get new insights about it.</p>
<p>The tutorial is divided in three main parts:</p>
<ul>
<li>In the <strong>Sequence </strong>part, you will see how to look efficiently for a particular protein sequence, how to blast it against the database of your choice to find homologues, how to perform a multiple alignment of the homologues you've selected and how to edit this alignment.</li>
<li>The <strong>Structure </strong>part is about molecular visualization, homology modeling and structural domain prediction.</li>
<li>In the <strong>Function </strong>part, you will be introduced to you 3 useful servers to investigate the function of a protein. i.e. finding interactors, co-expressed genes, see a phylogenetic profile, easily access papers citing your gene etc ...</li>
</ul>
<p>During all the three parts, we will use the <em>S. cerevisiae </em>VPS36 protein as an example.</p><p>Address of the bookmark: <a href="http://www.mrc-lmb.cam.ac.uk/rlw/text/bioinfo_tuto/introduction.html" rel="nofollow">http://www.mrc-lmb.cam.ac.uk/rlw/text/bioinfo_tuto/introduction.html</a></p>]]></description>
	<dc:creator>Jit</dc:creator>
</item>

<item>
  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/13014/bioinformatics-jrf-vacancy-at-icgeb-new-delhi</guid>
  <pubDate>Wed, 23 Jul 2014 16:07:15 -0500</pubDate>
  <link></link>
  <title><![CDATA[Bioinformatics JRF vacancy at ICGEB, New Delhi]]></title>
  <description><![CDATA[
<p>Junior Research Fellow for a DBT sponsored project entitled "Computational and experimental characterization of stage specific arginine methylation in P. falciparum proteome". </p>

<p>Candidates should have a 1st class MSc/MTech/BTech degree in Bioinformatics. Please send complete CV, quoting Application for RMETH-JRF-2014, by email to Dr. Dinesh Gupta: dinesh@icgeb.res.in</p>

<p>Closing date for applications: 6 August 2014</p>

<p>More at http://www.icgeb.org/tl_files/Vacancies/JRF.pdf</p>
]]></description>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11313/linux-sort-commands-for-bioinformatics</guid>
	<pubDate>Sat, 31 May 2014 15:41:16 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11313/linux-sort-commands-for-bioinformatics</link>
	<title><![CDATA[Linux Sort Commands for Bioinformatics]]></title>
	<description><![CDATA[<p>Almost all the scripting languages such as Perl, Python etc have built-in sort, but unfortunately none of them are as flexible as sort command. But one when it come to space efficiency GNU sort stands at the top. It can sort a 20Gb file with less than 2Gb memory. It is not trivial to implement so powerful a sort by yourself.</p><p>sort a space-delimited file based on its first column, then the second if the first is the same, and so on:<br />sort input.txt</p><p>sort a huge file (GNU sort ONLY):<br />sort -S 1500M -t $HOME/tmp input.txt &gt; sorted.txt</p><p>sort starting from the third column, skipping the first two columns:<br />sort +2 input.txt</p><p>sort the second column as numbers, descending order; if identical, sort the 3rd as strings, ascending order:<br />sort -k2,2nr -k3,3 input.txt</p><p>sort starting from the 4th character at column 2, as numbers:<br />sort -k2.4n input.txt</p><p>More Linxu sort command information<br /><br />If you have any sort commands you'd like to share, please add them to our comments section below. For more help, you can also type:<br /><br />man sort<br /><br />or<br /><br />sort --help<br /><br />on your Unix/Linux system.</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
</item>
<item>
	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11399/next-generation-sequencing-in-r-or-bioconductor-environment</guid>
	<pubDate>Mon, 02 Jun 2014 18:03:09 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11399/next-generation-sequencing-in-r-or-bioconductor-environment</link>
	<title><![CDATA[Next generation sequencing in R or bioconductor environment]]></title>
	<description><![CDATA[<p>There are many R software and bioconductor packages for NGS data analysis, some of them are as follows</p><h3><a name="TOC-Biostrings" id="TOC-Biostrings"></a>Biostrings</h3><p>The Biostrings package from Bioconductor provides an advanced environment for efficient sequence management and analysis in R. It contains many speed and memory effective string containers, string matching algorithms, and other utilities, for fast manipulation of large sets of biological sequences. The objects and functions provided by Biostrings form the basis for many other sequence analysis packages. <a href="http://bioconductor.org/packages/release/bioc/html/Biostrings.html">Documentation</a></p><div><div style="text-align: left;"><div style="color: #000000;"><h4><a name="TOC-IRanges-Overview" id="TOC-IRanges-Overview"></a>IRanges Overview</h4><p>IRanges provides the low-level infrastructure and containers for handling sets of integer ranges within Bioconductor's BioC-Seq domain. Its classes and methods provide support for many more high-level packages like GenomicRanges, ShortRead, Rsamtools, etc. <a href="http://bioconductor.org/packages/release/bioc/html/IRanges.html">Documentation</a></p><div style="text-align: right;"><div style="text-align: left;"><h4><a name="TOC-GenomicRanges-Overview" id="TOC-GenomicRanges-Overview"></a>GenomicRanges Overview</h4><p>The <em>GenomicRanges</em> package serves as the foundation for representing genomic locations within the Bioconductor project. It is built upon the <em>IRanges</em> infrastructure and defines three major data containers - <em>GRanges, GRangesList</em> and <em>GappedAlignments</em> - which are supporting other important BioC-Seq packages including <em>ShortRead, Rsamtools, rtracklayer, GenomicFeatures</em> and <em>BSgenome</em>.&nbsp; Compared to the IRanges container, the GRanges/<em>GRangesList</em> classes are more flexible and extensible to store additional information about sequence ranges, such as chromosome identifiers (sequence space), strand information and annotation data. <a href="http://bioconductor.org/packages/release/bioc/html/GenomicRanges.html">Documentation</a></p></div></div></div></div><h3><a name="TOC-Motif-Discovery" id="TOC-Motif-Discovery"></a>Motif Discovery</h3><h4><a name="TOC-cosmo" id="TOC-cosmo"></a>cosmo</h4><p>The cosmo package allows to search a set of unaligned DNA sequences for a shared motif that may function as transcription factor binding site. The algorithm extends the popular motif discovery tool MEME (Bailey and Elkan, 1995) in that it allows the search to be supervised by specifying a set of constraints that the motif to be discovered must satisfy. <a href="http://bioconductor.org/packages/release/bioc/html/cosmo.html">Documentation</a></p></div><div>
<p><span></span><span></span></p>
<div style="color: #0000ff;"><h4><a name="TOC-BCRANK" id="TOC-BCRANK"></a>BCRANK</h4><p>BCRANK is a method that takes a ranked list of genomic regions as input and outputs short DNA sequences that are overrepresented in some part of the list. The algorithm was developed for detecting transcription factor (TF) binding sites in a large number of enriched regions from high-throughput ChIP-chip or ChIP-seq experiments, but it can be applied to any ranked list of DNA sequences. Documentation</p>
<p><a href="http://bioconductor.org/packages/release/bioc/html/BCRANK.html"></a></p>
<p>rGADEM: <a href="http://bioconductor.org/packages/devel/bioc/html/rGADEM.html">Documentation</a></p><p>MotIV: <a href="http://bioconductor.org/packages/devel/bioc/html/MotIV.html">Documentation</a></p></div><h3><a name="TOC-ShortRead" id="TOC-ShortRead"></a>ShortRead</h3><p>The ShortRead package provides input, quality control, filtering, parsing, and manipulation functionality for short read sequences produced by high throughput sequencing technologies. While support is provided for many sequencing technologies, this package is primairly focused on Solexa/Illumina reads. <a href="http://bioconductor.org/packages/release/bioc/html/ShortRead.html">Documentation</a></p><h3><a name="TOC-Rsamtools" id="TOC-Rsamtools"></a>Rsamtools</h3><p>Rsamtools provides functions for parsing and inspecting samtools BAM formatted binary alignment data. SAM/BAM is quickly becoming a universal standard alignment format, and is now supported by a wide variety of alignment tools. <a href="http://bioconductor.org/help/bioc-views/2.7/bioc/html/Rsamtools.html">Documentation</a></p>
<p><a href="http://samtools.sourceforge.net/">Samtools Website</a><br /> <a href="http://bio-bwa.sourceforge.net/">BWA (Burrows-Wheeler Alignment) Website</a><br /><span style="color: #0000ff;"></span></p>
<div style="color: #000000;">&nbsp;</div></div><div>
<p><span style="color: #000000;">Additional tools for SNP analysis:&nbsp;</span></p>
<p><a href="http://bioconductor.org/help/bioc-views/release/bioc/html/snpMatrix.html">snpMatrix</a></p><h3><a name="TOC-BSgenome" id="TOC-BSgenome"></a>BSgenome</h3><p>BSgenome provides an object oriented infrastructure for interacting with a Biostring based genome sequence. BSgenome packages exist for many common genomes, and can be created to represent custom genomes. See the "How to forge a BSgenome data package" Vignette for instructions to create a new BSgenome package if a prebuilt package does not exist for your organism. <a href="http://bioconductor.org/packages/release/bioc/html/BSgenome.html">Documentation</a></p><h3><a name="TOC-rtracklayer" id="TOC-rtracklayer"></a>rtracklayer</h3><p>rtracklayer provides an interface for exporting annotation feature data to various genome browsers and file formats (such as GFF). See the Small RNA Profiling exercise for an example of using rtracklayer to visualize alignment coverage. <a href="http://bioconductor.org/packages/release/bioc/html/rtracklayer.html">Documentation</a></p><h3><a name="TOC-biomaRt" id="TOC-biomaRt"></a>biomaRt</h3><p>The biomaRt package, provides an interface to a growing collection of databases implementing the BioMart software suite (http:// www.biomart.org). The package enables online retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas. This data is retrieved automatically via the Internet, so it's recommended that you cache the data locally, or check versions if your code will be adversely affected by updates to these data. <a href="http://bioconductor.org/packages/release/bioc/html/biomaRt.html">Documentation</a></p><h3><a name="TOC-ChIP-Seq-Analysis-Packages" id="TOC-ChIP-Seq-Analysis-Packages"></a>ChIP-Seq Analysis Packages</h3><p>Bioconductor provides various packages for analyzing and visualizing ChIP-Seq data. Only a small selection of these packages is introduced here. Additional useful introductions to this topic are: <a href="http://www.bioconductor.org/workshops/2009/SeattleJan09/ChIP-seq/">BioC ChIP-seq Case Study</a> and BioC <a href="http://www.bioconductor.org/help/course-materials/2009/SeattleNov09/ChIP-seq/">ChIP-Seq</a>.</p><h4><a name="TOC-chipseq" id="TOC-chipseq"></a>chipseq</h4><p>The chipseq package combines a variety of HT-Seq packages to a pipeline for ChIP-Seq data analysis. <a href="http://bioconductor.org/packages/release/bioc/html/chipseq.html">Documentation</a></p><h4><a name="TOC-BayesPeak" id="TOC-BayesPeak"></a>BayesPeak</h4><p>BayesPeak is a peak calling package for identifying DNA binding sites of proteins in ChIP-Seq experiments. Its algorithm uses hidden Markov models (HMM) and Bayesian statistical methods. The following sample code introduces the identification of peaks with the BayesPeak package as well as the incorporation of read coverage information obtained by the chipseq package. <a href="http://bioconductor.org/packages/release/bioc/html/BayesPeak.html">Documentation</a> [ <a href="http://www.biomedcentral.com/1471-2105/10/299">Publication</a> ]</p><h4><a name="TOC-PICS" id="TOC-PICS"></a>PICS</h4><p>The PICS package applies probabilistic inference to aligned-read ChIP-Seq data in order to identify regions bound by transcription factors. PICS identifies enriched regions by modeling local concentrations of directional reads, and uses DNA fragment length prior information to discriminate closely adjacent binding events via a Bayesian hierarchical t-mixture model. The following sample code uses the test data set from the above BayesPeak package in order to compare the results from both methods by identifying their consensus peak set. <a href="http://www.bioconductor.org/packages/release/bioc/html/PICS.html">Documentation</a> [ <a href="http://www.hubmed.org/display.cgi?uids=20528864">Publication</a> ]</p><h4><a name="TOC-ChIPpeakAnno" id="TOC-ChIPpeakAnno"></a>ChIPpeakAnno</h4><p>The ChIPpeakAnno package provides. batch annotation of the peaks identified from either ChIP-seq or ChIP-chip experiments. It includes functions to retrieve the sequences around peaks, obtain enriched Gene Ontology (GO) terms, find the nearest gene, exon, miRNA or custom features such as most conserved elements and other transcription factor binding sites supplied by users. The package leverages the biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest and stat packages. <a href="http://bioconductor.org/packages/release/bioc/html/ChIPpeakAnno.html">Documentation</a></p><h4><a name="TOC-Additional-ChIP-Seq-Packages" id="TOC-Additional-ChIP-Seq-Packages"></a>Additional ChIP-Seq Packages</h4><p>DiffBind: <a href="http://www.bioconductor.org/packages/release/bioc/html/DiffBind.html">Documentation</a></p><p>MOSAICS: <a href="http://bioconductor.org/packages/devel/bioc/html/mosaics.html">Documentation</a></p><p>iSeq: <a href="http://bioconductor.org/packages/release/bioc/html/iSeq.html">Documentation</a></p><p>ChIPseqR: <a href="http://bioconductor.org/packages/release/bioc/html/ChIPseqR.html">Documentation</a></p><p>ChiPsim: <a href="http://bioconductor.org/packages/release/bioc/html/ChIPsim.html">Documentation</a></p><p>CSAR: <a href="http://www.bioconductor.org/packages/devel/bioc/html/CSAR.html">Documentation</a></p><p>ChIP-Seq Pipeline: <a href="http://www.bioconductor.org/packages/release/bioc/html/PICS.html">PICS</a>, rGADEM and MotIV (<a href="http://www.rglab.org/pics-and-bioconductor/">developer web site</a>)</p><p>SPP: <a href="http://compbio.med.harvard.edu/Supplements/ChIP-seq/">ChIP-seq processing pipeline</a></p><p><a href="http://compbio.med.harvard.edu/Supplements/ChIP-seq/tutorial.html">SPP Tutorial</a></p><p><a href="http://liulab.dfci.harvard.edu/MACS/index.html">MACS</a></p><p><a href="http://gmdd.shgmo.org/Computational-Biology/ChIP-Seq/download/SIPeS">SIPeS</a></p><h3><a name="TOC-RNA-Seq-Analysis" id="TOC-RNA-Seq-Analysis"></a>RNA-Seq Analysis</h3><h4><a name="TOC-Counting-Reads-that-Overlap-with-Annotation-Ranges-" id="TOC-Counting-Reads-that-Overlap-with-Annotation-Ranges-"></a>Counting Reads that Overlap with Annotation Ranges&nbsp;</h4><p>The GenomicRanges package provides support for importing into R short read alignment data in BAM format (via Rsamtools) and associating them with genomic feature ranges, such as exons or genes. This way one can quantify the number of reads aligning to annotated genomic regions. The package defines general purpose containers for storing genomic intervals as well as more specialized containers for storing alignments against a reference genome. The two main functions for read counting provided by this infrastructure are <span>countOverlaps <span style="color: #000000;"><span>and</span></span> summarizeOverlaps</span>. For their proper usage, it is important to read the corresponding <a href="http://www.bioconductor.org/packages/devel/bioc/vignettes/GenomicRanges/inst/doc/summarizeOverlaps.pdf">PDF manual</a>. <a href="http://bioconductor.org/packages/release/bioc/html/GenomicRanges.html">Documentation</a></p><h4><a name="TOC-Differential-Gene-Expression-Analysis-with-DESeq" id="TOC-Differential-Gene-Expression-Analysis-with-DESeq"></a>Differential Gene Expression Analysis with DESeq</h4><p>The DESeq package contains functions to call differentially expressed genes (DEGs) in count tables based on a model using the negative binomial distribution. It expects as input a data frame with the raw read counts per region/gene of interest (rows) for each test sample (columns).&nbsp; Such a count table can be imported into R or generated from BAM alignment files using the <span>countOverlaps</span> function as introduced above. <a href="http://www.bioconductor.org/packages/release/bioc/html/DESeq.html">Documentation</a></p><h4><a name="TOC-Differential-Gene-Expression-Analysis-with-edgeR" id="TOC-Differential-Gene-Expression-Analysis-with-edgeR"></a>Differential Gene Expression Analysis with edgeR</h4><p>The edgeR package uses empirical Bayes estimation and exact tests based on the negative binomial distribution to call differentially expressed genes (DEGs) in count data.&nbsp;</p>
<p><a href="http://www.bioconductor.org/packages/release/bioc/html/edgeR.html">Documentation</a></p>
<p><span style="color: #000000;">A variety of additional R packages are available for normalizing RNA-Seq read count data and identifying differentially expressed genes (DEG): <br /> </span></p><p><a href="http://bioconductor.org/packages/devel/bioc/html/easyRNASeq.html">easyRNASeq</a> (simplifies read counting per genome feature)</p><p><a href="http://www.bioconductor.org/packages/release/bioc/html/DEXSeq.html">DEXSeq</a> (Inference of differential exon usage);&nbsp;<a href="http://www.bioconductor.org/packages/release/data/experiment/html/parathyroidSE.html">parathyroidSE</a> explains how to generate exon read counts in R</p><p><a href="http://bioconductor.org/packages/release/bioc/html/DEGseq.html">DEGseq</a></p><p><a href="http://www.bioconductor.org/packages/release/bioc/html/baySeq.html">baySeq</a> (also see: <a href="http://www.bioconductor.org/packages/release/bioc/html/segmentSeq.html">segmentSeq</a>)</p><p><a href="http://bioconductor.org/packages/release/bioc/html/Genominator.html">Genominator</a> (<a href="http://www.hubmed.org/display.cgi?uids=20167110">Bullard et al. 2010</a>)</p><div style="text-align: right;"><div style="text-align: left;"><h4><a name="TOC-Detection-of-Alternative-Splice-Junctions" id="TOC-Detection-of-Alternative-Splice-Junctions"></a>Detection of Alternative Splice Junctions</h4>
<p><span style="color: #000000;">Another utility of RNA-Seq experiments is the analysis of splice junctions. The following software suggestions provide this utility:</span></p>
<p><a href="http://woldlab.caltech.edu/rnaseq/">ERANGE<br /> </a><a href="http://tophat.cbcb.umd.edu/">TopHat</a></p><p><a href="http://biogibbs.stanford.edu/%7Ekinfai/SpliceMap/">SpliceMap</a></p><p><a href="http://solidsoftwaretools.com/gf/project/splitseek/">SplitSeek</a></p><h3><a name="TOC-DNA-Methylation-Data-Analysis" id="TOC-DNA-Methylation-Data-Analysis"></a>DNA-Methylation Data Analysis</h3><div><ul>
<li><span style="font-size: 10pt;"><a href="http://www.bioconductor.org/help/course-materials/2012/BiocEurope2012/mattia_pelizzola_methylPipe.pdf">methylPipe</a></span></li>
<li><span style="font-size: 10pt;"><a href="http://www.bioconductor.org/packages/devel/bioc/html/bsseq.html">bsseq</a></span></li>
<li><a href="http://www.bioconductor.org/packages/devel/bioc/html/BiSeq.html">BiSeq</a></li>
<li>Much more under <a href="http://www.bioconductor.org/packages/devel/BiocViews.html#___DNAMethylation">BiocViews</a></li>
</ul></div></div></div><h3><a name="TOC-HT-Seq-Data-Visualization" id="TOC-HT-Seq-Data-Visualization"></a>HT-Seq Data Visualization</h3>
<p><a href="http://www.bioconductor.org/packages/release/bioc/html/ggbio.html">ggbio</a>: ggplot2 extension for genomics data (<a href="http://tengfei.github.com/ggbio/">online manual</a>) <a href="http://www.bioconductor.org/packages/devel/bioc/html/Gviz.html">Gviz</a>:&nbsp;Plotting data and annotation information along genomic coordinates <a href="http://bioconductor.org/packages/release/bioc/html/HilbertVis.html">HilbertVis</a>: Hilbert genome plots</p>
<p><a href="http://bioconductor.org/packages/release/bioc/html/GenomeGraphs.html">GenomeGraphs</a>: Plotting genomic information from Ensembl</p><p><a href="http://www.hubmed.org/display.cgi?uids=18507856">TileQC</a>: Flow Cell Quality Visualization</p><p><a href="http://bioconductor.org/packages/release/bioc/html/rtracklayer.html">rtracklayer</a>: R interface to genome browsers</p><p><a href="http://genoplotr.r-forge.r-project.org/">genoPlotR</a>: Plotting maps of genes and genomes</p><p><a href="http://bioconductor.org/packages/release/bioc/html/Genominator.html">Genominator</a>: Tools for storing, accessing, analyzing and visualizing genomic data.</p><p>&nbsp;</p><p>To install all packages</p><blockquote><p>source("http://bioconductor.org/biocLite.R")<br />biocLite()<br />biocLite(c("ShortRead", "Biostrings", "IRanges", "BSgenome", "rtracklayer", "biomaRt", "chipseq", "ChIPpeakAnno", "Rsamtools", "BayesPeak", "PICS", "GenomicRanges", "DESeq", "edgeR", "leeBamViews", "GenomicFeatures", "BSgenome.Celegans.UCSC.ce2"))</p></blockquote></div>]]></description>
	<dc:creator>John Parker</dc:creator>
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