diff --git a/doc/examples/scalings_example.ipynb b/doc/examples/scalings_example.ipynb index 1a0319b..9476a02 100644 --- a/doc/examples/scalings_example.ipynb +++ b/doc/examples/scalings_example.ipynb @@ -3,29 +3,59 @@ { "cell_type": "code", "execution_count": 1, - "metadata": {}, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "--2022-04-12 10:00:02-- https://data.4dnucleome.org/files-processed/4DNFI3PUO824/@@download/4DNFI3PUO824.pairs.gz\n", - "Resolving data.4dnucleome.org (data.4dnucleome.org)... 34.225.43.243, 34.199.170.160\n", - "Connecting to data.4dnucleome.org (data.4dnucleome.org)|34.225.43.243|:443... connected.\n", - "HTTP request sent, awaiting response... 403 Forbidden\n", - "2022-04-12 10:00:02 ERROR 403: Forbidden.\n", + "--2023-12-18 23:04:28-- https://osf.io/download/crgu8/\n", + "Resolving osf.io (osf.io)... 35.190.84.173\n", + "Connecting to osf.io (osf.io)|35.190.84.173|:443... connected.\n", + "HTTP request sent, awaiting response... 302 FOUND\n", + "Location: https://files.de-1.osf.io/v1/resources/638ue/providers/osfstorage/623993788d53ef082867e2b9 [following]\n", + "--2023-12-18 23:04:28-- https://files.de-1.osf.io/v1/resources/638ue/providers/osfstorage/623993788d53ef082867e2b9\n", + "Resolving files.de-1.osf.io (files.de-1.osf.io)... 35.186.249.111\n", + "Connecting to files.de-1.osf.io (files.de-1.osf.io)|35.186.249.111|:443... connected.\n", + "HTTP request sent, awaiting response... " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "302 Found\n", + "Location: https://storage.googleapis.com/cos-osf-prod-files-de-1/b72f21bb7e21d00541fb3cbc50ef77d67b75970f7d255912ca527fb4c8e5cc0a?response-content-disposition=attachment%3B%20filename%3D%22test_pairs.wp-all.pairs%22%3B%20filename%2A%3DUTF-8%27%27test_pairs.wp-all.pairs&GoogleAccessId=files-de-1%40cos-osf-prod.iam.gserviceaccount.com&Expires=1702937129&Signature=0tM4rWv5RPZjFTYCKzHNbOZoInW3EOidpN5eHp1mlQv%2BWxUbUQ%2BqHDqVmJB4afWQ9CeQpovADOp%2BHNDVxr4GhotEENmyAd7GGdoGRkS%2FeSXM3G1hLxR5H3S5kBWfTVk57pRUXu%2FNj%2FZXOTJo5zKizIdmYlpPZ%2BDZZJvfXuExR3G6OWXcM3P7ufpFe6d53ZxiqpyhxIKVOU4uYo7zwFyxxofGrd5DONsz53sEH15S%2Fc84emZrxaFiQW5%2FEaupoEtLJQHcFc5au3fh8wApS4gtTU%2FDkINvnkyEDXyxND7%2FJDfQ0xJRRjelDXuFVHHDxbIqIfVhQnFK0QMEmlyoBLax1g%3D%3D [following]\n", + "--2023-12-18 23:04:29-- https://storage.googleapis.com/cos-osf-prod-files-de-1/b72f21bb7e21d00541fb3cbc50ef77d67b75970f7d255912ca527fb4c8e5cc0a?response-content-disposition=attachment%3B%20filename%3D%22test_pairs.wp-all.pairs%22%3B%20filename%2A%3DUTF-8%27%27test_pairs.wp-all.pairs&GoogleAccessId=files-de-1%40cos-osf-prod.iam.gserviceaccount.com&Expires=1702937129&Signature=0tM4rWv5RPZjFTYCKzHNbOZoInW3EOidpN5eHp1mlQv%2BWxUbUQ%2BqHDqVmJB4afWQ9CeQpovADOp%2BHNDVxr4GhotEENmyAd7GGdoGRkS%2FeSXM3G1hLxR5H3S5kBWfTVk57pRUXu%2FNj%2FZXOTJo5zKizIdmYlpPZ%2BDZZJvfXuExR3G6OWXcM3P7ufpFe6d53ZxiqpyhxIKVOU4uYo7zwFyxxofGrd5DONsz53sEH15S%2Fc84emZrxaFiQW5%2FEaupoEtLJQHcFc5au3fh8wApS4gtTU%2FDkINvnkyEDXyxND7%2FJDfQ0xJRRjelDXuFVHHDxbIqIfVhQnFK0QMEmlyoBLax1g%3D%3D\n", + "Resolving storage.googleapis.com (storage.googleapis.com)... 142.251.37.123, 142.251.36.91, 142.251.36.123, ...\n", + "Connecting to storage.googleapis.com (storage.googleapis.com)|142.251.37.123|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 564902846 (539M) [application/octet-stream]\n", + "Saving to: ‘./tmp/test.pairs’\n", + "\n", + "./tmp/test.pairs 100%[===================>] 538.73M 163MB/s in 3.5s \n", + "\n", + "2023-12-18 23:04:33 (156 MB/s) - ‘./tmp/test.pairs’ saved [564902846/564902846]\n", "\n" ] } ], "source": [ - "!wget https://data.4dnucleome.org/files-processed/4DNFI3PUO824/@@download/4DNFI3PUO824.pairs.gz -O ./tmp/MicroC.pairs.gz " + "!wget https://osf.io/download/crgu8/ -O ./tmp/test.pairs" ] }, { "cell_type": "code", - "execution_count": 1, - "metadata": {}, + "execution_count": 2, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "%load_ext autoreload\n", @@ -34,8 +64,12 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": {}, + "execution_count": 3, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "import warnings\n", @@ -58,17 +92,25 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": {}, + "execution_count": 4, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ - "pairs_path = '../tmp/MicroC.pairs.gz'" + "pairs_path = './tmp/test.pairs'" ] }, { "cell_type": "code", - "execution_count": 4, - "metadata": {}, + "execution_count": 5, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "mm10_chromsizes = bioframe.fetch_chromsizes('mm10', as_bed=True)\n", @@ -81,8 +123,12 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, + "execution_count": 6, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [ "cis_scalings, trans_levels = scaling.compute_scaling(\n", @@ -90,34 +136,36 @@ " regions=mm10_arms,\n", " chromsizes=mm10_chromsizes,\n", " dist_range=(10, 1000000000), \n", - " n_dist_bins=128,\n", + " n_dist_bins_decade=8,\n", " chunksize=int(1e7),\n", - " cmd_in=\"gzip -dc \"\n", + " #cmd_in=\"gzip -dc \"\n", " )\n", "\n", "# calculate average trans contact frequency _per directionality pair_\n", "# convert from int to float64 to avoid overflow\n", "avg_trans = (\n", " trans_levels.n_pairs.astype('float64').sum() \n", - " / trans_levels.np_bp2.astype('float64').sum()\n", + " / trans_levels.n_bp2.astype('float64').sum()\n", ")\n" ] }, { "cell_type": "code", - "execution_count": 6, - "metadata": {}, + "execution_count": 7, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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", 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" ] }, - "metadata": { - "needs_background": "light" - }, + "metadata": {}, "output_type": "display_data" } ], @@ -185,28 +233,24 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "vscode": { + "languageId": "python" + } + }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { - "display_name": "Python 3.10", + "display_name": "main", "language": "python", - "name": "python310" + "name": "main" }, "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.4" + "name": "", + "version": "" } }, "nbformat": 4, diff --git a/pairtools/cli/scaling.py b/pairtools/cli/scaling.py index 5b0d927..0b8512a 100644 --- a/pairtools/cli/scaling.py +++ b/pairtools/cli/scaling.py @@ -5,7 +5,7 @@ import click import pandas as pd -from ..lib import fileio, pairsam_format, headerops +from ..lib import fileio from . import cli, common_io_options from ..lib.scaling import compute_scaling @@ -39,21 +39,21 @@ @click.option( "--dist-range", type=click.Tuple([int, int]), - default=(10, 1_000_000_000), + default=(1, 1_000_000_000), show_default=True, required=False, help="Distance range. ", ) @click.option( - "--n-dist-bins", + "--n-dist-bins-decade", type=int, - default=128, + default=8, show_default=True, required=False, - help="Number of distance bins to split the distance range. ", + help="Number of bins to split the distance range in log10-space, specified per a factor of 10 difference.", ) @common_io_options -def scaling(input_path, output, view, chunksize, dist_range, n_dist_bins, **kwargs): +def scaling(input_path, output, view, chunksize, dist_range, n_dist_bins_decade, **kwargs): """Calculate pairs scalings. INPUT_PATH : by default, a .pairs/.pairsam file to calculate statistics. @@ -63,10 +63,10 @@ def scaling(input_path, output, view, chunksize, dist_range, n_dist_bins, **kwar Output is .tsv file with scaling stats (both cis scalings and trans levels). """ - scaling_py(input_path, output, view, chunksize, dist_range, n_dist_bins, **kwargs) + scaling_py(input_path, output, view, chunksize, dist_range, n_dist_bins_decade, **kwargs) -def scaling_py(input_path, output, view, chunksize, dist_range, n_dist_bins, **kwargs): +def scaling_py(input_path, output, view, chunksize, dist_range, n_dist_bins_decade, **kwargs): if len(input_path) == 0: raise ValueError(f"No input paths: {input_path}") @@ -93,13 +93,13 @@ def scaling_py(input_path, output, view, chunksize, dist_range, n_dist_bins, **k regions=view, chromsizes=None, dist_range=dist_range, - n_dist_bins=n_dist_bins, + n_dist_bins_decade=n_dist_bins_decade, chunksize=chunksize, ) summary_stats = pd.concat([cis_scalings, trans_levels]) # save statistics to the file - summary_stats.to_csv(outstream, sep="\t") + summary_stats.to_csv(outstream, sep="\t", index=False) if instream != sys.stdin: instream.close() diff --git a/pairtools/lib/__init__.py b/pairtools/lib/__init__.py index 38a9b6b..adce296 100644 --- a/pairtools/lib/__init__.py +++ b/pairtools/lib/__init__.py @@ -2,6 +2,7 @@ from . import dedup from . import filterbycov from . import headerops +from . import pairsio from . import pairsam_format from . import parse from . import parse_pysam diff --git a/pairtools/lib/fileio.py b/pairtools/lib/fileio.py index 2bd5f46..c49bc10 100644 --- a/pairtools/lib/fileio.py +++ b/pairtools/lib/fileio.py @@ -3,7 +3,6 @@ import subprocess import sys - class ParseError(Exception): pass @@ -235,3 +234,32 @@ def close(self, timeout=None): self._stream.close() retcode = self._proc.wait(timeout=timeout) return retcode + + +def get_stream_handlers(instream): + """ + Get the readline and peek functions for the provided input stream. + + Parameters: + instream (file-like object): The input stream to get the handlers for. + + Returns: + tuple: A tuple containing the following elements: + - readline_f (function): The readline function for the input stream. + - peek_f (function): The peek function for the input stream. + + Raises: + ValueError: If the peek function cannot be found for the provided stream. + """ + readline_f, peek_f = None, None + if hasattr(instream, "buffer"): + peek_f = instream.buffer.peek + readline_f = instream.buffer.readline + elif hasattr(instream, "peek"): + peek_f = instream.peek + readline_f = instream.readline + else: + raise ValueError("Cannot find the peek() function of the provided stream!") + return readline_f, peek_f + + diff --git a/pairtools/lib/headerops.py b/pairtools/lib/headerops.py index ecfaa2f..14624df 100644 --- a/pairtools/lib/headerops.py +++ b/pairtools/lib/headerops.py @@ -9,7 +9,7 @@ from .. import __version__ from . import pairsam_format -from .fileio import ParseError +from .fileio import ParseError, get_stream_handlers from .._logging import get_logger @@ -21,19 +21,6 @@ COMMENT_CHAR = "#" -def get_stream_handlers(instream): - # get peekable buffer for the instream - readline_f, peek_f = None, None - if hasattr(instream, "buffer"): - peek_f = instream.buffer.peek - readline_f = instream.buffer.readline - elif hasattr(instream, "peek"): - peek_f = instream.peek - readline_f = instream.readline - else: - raise ValueError("Cannot find the peek() function of the provided stream!") - return readline_f, peek_f - def get_header(instream, comment_char=COMMENT_CHAR, ignore_warning=False): """Returns a header from the stream and an the reaminder of the stream diff --git a/pairtools/lib/pairsio.py b/pairtools/lib/pairsio.py new file mode 100644 index 0000000..68170c6 --- /dev/null +++ b/pairtools/lib/pairsio.py @@ -0,0 +1,49 @@ +import pandas as pd + +from . import fileio, headerops + +def read_pairs(pairs, nproc=3, cmd_in=None, **kwargs): + """ + Reads a file with .pairs format and returns a header, a dataframe of pairs, and chromsizes. + + Parameters: + pairs (str or file-like object): A path to a .pairs file to read or an open file-like object/handle. + nproc (int): Number of processes to use for reading the file. Default is 3. + cmd_in (str): The command to be used for reading the file. Default is None. + + **kwargs: Additional keyword arguments to be passed to pd.read_csv. Useful options include: + - chunksize (int): If specified, return an iterable object of type TextFileReader that reads in chunks of lines. + - usecols (list-like or callable): Return a subset of the columns. If list-like, all elements must either be positional or strings. If callable, the callable function will be evaluated against the column names, returning names where the callable function evaluates to True. + + Returns: + tuple: A tuple containing the following elements: + - pairs_df (pd.DataFrame): A pandas DataFrame with pairs. + - header (list of str): The original header of the pairs file. + - chromsizes (dict): A dictionary containing chromosome sizes extracted from the header. + """ + pairs_stream = ( + fileio.auto_open( + pairs, + mode="r", + nproc=nproc, + command=cmd_in, + ) + if isinstance(pairs, str) + else pairs + ) + + header, pairs_body = headerops.get_header(pairs_stream) + cols = headerops.extract_column_names(header) + + chromsizes = headerops.extract_chromsizes(header) + + pairs_df = pd.read_csv( + pairs_body, + header=None, + names=cols, + sep="\t", + dtype={"chrom1": str, "chrom2": str}, + **kwargs + ) + + return pairs_df, header, chromsizes \ No newline at end of file diff --git a/pairtools/lib/scaling.py b/pairtools/lib/scaling.py index 9432434..7e89b46 100644 --- a/pairtools/lib/scaling.py +++ b/pairtools/lib/scaling.py @@ -2,6 +2,7 @@ import pandas as pd from .regions import assign_regs_c +from . import pairsio import bioframe @@ -207,7 +208,8 @@ def bins_pairs_by_distance( if not keep_unassigned: pairs_reduced_df = (pairs_reduced_df - .query('(start1 >= 0) and (end1 > 0) and (start2 >= 0) and (end2 > 0)') + .query('(start1 >= 0) and (start2 >= 0)') + # do not test for end1 and end2, as they can be -1 if regions and not specified .reset_index(drop=True)) pairs_reduced_df["min_dist"] = np.where( @@ -225,10 +227,14 @@ def bins_pairs_by_distance( # importantly, in the future, we may want to extend the function to plot scalings # for pairs from different regions! - pairs_for_scaling_mask = ( + cis_region_pairs = ( (pairs_reduced_df.chrom1 == pairs_reduced_df.chrom2) & (pairs_reduced_df.start1 == pairs_reduced_df.start2) & (pairs_reduced_df.end1 == pairs_reduced_df.end2) + ) + + pairs_for_scaling_mask = ( + cis_region_pairs & (pairs_reduced_df.min_dist > 0) & (pairs_reduced_df.max_dist < np.iinfo(np.int64).max) ) @@ -262,7 +268,7 @@ def bins_pairs_by_distance( if ignore_trans: pairs_no_scaling_counts = None else: - pairs_no_scaling_df = pairs_reduced_df.loc[~pairs_for_scaling_mask] + pairs_no_scaling_df = pairs_reduced_df.loc[~cis_region_pairs] pairs_no_scaling_counts = pairs_no_scaling_df.groupby( by=[ @@ -328,71 +334,61 @@ def compute_scaling( pairs, regions=None, chromsizes=None, - dist_range=(int(1e1), int(1e9)), - n_dist_bins=8 * 8, + dist_range=(int(1e0), int(1e9)), + n_dist_bins_decade=8, chunksize=int(1e7), ignore_trans=False, keep_unassigned=False, filter_f=None, - nproc_in=1, - cmd_in=None, + nproc_in=4, ): """ - Main function for computing scaling. + Compute the contact-frequency-vs-distance (aka "scaling") curve from a table of contacts. Parameters ---------- - pairs: pd.DataFrame, stream of fiel paht with pairs. - regions: bioframe viewframe, anything that can serve as input to bioframe.from_any, or None - chromsizes: additional dataframe with chromosome sizes, if different from regions - dist_range: (int, int) tuple with distance ranges that will be split into windows - n_dist_bins: number of logarithmic bins - chunksize: size of chunks for calculations - ignore_trans: bool, ignore trans or not - keep_unassigned: bool, keep pairs that are not assigned to any region - filter_f: filter function that can be applied to each chunk - nproc_in - cmd_in + pairs : pd.DataFrame or str or file-like object + A table with pairs of genomic coordinates representing contacts. + It can be a pandas DataFrame, a path to a pairs file, or a file-like object. + regions : bioframe viewframe or None, optional + Genomic regions of interest. It can be anything that can serve as input to bioframe.from_any, + or None if not applicable. + chromsizes : pd.DataFrame or None, optional + Additional dataframe with chromosome sizes, if different from regions. + dist_range : tuple of int, optional + The range of distances to calculate the scaling curve. Default is (10, 1000000000). + n_dist_bins : int, optional + The number of distance bins per order of magnitude in a log10-space. Default is 8. + chunksize : int, optional + Size of chunks for calculations. Default is 10000000. + ignore_trans : bool, optional + Ignore trans interactions or not. Default is False. + keep_unassigned : bool, optional + Keep pairs that are not assigned to any region or not. Default is False. + filter_f : function or None, optional + A function that to filter contacts. Default is None. + nproc_in : int, optional + Number of processes to use for reading pairs file. Default is 1. Returns ------- - + sc : pd.DataFrame + Scaling information for each distance bin. + trans_counts : pd.DataFrame or None + Trans interaction counts for each distance bin. None if ignore_trans is True. """ - dist_bins = geomspace(dist_range[0], dist_range[1], n_dist_bins) + dist_bins = geomspace( + dist_range[0], + dist_range[1], + int(np.round(np.log10(dist_range[1]/dist_range[0])*n_dist_bins_decade)) + ) if isinstance(pairs, pd.DataFrame): pairs_df = pairs elif isinstance(pairs, str) or hasattr(pairs, "buffer") or hasattr(pairs, "peek"): - from . import fileio, headerops - - pairs_stream = ( - fileio.auto_open( - pairs, - mode="r", - nproc=nproc_in, - command=cmd_in, - ) - if isinstance(pairs, str) - else pairs - ) - - header, pairs_body = headerops.get_header(pairs_stream) - - cols = headerops.extract_column_names(header) - - if chromsizes is None: - chromsizes = headerops.extract_chromsizes(header) - - pairs_df = pd.read_csv( - pairs_body, - header=None, - names=cols, - chunksize=chunksize, - sep="\t", - dtype={"chrom1": str, "chrom2": str}, - ) + pairs_df, _, _ = pairsio.read_pairs(pairs, nproc=nproc_in, chunksize=chunksize) else: raise ValueError( "pairs must be either a path to a pairs file or a pd.DataFrame" @@ -412,12 +408,14 @@ def compute_scaling( ) sc = sc_chunk if sc is None else sc.add(sc_chunk, fill_value=0) + trans_counts = ( trans_counts_chunk if trans_counts is None else trans_counts.add(trans_counts_chunk, fill_value=0) ) + # if not (isinstance(regions, pd.DataFrame) and # (set(regions.columns) == set(['chrom', 'start','end']))): # raise ValueError('regions must be provided as a dict or chrom-indexed Series of chromsizes or as a bedframe.') @@ -429,22 +427,54 @@ def compute_scaling( if not ignore_trans: trans_counts.reset_index(inplace=True) - trans_counts["n_bp2"] = (trans_counts["end1"] - trans_counts["start1"]) * ( + trans_counts["n_bp2"] = ( + (trans_counts["end1"] - trans_counts["start1"]) * ( trans_counts["end2"] - trans_counts["start2"] - ) + )) return sc, trans_counts -def norm_scaling_factor(bins, cfreqs, anchor=1.0, binwindow=(0, 3)): - i = np.searchsorted(bins, anchor) - return cfreqs[i + binwindow[0] : i + binwindow[1]].mean() +def norm_scaling_factor(bins, cfreqs, norm_window): + """ + Calculate the normalization factor for a contact-frequency-vs-distance curve, + by setting the average contact frequency in a specified range of distances to 1.0. + + Args: + bins (array-like): The distance bins. + cfreqs (array-like): The contact frequencies. + norm_window (tuple of float): A tuple with the range of distances to use for normalization. + + Returns: + float: The normalization scaling factor. + """ + + lo, hi = np.searchsorted(bins, norm_window) + return cfreqs[lo:hi+1].mean() + +def norm_scaling(bins, cfreqs, norm_window, log_input=False): + """ + Normalize a contact-frequency-vs-distance curve, by setting the average contact frequency + in a given window to 1.0. -def norm_scaling(bins, cfreqs, anchor=1.0, binwindow=(0, 3)): - return cfreqs / norm_scaling_factor(bins, cfreqs, anchor, binwindow) + Args: + bins (array-like): The distance bins. + cfreqs (array-like): The contact frequencies. + norm_window (tuple of float): A tuple with the range of distances to use for normalization. + log_input (bool, optional): Whether the input contact frequencies were log-transformed. Defaults to False. + Returns: + float or array-like: The normalized contact frequencies. + """ + + norm = norm_scaling_factor(bins, cfreqs, norm_window) + if log_input: + return cfreqs - norm + else: + return cfreqs / norm + def unity_norm_scaling(bins, cfreqs, norm_range=(1e4, 1e9)): bin_lens = np.diff(bins) bin_mids = np.sqrt(bins[1:] * bins[:-1]) diff --git a/tests/test_scaling.py b/tests/test_scaling.py index 8991f24..718a133 100644 --- a/tests/test_scaling.py +++ b/tests/test_scaling.py @@ -22,4 +22,4 @@ def test_scaling(): output = pd.read_csv(io.StringIO(result), sep="\t", header=0) - assert output["n_pairs"].sum() == 5 + assert output["n_pairs"].sum() == 7 # double unmapped pairs are currently ignored by lib.scaling